I RFTA and the majority of the complaints are about call center metrics and the pressure to ration care. These are real concerns about misuse of metrics, but not AI. The AI empathy thing was a 2024 pilot that was discontinued.
FWIW my wife works for Kaiser and finds a lot of value in the the medical LLM tools available to her. She tells me being able to do live translation, summarize notes, and quickly get comprehensive answers save her time and help her give better care. Her older patients also frequently come in bringing AI-powered alerts from their apple watches that detected cardiac events.
It's annoying that we use broad terms to describe a set of technologies that in some ways can be problematic and in another ways are very beneficial. We gotta evaluate each of these as they come rather than talk about blanket bans.
Being close relative for several med and care workers we have discussed it a lot and consensus is that it really depends. For example relying on LLM summaries sounds great until it doesn't. It doesn't matter whether you misunderstand LLM summary or LLM "misunderstands" you – there are real risks involved, and you wouldn't want them to weigh on your conscience if they were to materialize.
Relying on LLM to summarize things for you has one more issue. To outsiders, this seems like a tedious process, but is actually very important part of the thought process. Wording your thoughts and writing these down helps people to discover new aspects of the problem. It's how people learn.
At the moment consensus is that it must not be banned, but also not mandated in any way - people must take responsibility, and they must be able to decide for themselves where and when the LLM use is justified and where it is not.
I don’t think that it is possible to both allow the use of LLM and not mandate them in modern metric driven work places. Either you ban them or you force people to use them for game theoretic reasons: they are slower than their peers and quality of the work is harder to measure than quantity. All you achieve is shifting the blame to the employees if the LLM messes up. Come to think of it, that probably is a highly desirable outcome for the decision makers, so perhaps that will actually be the policy that becomes universally adopted.
> I don’t think that it is possible to both allow the use of LLM and not mandate them in modern metric driven work places.
What I’d personally be most concerned about would be the risk of bad models instead of SOTA being used which would be especially error and hallucination prone.
If you’re gonna do it, do it right. Otherwise don’t bother at all.
Things like this are (sadly) common (and age-old) problems with automation and computerization. (For a vivid account of this phenomenon, check out the novel _Close to the Machine_, by Ellen Ullman.)
As executives and analysts increasingly use the "AI" craze to push automation and computerization (and layoffs) generally, even aside from AI proper, it should not be surprising that the individuals and groups opposing those moves also use the same labels.
The lack of precision in language here sucks. It sucks for the discourse and it also sucks when it comes to focusing anger and productive energy on the core problems (obfuscation of human responsibility, erosion of human agency, declining institutional flexibility, deprofessionalization, etc.). But it doesn't begin with the critics of AI.
It's a feature. Or at least, a perk. If they want to claim this new shiny rock is AI and people buy it, then of course it's in their best interest to keep the black box mysterious. Being subterfuge for muddying the discourse of critique is just a nice side bonus.
But it is only a perk for the scam artists who benefit from that.
Yes, it makes sense that the confusion aligns with their interests, and they are unavoidably a big part of the conversation. But it remains a problem for the non-overlapping group of people who actually value the social contract, and for us finding a solution which helps take one more step to defeat the scammers remains valuable.
Near as I can tell, like crypto, 90% of the ‘discussion’ has been taken over by scam artists, and any folks trying to have a non-scam discussion get yelled at by everyone else.
I am very interested in your reading of Close to the Machine. I read it myself a couple of years ago and found it a wonderful telling of the early days of tech, with overtones of the "technology workplace" that were still very true to this day. I did not pick up on any commentary on automation or computerization, outside of the general critique of bureaucratic systems that alienate you from the outcomes of your labor.
Do you have anything I could read to understand your reading better? I would love to be able to dive back into one of my favorite books with a new lead.
There is still a categorical difference between how they are being used. Specifically analytic vs generative. Generative AI (LLMs and image generators) are the ones people have issues with - pretty much nobody cares about ML processing for analysis.
There’s a bit of a grey area, for example speech recognition. Would you classify that as analytic or generative? Whisper and speech LLMs work pretty well, but can completely make up stuff that wasn’t in the audio at all (see e.g. “thank you for watching” transcribed during silence). Other approaches are closer to the acoustic evidence but may make other mistakes (especially wrongly transcribing long tail, low frequency terms). Pick your poison.
> pretty much nobody cares about ML processing for analysis.
I work in a bank and a can tell you that the customers absolutely hate ML when it rejects their loan application. Over the pond in the US, I have an impression that the fico score is not exactly popular either, but I have no first hand experience.
It is correct to argue about misleading terminology. "AI" contains the word "intelligence", and for instance logistic regression algorithm is not intelligent, while it is clearly ML, since machine learns something. As Machine learning is broader category, it should include Artificial Intelligence, not vice versa.
Also, 'every single course' is perhaps an overstatement - a course that I co-authored tries to get it right from the first principles.
The machine is learning something so that it can produce outputs based on its learned knowledge. At a high level that seems to be very clearly AI. What am I missing here? You’re probably right, I’m asking genuinely.
It's a matter of definitions, but I can at least understand someone wanting to make a distinction between reactive and non-reactive 'AI' (such as data filters).
There's overlap and edge cases, though: Maybe you have a program that summarizes texts. One could argue that's no different from a passive filter. But can you then ask questions about the text? That's unquestionably AI.
To me they're the same thing. If there's a bunch of training data that is fed into a system that creates a model, then it's not traditional programming, where someone laboriously writes out if statements by hand. AI and ML aren't, as far as I'm aware, rigorously specifically defined terms. They're words that marketing picked up and ran with it. To me, what matters is: is there a black box somewhere in the system that's a bag of numbers, or is it code that a human could dig in and read.
There are both ML that is not AI, and AI that is not ML.
For example, if you pick them manually, decision trees can be AI but not ML. Video game character behavior is a trivial example.
Eliza for example is also not ML, but could be called AI.
Likewise, there is ML that is not AI. Such is debatable, because you could always argue that using machine-learning on anything results in intelligence. The way I see it, things like image enhancement or voice replacement are not artificial intelligence at all. I probably could not define a hard line where it becomes artificial intelligence though.
I don’t know what the op meant by manually picking but the expert systems of the 80s and case based reasoning systems of the 90s used fairly static decision functions and were explicitly called AI at the time.
AI and ML have very clear definitions[1]. ML has been a subset of AI, always has been. Latest marketing or "scare quotes" doesn't/shouldn't change that. Especially not in a technical forum like HN.
Laypeople are changing how “AI” is used in common language, like they previously did for “algorithm” and “crypto”.
The textbook definition of AI is a system that solves problems that are difficult for humans. Whether the approach uses formal logic, machine learning, neural networks as a special case of machine learning, optimization, search problems, etc. does not matter.
I never heard people calling machine learning "AI" until large language models made it trivial to market it as such. Like, I remember back when Netflix, for instance, was going around advertising how machine learning (not AI) powers their recommendations.
You should listen better. The University of Edinburgh had an entire Department of Artificial Intelligence when I was an undergrad there in the 1990s, and one of the things it researched was machine learning.
That example kind of illustrates my point though? ML being in an AI book doesn't mean ML is AI, just as being in the dairy section does not make almond milk dairy.
It illustrates that some people can’t distinguish between a useful label by association for the general public, and their own desperate compulsion to litigate hair-splitting category distinctions.
Someone who was truly on the ball on this matter might’ve observed that Edinburgh in the 90s was so balkanized by internecine personality conflicts that most research that might later be strictly labelled “machine learning” actually took place in adjacent units and not directly under the DAIry. But I suppose you haven’t heard that, either.
Exactly what do you think my argument is? It's not "I didn't hear of [anything], therefore it doesn't exist / is not admissible". It's roughly "I didn't see machine learning referred to as 'AI' for years, until LLMs happened, at which point most companies that used to say 'machine learning' started calling the same things 'AI'".
You don't have to be snarky about it. I've heard it's okay to not know things. Is that wrong too?
Also:
> desperate compulsion to litigate hair-splitting category distinctions.
All I'm saying is that neither one is a strict subset of the other. Even though AI and ML are incredibly related to the point of even mostly overlapping in practice, they're not the same thing! AI is an outcome and ML is a mechanism. You can use the mechanism to achieve the outcome, or you can use a different mechanism to achieve the outcome, or you can use the mechanism to achieve a different outcome. That's all. If that's a hair-splitting category distinction to you, then so be it.
Ed: I disagree. My recollection is that machine learning was routinely sold as “AI” even when it obviously wasn’t. (IBM’s Watson was good at Jeopardy but not real medical applications.)
This isn’t exactly the same, but nothing in the book Paradigms of Artificial Intelligence would be considered AI today.
You must be thinking of a different machine learning. All the on-device machine learning, backend machine learning, OCR, etc. was all called "machine learning" before LLMs. Yes, the field of artificial intelligence still existed, often used machine learning, and called the result "AI". But Apple would call keyboard prediction machine learning. Microsoft would call OCR machine learning. YouTube called machine transcription machine learning. Google called camera image enhancement machine learning.
Microsoft now calls everything AI (actually mostly "Copilot"). YouTube now calls everything AI (including genuine LLMs and generative features, but also everything it used to call machine learning). Google now calls everything AI (including everything it used to call machine learning). Apple is seemingly the only one immune.
My argument is not that no one ever used "AI" to refer to a product that utilized machine learning, but rather that the term of art in the industry for machine learning itself was actually "machine learning", not "AI", until LLMs took over and made it "AI".
You would not pull a library off the shelf for "AI", it would be for machine learning. You would not implement and perform "AI", but machine learning. Even central parts of the AI ecosystem like PyTorch advertise as being for "deep learning", which is a subset of machine learning. Not "AI".
Counter example, the book that is the foundation of much coursework and learning for people in AI, has a whole section on "Machine Learning" with all that k-means and such in there - https://aima.cs.berkeley.edu/
I'm really not sure how that's a counterexample. The section is called machine learning, not AI. Machine learning is a useful tool for artificial intelligence, so I'd be surprised if a book about AI did not talk about it.
I'm saying that Machine Learning was borne of AI from the very beginning. ML has become specialized enough that we may later (much much later) declare it somehow larger/separate/overlapping, but it originated from AI as the generic umbrella.
Thank you. I was starting to think the history revision was almost true, but your recollection is very much in sync with my own. Everything was machine learning, nobody talked about AI unless it was for research, now marketing has changed that, unfortunately.
> Everything was machine learning, nobody talked about AI unless it was for research
Machine learning was AI. The specific wording was a branding choice, because "AI" was a deeply stigmatized brand. ( https://en.wikipedia.org/wiki/AI_winter ) But there was not a conceptual division.
There's a close analogue to how modern genetic researchers are happy to tell you that your genome is not informative as to your "race", but it is informative as to your "ancestry".
It's stupid because there's no formal definition of what counts as AI, so we repeat the same conversation every time. Hence the joke ML is just AI that works.
There's a book from 1995, called Artificial Intelligence: A Modern Approach, by by Stuart Russell and Peter Norvig, which gives the definition "AI is the study of agents that receive percepts from the environment and perform actions." but doesn't define intelligence.
For a long time, AI was a bad word that stood for unfulfilled promise. See AI Winter. Hence, researchers strictly avoided the term while still working on learning algorithms, the same that power LLM training.
I took one longer ago than that and it wasn't all perceptrons and neural networks. It included other things too, like: planning, search methods, inference engines, decision trees, ...
Calling things "robots" is more about the amount of movement. Spinning in place like a washing machine sprayer isn't enough to qualify.
A paint conveyer belt is not a robot. A sprinkler system is not a robot. A CnC machine might be a robot. A conveyer belt that sorts items might be a robot. A roomba is a robot. And all of these function just fine.
I think of robots as general purpose, machines are specific purpose. When it works, we make it single purpose because that’s far far cheaper than general purpose.
>> Cardiac events from Apple Watches is not “AI” though
> It would have been, 20 years ago.
No, it would have been called what it is both then and now; an asynchronous message emitted by a device having sensors capable of detecting when to do so.
I understand the frustration, but it's justifiable for the public to be concerned about AI in general because the novelty of the technology means that boundaries between beneficial and problematic usage is not yet stable and well defined. For existing technologies consensus on that has usually been reached, although it changes over time. In many cases we may not yet have enough information to decide.
Nor is this a trivial decision. AI has the potential to change society and economic relations as profoundly as the industrial revolution, or the invention of the printing press.
These boundaries are also contested, as interests which benefit from a particular application are different from those whose interests are harmed. Society needs to identify which usages have a net benefit.
It also needs to define which usages cause "absolute" harms which is will consider unacceptable regardless of benefits to some parties. Such as, potentially, reductions in personal autonomy, increased leverage or dominance by government or private interests.
Not only that, but data and models which were collected/ built for one purpose can easily be adapted for others.
This is also basically now happening all at once in many domains.
In short, you can expect there to be tension over these boundaries for some time. It's not realistic to expect that others will agree with your personal perception of which applications are "obviously" unproblematic.
>> It's annoying that we use broad terms to describe a set of technologies that in some ways can be problematic and in another ways are very beneficial. We gotta evaluate each of these as they come rather than talk about blanket bans.
I totally get it. I think few years, if some company said they record and transcribe every meeting/interview they take, it would be concerning. Now, its somewhat a norm for people to use these AI meeting tools which record everything you say and then go back to recording and exactly what people said. I'd call it surveillance than AI
everyone is very thirsty for AI hate, so its not unexpected. Today its a mixed bag of corpo hate, anxiety about the future, inequality and traditional class warfare, combined with the typical technical ignorance.
I would expect companies to blend shit metrics with AI systems, if not at Kaiser then at other places. People lack imagination and using AI to monitor your workforce has to be one of the possibly worst ways to use it. Alternatively some dickhead will "lean startup" their way into measuring "performance" in such a way with the "help" of AI that they will do something even worse.
> Today its a mixed bag of corpo hate, anxiety about the future, inequality and traditional class warfare, combined with the typical technical ignorance.
Are there no actual problems with what it promises/how we're expected to use it at work/how it is used against us by people who use it at work? Is it just anxieties and feelings, that aren't actually grounded in anything? Everything's getting better for everyone, no downsides?
Nobody knows what's actually going to happen, so we assume the worst. It's like how we like to shit on Amazon without appreciating how some people have benefitted from being able to side-step the gatekeepers of old by being able to go straight to market themselves without needing bricks and mortar. Humanity, fear and distrust are best of friends. That's what I'm calling out, I have no interest in playing Nostradamus.
I think OP is a good case in point where people are blaming AI but really the issue here is the human in the loop, the person implementing these abhorrent policies that happen to be powered by AI.
“There is always a point at which the Amodei ceases to manipulate the media gestalt. A point at which the capital misallocation may well escalate, but beyond which the Amodei has become symptomatic of the capital markets themselves. Amodei as we ordinarily understand it is innately media-related. The Hangzhou hackers differ from other AI engineers precisely in their degree of self-consciousness, in their awareness of the extent to which media divorce the act of giving Amodei fuckin money from the original sociopolitical intent.”
I personally will not use a provider who uses llm tools. I know it makes me and my coworkers less careful and lazier. Qualities I dont want in a health care providor.
Ive actually moved primary care physicians over this once already, found the oldest guy I could who barely knows how to use a laptop but spends a bunch of extra time with me.
Funny how we assess risk. Not criticising you - I'm as irrational as the next guy - but "I found the oldest doctor I could" seems like it has a different set of risks baked in.
The older the doctor the more experience they have, but also their knowledge is more outdated (how many keep up with medical journals?) and their brain is worse at learning and connecting dots so I'm not sure I'd choose the oldest I could find.
Medicine however is not the same. Nor is our understanding of the human body.
For example, a 60 yo doctor would have been born before the first heart transplant, the recipient lasted 18 days. Now 5000 are performed each year and after 5 years 80% of recipients are alive.
Consider ambient listening in hospitals. Encounters are recorded then AI creates a summary. Those audio recordings then can be used for any other purpose. Consider the ramifications, A panopticon of metrics derived from AI. Imagine a AI used as a review tool across all ecounters a nurse performed in a year.
IA will transform how data is stored in healthcare. It's going to move towards the data lake model storing information in its raw form for post analysis.
If a human’s performance for 40 plus hours a week can be reduced to a performance score, that too in a field like healthcare, that alone feels weird. Sure there needs to be some way to reward people/evaluate their work etc, but I dunno if management by metrics is the best way, especially when those numbers are calculated by an algorithm.
Where has all the empathy gone? And common sense? :(
> Where has all the empathy gone? And common sense? :(
Contrary to popular belief, I don't think common sense has gone away. It just has been deprioritized at the altar of profit. It'll be visible loud and clear the very instant if/when the lives of the assholes chasing profits was on the line.
>> If a human’s performance for 40 plus hours a week can be reduced to a performance score ...
>> Where has all the empathy gone? And common sense? :(
> Contrary to popular belief, I don't think common sense has gone away. It just has been deprioritized at the altar of profit.
Or perhaps it has been left to starve due to apathy and an unrelenting pursuit to reduce the difficult job of leadership into a much simpler one based on arbitrary numeric values which are defensible to those higher in the managerial food chain.
Defensible on account of discharging their relentless duties of generating shareholder value within legal limits... i.e. profit.
The fact that it is done in a lopsided way at the expense of everything else is just sign of societal decline due to deification of money and letting the tiger of capitalism roam without boundaries.
sadly, this is happening more as medicine and healthcare become more and more corporate. Seeing this as hospitals all get acquired into these mega health systems (ostensibly to fight the now merged mega health insurance companies), that then like to throw their weight around.
a bit upside down - wealth extraction is a measure of power.
development of power can be based on all sorts of things, it depends on the framework.
a nurse who is utterly incompetent will be fired quickly.
after a certain threshold though, obviously, competition won't be about 'ability' so much - but there are baseline ability and professionalism thresholds.
It’s somewhat the point of democracy to maintain a limit on rent seekers’ and wealth extractors’ power on the political process. It should come as no surprise that the individuals who have grifted and extorted their way into power are also fiercely antidemocratic. The xenophobes and bigots that have hitched their wagons are equally deplorable.
I'ma keep it creamy with you, both parties have had the kind of political majority required to clamp down on the corporatization of our society, and neither have so much as paid lip service to doing so. You want to be mad at the current administration by all means there's fertile ground, but don't waste anyone's time blaming them for a situation that's been decades in the making with both major political parties pushing in tandem to realize it.
The last time was 2009-2010 for the Democrats. The Republicans have never held 60 seats.
But the real crime is that the left never exploited that. If I was in charge, I’d have mountains of draft legislation vetted, proofread, run by every lawmaker, and printed out years before any potential majority just in case it ever came about. Whoever was in charge of the DNC in 2009 should feel ashamed of letting a generational advantage largely go to waste.
Fillibuster is a senate procedure rule. That's about the weakest a thing could be. At any point Democrats could have gotten rid of the filibuster with a 51 majority.
Democrats would much rather let congress do nothing than do something. It's hurt their reputation so much.
It's an oddly convenient tool. Especially if you value passing good laws less than allowing bad laws to pass. And it seems like our government is indeed run like a business; highly risk adverse to the point where it's better to spend more time in meetings than doing actual work. These people won't be chastised as much as they deserve for doing nothing, so that won't push them either.
I like the idea of the filibuster, but like most things it degraded from a way to force the stand to consider your ideas at all costs, to a blatant stalling tactic, to a lazy button to push against anything you disagree with. I'd rather throw it out these days than keep it, but ideally we'd completely revamp it to close such obvious loopholes and bring back some skin in the game.
Crack open some Wikipedia and learn about how there were at least 2-3 independents as part of the 60 votes, who often did not vote with Democrats. See the myriad compromises that had to be made for healthcare reform to pass so that the ACA could become reality, including nixing the “public” option due to some of those aforementioned independents.
If you're going to play the "both sides are the same" game you need to be more precise in what that means. DNC is absolutely subservient to their patrons and party leadership in general owned by the donor class.
But the similarities stop there. The party platforms are in stark difference, and the GOP is now literally a cult of personality run by a mob boss. The naked corruption is off the charts.
In fact right now Trump is working to cancel or refusing to acknowledge mid-term elections and acts as if he were king.
I say this as someone who used to be a Democrat but left in disgust when Clinton remade the DNC into pro corporate puppetry. Partisan politics is a cancer on the citizenry and may very well be the end of what we call democracy in the United States.
I've tracked presidential politics since watching the Watergate hearings and what is happening today is beyond the political pale.
My pushback is that now is not the time for both-sides-ism. It needs to be addressed but most voters are poorly informed or vote their emotions and that talking point needs to go in the back pocket for later, if there is one.
I get your point, and the other one stating that Democrats are not "the left", but they are the the least worst option that a 2 party system offers.
The game is rigged, but this quote nails it:
On Undecided Voter s: "To put them in perspective, I think of being on an airplane. The flight attendant comes down the aisle with her food cart and, eventually, parks it beside my seat. “Can I inter est you in the chick en? ” she asks. “Or would you prefer the platter of shit with bits of broke n glass in it?”
To be undecided in this elect ion is to pause for a moment and then ask how the chick en is cooked.”
― David Sedaris
"My pushback is that now is not the time for both-sides-ism"
Of course, and that line of reasoning has consistently failed at the polls since it was deployed as a readguard attempt to bolster Clinton's failed presidential campaign. Like, how many times does the DNC have to stick a fork in this particular outlet before it becomes transparent that this line of rhetoric simply doesn't produce the desired results?
Not only is it absolutely time, it is well and truly past time to underline the functionally identical economic policies of both parties, how the economic turmoil this causes drives identity politics and political division in this country, with a clear eye towards bringing an end to all of that through any means available.
The Democratic party absolutely needs to be taken to task and none of their bullshit should be tolerated or defended, ever, except one small exception: election day, in the general election -- because we can't fix the government if it's no longer a democracy.
Identity politics hasn't been a national debate topic... ever? Unless you count "the presidential candidate is a woman/black" as identity politics. Harris was quiet on trans issues in her campaign and Obama didn't talk much at all about gay marriage in 2008. Maybe he was more accommodating in 2012, but it didn't come up in his campaign.
If you read through any of the DNC talking points of any given campaign, you're not going to see much on social issues until you maybe get to Kennedy. It's just not really something that's a pressing issue for a presidential run.
And honestly, I can't think of any social policies in the last 50 years that was seriously pushed by a sitting president. They at best pay lip service by painting a rainbow on some building, often years after the actual legal and legislative battles were won.
----
Now, to directly answer your question: I'd rather not rely on deplorables to vote progressive. the nature of how they approach life simply won't allow that, even if they are otherwise in full agreement with every point. We need to energize the entire 3rd of the country that took one of the most important elections in the past 60 years and simply shrugged, staying home. We need to give them someone who will fight for them.
Non-US PoV - US identity politics as an actual threat to panic and pearl clutch about seems to be largely a creation of the US right.
Actual US identity expression "issues" (visible drag queens, actually trans people, sports questions) seem to be small number small beer problems that should fall under US principles of "We let Nazi's march, so why not Furries" ?
> an actual threat to panic and pearl clutch about seems to be largely a creation of the US right.
"woke" has been a goldmine for the Right. Who needs policy when fear, panic, and anger get the voters in those booths? After all, drag queens and trans people are scary -- think of the children!
> will you give up identity politics for the deplorables vote?
That phrase gets used a lot, I'm curious what you mean by that.
If you mean "woke", then you're probably missing the irony of how that is actually used politically. Based on the phrasing of your question, I'm guessing you might have an irony deficiency. But please go on.
Political discussion here is frowned upon because it usually devolves into partisan name calling -- which justifies it not being tolerated.
But if you want to discuss policy or "hacking society", please do. I am of no political party and am more than happy to acknowledge the foibles of those I might associate with, as well as any of my own because everybody makes mistakes, no?
So, who in the US is actually using identity politics as a distraction?
I ask because as an outsider I overwhelmingly see US identity politics issues being raised by the new "Republicans" and to a lesser degree by the old Republicans.
> if you materially make peoples lives better they will vote for you.
This doesn't explain the last election in the slightest unless relaxed to "if you pinky promise to materially make peoples lives better..."
I agree with the former, and conceptually with latter. But we've seen people vote against their best interests because of the promise of destroying those who've they've been taught to hate. Contemporary US immigration "policy" is a case in point.
No, we haven't. People do not "vote against their interests", as much as commenters online love to claim that. What actually happens is that they believe what they vote for will advance their well-being, and you disagree with their assessment. That's a very, very different thing.
The idea that there are any significant number of people out there deliberately hurting themselves for hate's sake is a complete myth. People reach for it because it feels good to imagine that your opponents are hate-warped idiots, but there is not a shred of evidence to support such a claim. When you actually talk to people (and not just assume you know what's in their heads), you find out that they, like you, are just trying to do good in an imperfect world.
sure, US political parties have been largely pro big-biz
but if you can't see the stark difference in pro-mega-corp policies and blatant pay-to-play corruption in the last 1.5 yrs with the previous 4 years, you're clearly not paying attention
the fact that BigCorp couldn't wait to get rid of Lina Khan, and found a willing ally in Trump, is just one tiny example
If you employ a few hundred nurses, how exactly would you evaluate how well they show empathy?
You can't rely on asking the customer. When they're upset (they often are in these calls), they'll lean towards the negative regardless.
I don't know how well these AIs evaluate, but if they're even a little bit good, it makes sense to use it to screen for outliers, then have a human listen to those outliers and judge.
"You can't ask people because the experience is so universally terrible they'll just tell you it's terrible" isn't really an argument against surveys, it just means you need more specific questions they'll be fired up to answer
Let me suggest the following: Ask the nurses if they want the customer to rate them.
A significant fraction of the calls they answer are patients shouting at them because of:
- Long wait times
- They don't like their doctor
- They don't like the advice they're given (sorry, but we're not going to book you as a high priority appointment if all you can tell me is you have a headache. Sorry, we're not going to prescribe a narcotic for a scraped knee.)
- Several reasons that have nothing to do with the nurse, but the customer will still blame the nurse.
I’m not sure I understand your point. These things remain true regardless of whether or not you find ways to improve your process. Do we just… not try to improve because there is noise to sift through?
Classic "1 star review because UPS lost my delivery" metric.
I'd guess most people have had a situation where there's a corporate problem, the support person you talk to literally doesn't have the tools or the agency to fix it, but then you're asked to rate their performance on whether or not they solved the issue, with no option to say "Actually they did their best but this isn't their fault."
Ebay solved this decades ago. You can rate the seller and product separately. adding 2-3 ratings won't fix everything of course, but it would be a start.
I suppose it is political because these companies rarely want accurate assessment of their labor to begin with. They want any justification needed to lay anyone off at any time while minimizing legal liability.
By a knowledgeable/skilled person who listens to the call. (Which the AI solution provides).
Can you point me to the information you evidently have about which models Kaiser is using? All I can find is that they're using innovaccer, which can use any of anthropic, openai, and meta models on AWS or azure. Even their published papers don't seem to specify a particular model or capability level, just "AI". For all we know it's a gpt mini or similarly cost-effective model that has the context awareness of a Labrador hearing the word "walk".
Yeah, this whole discussion cracks me up. I have a number of direct experiences with Kaiser nurses. They repeatedly got into arguments with doctors in front of me, tried to countermand doctors' instructions, ignored their patients, and complained to each other about their patients while they were right there.
Repeated unprofessional behavior with no discernible change after trying to address it. My take is that the Kaiser nursing org has a serious discipline and customer (patient) focus problem.
To one degree or another, this is endemic among nurses. It's part of a broader cultural element: nursing programs have entrenched a culture of nurses vs. doctors. There are literally questions on their licensing exam to the effect of "which of these orders from a doctor should you refuse to enact?" (rather than, say, "which of these orders should you contact the doctor to seek clarification on?" or some other collaborative take). Nurses are taught their job is to protect patients from physicians. Given they don't have the expertise to do that , the general result is more broadly a power struggle in the guise of patient care.
The necessity of teaching nurses that doctors orders are not sacrosanct comes from the bitter experience of doctors giving orders that are wrong.
Asking for clarification is great, but doctors can be very reluctant to hear. The bottom line is that the nurse must not do certain things and the certification exam is there to make sure they know it.
Think of it in relation to the “anybody can stop the assembly line” part of quality control.
I agree (with the obvious qualification that there are excellent nurses out there who do a great job and don't let this stuff get in the way of helping their patients, some Kaiser nurses included). But I also see a marked difference in behavior and outcomes in other hospitals I've been to. Yes, there are still some unprofessional nurses in those networks as well, but judging by the outcomes, the hospitals don't let them do damage.
Most of the folks here on HN are dealing with customer feedback in systems automation in one form or another - it's pretty unavoidable in this age of LLM trendiness. The customers of healthcare (in both private and publicly funded systems) are the patients. So while the term might not be super natural it's an understandable one to use.
Patients are not customers, or at least I don’t want to live in a world where patients are considered customers. Customers and vendors are usually more of a symmetric relationship: price transparency, alternatives, lack of urgency. These are all characteristics of transactions that healthcare often lacks.
But they don't want to, because figuring that out is your job as a supervisor.
If you outsource that work to customers/patients, you'll end up with the car dealership model, where the sales rep begs you to give a 10 on every single question including on the interior design so they don't get fired.
That's the part most of this discussion misses. Supervisors exist for a reason. Congrats on your flat org structure, you fucked up an important feedback channel.
> where the sales rep begs you to give a 10 on every single question including on the interior design so they don't get fired.
Oh yes, and the nurses did employ strategies like that pre-LLM (don't know if they still do). They had to be very strategic about it (you can't just say "Rate me a 10.")
I am quite heavily in AI, and I would say I am pro AI. However this use-case for AI is putting AI in the wrong position. AI should be in service to all humans. An administrator building out a middle management KPI based on AI is a misapplication of AI.
Hospital systems are incentivized to avoid the real problems with healthcare. People want timeliness and they want quality care which hospital systems are not incentivized towards in the US. The incentives are profit, which given budgets means corners cut.
Triaging is an opaque system to the patient. It's an important process to doll out finite resources but it also very frustrating to be told, "soon" when you've been waiting 15 hours to see someone. Frankly, if I were King for a day, the first thing I would do is break up the monolithic hospital systems and build out more urgent care.
I would also try to find a way to facilitate transferring less critical patients from ERs to urgent care centers. Right now a hospital won't take the risk, especially if you are sitting in waiting room because beds are full. You can't easily punt a patient because them leaving would be against medical advice.
It’s not even been five years of AI, and we’ve already arrived at the point where the human is wrong and the AI is right.
Mind you this is in an area where the benchmark is the opinion of the human ! So if the customer is saying you’ve shown enough empathy but AI says you haven’t, then you take opinion of the AI?
Soon we’re going to have a situation where the patient is breathing, but the AI says he’s dead.
Isn’t it a running joke at this point that if you do what customers ask instead of focusing on the highest quality of service you get worse outcomes and the customer is still unhappy?
I thought that was more about correctly interpreting their asks, and not just actioning without consideration. If all your customers are saying your chair could use a cushion, it doesn't mean add a cushion, it means the chair is uncomfortable and you need to investigate why.
If all your customers are unhappy, then you probably aren't providing the high quality of service you think you're providing. After all, they're the judge, not you.
There's a great academic book called "Stupid Rules". Excessive rules (or KPIs - often rules in disguise) exist because we don't like authority.
Get the doctor to assess the nurse. Or the head nurses if you don't trust doctors. The nurses have managers, and if none of the doctors or head nurses can be trusted with a simple matter like assessing whether nurses are doing their jobs then you got bigger issues.
Oh no, the boss might play favourites if it's not an objective measure! Oh the injustice /s
But stupid rules or KPI also allow favourites. You can use an officious 30 point checklist and play favourites while ticking boxes. You can even rig "objective" data by controlling other factors (e.g. giving someone difficult customers do deal with).
Yeah, data driven would be nice, if you have good data. But data driven is a power tool. You don't measure SLOC or reward token use in software because of perverse incentives.
When reading the headline I was thinking we were talking about evaluating things like whether a nurse asked the right questions of the patient from a best practices point of view (say you have <insert condition> and the best practices for that are to ask the patient about pain level and which side it's coming from and check in with them every X hours).
But evaluating tone and empathy? Great, now every nurse is gonna be wasting their time and energy making sure to recite the best canned, optimized text-adventure incantations for the KPI every time they enter the room instead of using their brains to see what the patient actually needs.
"Hello Mr. Smith our patients are our top priority at Kaiser and your nursing staff here at Kaiser Raccoon City are here to make sure you are cared for, comfortable, and safe. If you have any concerns or are feeling anxiety be sure to press the nurse button and we will be happy to assist you, we appreciate the trust you place in us and are eager to celebrate your recovery with you." < nurse now realizes Mr. Smith has been choking and losing consciousness while she was reciting that spiel >
That is surprising. My primary care provider had a different response. Basically he said something in line of
"You wouldn't believe how much of a relief it has been. In your last visit, you saw me typing everything you were saying, right? I don't have to. I can listen to you and take very specific notes as necessary as opposed to focusing on both typing and listening to you at the same time. It has bought my stress levels down to here." (Indicated by his hand lowering)
On the one hand, pre-LLM there was plenty of software out there for medical use, and they had to be HIPPA compliant, etc. I've worked with people who used to write that SW (they hated the job because HIPPA was so strict). The rational side of me is saying I shouldn't be biased against these, and that there's no way they would relax the requirements.
On the other hand, the emotional side of me screams: It's LLMs! Huge privacy concern!
I try to let the rational side win. I've always given consent. Especially because I liked my doctor pre-LLMs, and it seems silly to suddenly mistrust him and go to a doctor I don't know at all.
Indeed, I always turn this down as I don't consent. If you had a thorough read of the major providers' Terms of Service, you wouldn't either.
It's a shame, if they had an AI transcription tool that kept everything in-house I'd be much more comfortable with it. Or perhaps some kind of zero-knowledge cloud-based product where I hold the keys.
I use Kaiser, recently their webpage asked nicely if I would sign a HIPAA waiver to share my data with third parties for marketing purposes. The default was Deny and they made that easy, but it was concerning.
Having seen the type of insane shit these LLM transcription tools shit out on the regular, I wouldn't trust these tools for even the most mundane note taking in a medical setting, especially if there's a summarization feature.
I've seen summaries that implied the opposite of what was actually said, and even the transcripts themselves often contain egregious errors. I can so easily imagine these tools summarizing "I drink coke often" to "I use cocaine often", as a random simple example. All nuance gets lost, all context gets lost and unless you're vigilant and looking out for these types of errors it's so easy to slip by the cracks.
I've seen the quality of transcriptions, and it's awful. I wouldn't trust it for something as trivial as meeting notes, let alone medical transcripts. Either this doctor is going over the notes later to summarize them for your records anyway (which will cost them just as much time as the old way), or they're relying on the LLM to summarize, which is even more irresponsible.
Nursing and PCP are very different jobs. Ones a lot more cognitive than the other whereas the other involves actually doing/executing on a plan. I can see how AI would help reduce the cognitive burden while actually increase stress on the execution side.
While they definitely serve a purpose, primary care is not that.
If you present with anything other than healthy and fine, the ones I have had to see are less than helpful.
They simply do not have the depth or breath of training as a doctor. They're very good at executing a plan as part of a care team, and even making changes to that plan based on patient need. But they just simply aren't as good as doctors.
There's a reason they're replacing doctors. . . They're cheaper. That's it.
NZ uses AI dictation and according to doctors who were apprehensive at first, they now love it because they feel they spend less time note taking, more time listening to the patient, and can deal with patients better.
Similarly, I think anything we can do to help take the burden off the mundane parts of the job has helped clinicians focus on the actual hard parts. Where we get... bristling, is when there's any suggestion of "legislating" (operationally, not like, governmentally) care patterns and telling clinicians how to care for their patients.
Which is great, because anyone suggesting AI should replace clinical judgment and work is an idiot.
Workplace metrics and surveillance... What could possibly go wrong?
That being said, more than one (female at that) doctor has told me in confidence and based upon their observations during residencies, etc. that if I'm ever admitted, be very careful how I modulate my interactions with nurses. They're not all Florence Nightingale and Mother Theresa and there exist those who will @#$% you up on various pretexts or are just plain sloppy and negligent.
Despite all the moralising fluff, it's just a job, not some saintly vocation. Some safety oversight is needed, just as it is for any other work function. Still, can bet that anything 'Corporate' has mandated will be Goodharted up the wazoo.
Since we're off-topic, most of the information in that article (as it's often the case) is based mostly on Christopher Hitchen's work (book and documentary), a man who describes himself as "antitheist" and made a living out of publicly fighting religion. So not exactly an objective reporter.
I read a good chunk of the criticism against Mother Theresa as either willfull misunderstanding and/or just repeating the same literal three quotes from Hitchen's book (seriously, they're always there). I cannot say whether she was a good person or not, but I can say: if you ask "which evidence is there which doesn't lead back to a man with a personal vendetta?", the list gets significantly shorter.
This problem with workplace AI interfering with nurses ability to manage healthcare obligations for their clients is not confined to Kaiser. UHC has also introduced the AI surveillance tools and are using it to do similar things.
Kaiser is a vertically integrated healthcare provider. They provide insurance like UHC but they also require you, for the most part, to be treated in Kaiser medical facilities.
How can UHC use AI in the same way? They're an insurance company. They're not administering the actual healthcare?
>How can UHC use AI in the same way? They're an insurance company. They're not administering the actual healthcare?
UHC, the HC stands for Health Care, does have a field operation that handles home health care evaluations for those who live in rural areas with minimal access to medical facilities. Those patients are visited regularly by field personnel, trained nurses, who evaluate their conditions and insure that they have access to appropriate treatments for their conditions. Part of the evaluation of appropriate treatments has recently been pushed off to an AI-based system which uses various inputs to determine eligibility for treatment options.
> that might appear to be incentive to improve quality
Their goal isn't to provide high quality care. Their goal is to increase profits. It's not hard to imagine how improved quality would lead them to spend more money. (faster diagnoses of serious illnesses and recommending expensive care)
Indeed, increasing quality tends to increase costs and decrease profits so keeping costs aligned with their profit goals automatically degrades quality.
Psychopaths don't care about other peoples pain. Some MBA only care about their own ego, power, and money. They do well in corporate cultures that reward parasitic relationships with customers. =3
Mangione had back issues and apparently some difficulty in getting treatment for it, but he wasn't insured by UHC. According to his manifesto, he chose Brian Thompson as his victim because UHC was the largest health insurance company in the United States.
His alleged* manifesto. There is no reliable evidence that Luigi Mangione committed any crime. It seems more likely that Brian Thompson was killed by a disgruntled customer.
The nurses at our local rural hospital are tagged and tracked wherever they go on the hospital campus. Time spent in one spot is part of their review.
I wondered why they zip in and out of the rooms, when just a few years ago they would spend fifteen to twenty minutes in each room. The patient load hadn't grown. The number of nurses has gone up, not down.
So I'm blaming the stupid metric on their evaluations for a worse standard of care.
AKA the "Be your own advocate and demand more testing!" crowd.
Although Kaiser tends to repel such patients (they'll happy say "No" and tell you to find some other provider). The bulk of complaints I've heard about KP in California boil down to "They wouldn't give me a referral to a specialist".
The article mentions uses of AI but doesn't really give any examples of harm from AI. It does give specific examples where it sounds like Kaiser is optimizing calls to minimize cost rather than improve quality of care. It's also pretty easy to expect that the examples given (treating longer calls as a problem and penalizing nurses for giving more than 3 pieces of advice) reduce the quality of care.
They talk about workplace survillience. They use a machine learning tool that try to assess their emphaty, and such. The AI, while the tool technically can be called that, in the article is there to be a buzzword.
> where they were found to have done everything right on a call — except staying on the line for more than 15 minutes
Do these idiots not know how intelligent assholes work? If you make this a policy, everyone who has a gripe will eventually learn to delay a call to 14 minutes and then make an absurd ask.
It sucks because AI reduces call center costs in many toil tasks very effectively, regardless of whether you want to help or dissuade customers - it's just well-suited to the task and it's going to accelerate. It's a win for capital and the technology implementers, even if it's a loser for the call center employees and callers.
Some of the tech is pretty scary. One big vendor's solution [0] can provide not just AI agents but also use AI to snoop on calls in progress, evaluating sentiment from both sides [1], verifying phrases are said - pretty dystopian in theory. From experience, these things tend to go downhill based on the attitude at the top - is the mission to slash costs or take care of customers? A 1000 decisions follow from this one, and like Jira, it can be a useful tool or a prison-like hell.
90% of the time when I call a call center I need a human to fix an organisational bug - e.g. faulty billing or some other kind of mixup. AI cannot help with this.
If it's to do something normal you could do through the website there was no need for AI - a website or app suffices - provided it isnt terrible.
Capital definitely thinks it can save costs here but capital is getting increasingly delusional these days.
The HN crowd is not the usual demographic for call centers. Im willing to generalize a vast majority of callers can find the info they are looking for if they tried a little
I'd like my providers to use Abridge for their notes, but because Abridge doesn't allow patients to opt out of using the data for training I decline every time.
If you read the quotes from the union, they blame the management, and they cite workplace survillience as one issue, wich is happened to be a machine learning tool. So, of course the article talks about AI, because thats the trendy buzzword.
They already did a trial which used the trendy buzzword to surveil the nurses. The nurses want to implement controls on that trendy buzzword before it is further misused by management to cause harm to patients (by way of making the nurses focus on meeting some arbitrary performance metric rather than focusing on patient care).
motivated reasoning: study in advance of nursing union contract negotiations
The sad thing is that there are many issues, but the study didn't really address them. One would hope for more effective critics.
The AI application I'd like to see would be to identify the elective hyper-utilizers (so we could try to demotivate them by addressing what's really bothering them). That would improve quality of care for them and quality of life for providers, and create time for outreach to the under-utilizers who need preventative care.
There is an unfortunate cycle that has been playing out this year in USA. Insurance companies are arming up with AI to deny billing codes charged by providers. Providers are arming up with AI to listen in on provider-patient sessions to prove the billing codes are legit (And teach providers to use keywords in session).
The loser, as always, is the patient's quality of care.
> Providers are arming up with AI to listen in on provider-patient sessions to prove the billing codes are legit
This is not a decrease in quality of care - this is your provider having actual evidence of the care needs they discussed with you when they close their note, hours or days after seeing you.
> "Nurses fear that having long calls can lead to bad performance reviews"
> A company spokesperson said, "Kaiser Permanente does not use Average Handle Time to assess agent performance"
So uh, average time wasn't raised as a concern, calls beyond a certain threshold was. I wish this semantic discrepancy was better highlighted in the article.
They claim they do not use average handle time, but it is very common to get called into meetings to discuss why they spent a lot of time on some calls. The nurses get defensive (by definition - they have to justify the time used - it is a defense).
They also do get called into meetings if their average handle time is large.
It may still be true they don't use it for evaluating performance, but they absolutely do utilize it to "coach" the nurses.
It might not be a written metric, but do you actually believe that someone isn't being evaluated partially based on how many times they've had to talk to them about issues?
I highly doubt it. If this is the reason your manager knows who you are, you are absolutely going to be judged on it. It doesn't really matter what the policy says.
And the nurses absolutely feel like they are being punished for it. Just like having to consistently remind HR that your "absence problem" is due to covered FMLA leave - they know who you are because they've had to talk to you about absenteeism. In a call center of 500 people, it isn't likely they remember that you had issues because of their faulty systems.
> but do you actually believe that someone isn't being evaluated partially based on how many times they've had to talk to them about issues?
This is true for any job. I was unfairly fired from a job because somehow the manager got a perception of me being incompetent, because he often talked to me about problems in my work - most of those conversations ended with him saying "Oh, now I see why you did it that way."
Yeah, I didn't even want to lean out that far but I'm sure average handle time is incorporated in some manner.
But, just purely semantically, the statement Kaiser gave in response was worded in a precise smug corporate America style to dodge the main concern raised. I think it's important to call out weasel words.
> the statement Kaiser gave in response was worded in a precise smug corporate America style to dodge the main concern raised
I know nurses. And I know their unions. Kaiser can be extremely clear and tell the truth, and they'll still say "We don't believe you!" without any evidence other than being called in to talk about it.
I'm not anti-unions - I've benefited from them. But it's well known that distrust goes up when you have (or need) unions. It typically degenerates from "We" to "Us vs them".
Let me ask you this: Are you saying they shouldn't monitor the time at all?
Again: A tidbit of inside information: A number of Kaiser patients get such long wait times that they're issue isn't addressed when they try to call (i.e. they are told they'll be called back, and they're called back some other day). I don't know the percentage - likely small - but from a healthcare standpoint, it's unacceptable.
Another bit of information (likely not inside): Kaiser has a serious budget problem. They already pay amongst the top salaries for nurses, and they can't simply solve the problem by hiring more.
There's definitely a lot of room for weasel-wording there, where the metric really being used isn't the mathematical mean, but punishes people just the same.
the more I read about how AI is being used, the more I'm coming to the conclusion that despite me personally find it quite useful in my work, and even my personal life to some extent, it is a net negative to society as a whole, and if the choice is between zero AI or the AI that is being deployed, we'd be better out without it
what significant improvements to society or humanity have come about as direct result of AI, that wouldn't have been achieved without it? faster protein folding is the only one I can think of and that more a matter of "faster" than "impossible without AI"
I think at some point there's going to be some version of the Butlerian Jihad
I mean, "AI" as it presents itself in the zeitgeist is in its infancy. It's like making conclusions about the internet in the late 90s. Whatever it becomes likely hardly resembles what it is now. For better or for worse.
I'd like to think it's not meant to make life better for a regular nurse, but rather to weed out the abusive ones? At least that's how I see it from my flawed, post-communist country perspective.
And here is why: I guarantee you that the nurses are working in the "for-profit" units, and also, that still betrays ignorance of what "non-profit" actually means, which is the load-bearing topic of this thread.
I'm not sure the for-profit approach is exactly what's to blame. HMOs like Kaiser are legally forced to spend a certain fraction (80% percent for the worst case, more for large group plans) of their premium revenue on medical services. They can't save and pocket the money like a traditional for-profit enterprise.
This doesn't seem like a money-saving measure exactly. The main AIs the article talks about is making sure nurses on their nurses' lines aren't being assholes. I guess this used to be spot checked before so you save on that? Maybe? It seems like they are trying to solve the problem of some of their nurses staffing their nurses' line not treating their patients the way they're supposed to.
Increasingly health insurance companies and healthcare providers are intertwined. So they may spend 80% on healthcare, but then a big chunk of that could go to the urgent care clinics that they own.
And even if they don’t own the provider, they don’t have much incentive to lower total cost because 20% of a larger number means more total profit.
> Increasingly health insurance companies and healthcare providers are intertwined.
Kaiser is an HMO. They are the insurer and try to have their employees, such as these nursing lines, perform almost all of their care. Shifting from one line of business to another is purely internal and can't game Medical Loss Ratio like your scenario.
> they don’t have much incentive to lower total cost because 20% of a larger number means more total profit
There is some bad incentive here for sure. That being said, insurers do compete on price so they lose customers if they charge more than other insurers. Also, regulatory rate review can decide whether they can raise premiums a given amount.
I’m not talking about Kaiser. I’m talking about companies like UnitedHealth Group Incorporated who own UnitedHealthcare the insurance company and Optum the healthcare provider.
> That being said, insurers do compete on price so they lose customers if they charge more than other insurers.
Yeah but that’s a second order effect. Most companies are incentivized to cut costs because they will directly realize the profit. Insurance companies are incentives to cut costs only to grow market share.
I understand the point of the profit limits, but I don’t think it works very well in practice. I think it would probably be better to just have private companies without that profit cap and add a government insurer to compete with them.
That is because the problem was never the sub 3% profit margin or non profit insurance companies (in the case of Kaiser and many others).
The problem has always been pharmaceutical prices, liability costs, and inadequate supply of healthcare.
The government does not want to decrease the price of medicine by funding trials so medicine is in the public domain and cheaper, the government does not want to increase the number of matriculating doctors and bring down their time/money/stress costs, and the government does not want to enact tort reform so every step of the healthcare chain is spending inordinate amounts of time and money to prevent litigation.
In the US, you should always be double checking what your provider (or guidelines or whatever) is telling you to ensure that the information is maximizing your benefit instead of minimizing their liability.
Yes brother. This is the way. We pray to the line, only it can shelter us in these dark times of labor revitalization. HODL. May your returns be colossal.
[edit] preemptively, if you're going to claim "but this isn't art so irrelevant" then I claim bull fucking shit. It's the same problem no matter how you slice it whether it be engineering, support, art, or medicine. Get real. Look inward. Touch grass. If you think AI is a good thing for your profession--whatever that profession might be--you're probably a delusional psychotic. It's OK, you'll thank me later.
With all of that in mind I have to wonder whether there is overlap between these response groups and if so, how much. Could be zero to 100% without more information.
>About 14% of Americans think AI is moving us towards a better world. About 17% are creationists. About 26% believe in Telekinesis.
0 people that I know are in all three. Pretty confident about that.
For the any two of three cases where [A] includes creationists and those favorable to AI; [B] includes creationists and those who believe in telekinesis; [C] includes those favorable to AI and who believe in telekinesis.
[A] 0 ; [B] 0 ; [C] 0
Considering people that I know who could be part of one of the three groups now is an interesting question. I am pretty sure that two relatives are creationists based on interactions over the years. I haven't ever heard anyone I know talking about telekinesis so I probably have to say that this could be a non-zero number. If it is a non-zero number then [B] could end up being non-zero. AI is universally hated or even feared by those that I know who are being forced to use it or whose employer is adopting AI tools in their workplace.
So based on my own recollections I have to say that there are only 2 people that I know who belong to one of the three groups you identified. Interestingly enough, the children of those two creationists are not religious as adults. I think they had all they could stand growing up in that environment and as soon as they went to college they 'rebelled', leaving the parents disappointed that the kids didn't want to tote all that baggage in their own lives.
Sample size is small though since I don't know many people.
All of those beliefs seem approximately equally regressive? What percentage of people think there's something non-physical that actually exists? I'd put them in the same padded cell as the rest of those clowns.
Well then their protocols suck. I have many anecdotal data points about them fumbling in major ways when it matters (missed major pathologies, messed up surgeries, etc.).
If you have a choice of hospital networks, research carefully. Kaiser might be fine for many people's needs, it's not fine when it comes to intensive care.
The care quality of all major healthcare providers in the US is some pretty available data, and I've never heard anyone of being suspicious of Kaiser, of all companies. They're specifically known for having really good outcomes. It's like asking for a source that McDonald's sells the most burgers in America. It might not be true - maybe technically it's someone selling sliders or whatever, but it's so close it's probably not worth arguing over anyways.
I would love to learn the cost of the AI versus how many new workers they could afford to hire and get more calls done. But I assume the end goal will be full replacement of human workers once the AI has had enough time to learn the job.
The article doesn't seem to be about replacing nurses staffing their phones with AI. It seems to be about making sure the care they're providing is what the company wants.
People enjoy saying "AI can replace middle management" as a comeuppance but it's not what people think. In many ways, AI is primarily serving as middle management, yes. But what happens is that instead of one manager engaging in petty surveillance, harassment and browbeating to increase work intensity, you have ten clones of the manager doing the same thing. That's not the "woo hoo, automated middle management!" you were looking for.
> Nurses are instructed to stick to a script on phone calls and give no more than two to three pieces of advice, Capulong and other nurses said, which means they may sometimes need to decide whether to withhold advice or face a performance evaluation hearing.
> Another nurse speaking on condition of anonymity said “AI did not understand our job and would grade us wrong all the time.”
In theory AI could usher in the first time in history where one can escape from this trap - because qualitative judgments can be made at scale, from an unbiased and universal baseline. In this situation, for instance, rather than collapsing call transcripts and reports into metrics, it could evaluate whether red flags are encountered in the context of a call, and allow for qualitative guidance on improvement, across a comparative corpus of situations that are themselves chosen qualitatively.
But very few managers are empowered to take this kind of approach; they're evaluated by their ability to report quantitative metrics, and thus they must implement regimes of quantitative metrics. And leadership instructs them to use AI to build that regime more quickly.
If you want to see an "AI native" organization, it's one where leadership actively fights this tendency, and sees managers as product designers who make the end-user experience a beloved and empathy-driven one, as opposed to a gear that turns accountability into a single number on a screen.
What these complaints always boil down to is autonomy and control.
The more centralized an organization, the more it relies on metrics to understand and exert control over its employees and customers.
People started hating tech right around the time metrics became popular. I don't think it's a coincidence. AI just accelerates the trend.
The problem is the misidentification of AI as the issue. As long as we don't understand the real issue, we won't solve it. AI is just a tool. It's being used in a way that denies human agency.
Our cultural values need to shift away from safetism that demands centralization. And shift toward valuing human agency. That starts with talking about the core issue.
Everyone pushing tools/AI during initial development/investment and building its demand in the cultural discourse always highlights its ability for good.
Now, like many tools, the majority of those selling AI to make money off of large enterprise sell its ability to increase productivity, efficiency, compliance. Either to make money or to minimise risk. And so like you say, they just become tools to make these metrics move or report them at higher granularity. And often there is either a lack of imagination or a willful ignorance of the perverse outcomes with relationship to humans because they are in service of the organisation not it's employees.
Certainly, I agree that using AI to dehumanize - generally what companies seem to be doing with it - is super bad. And it's also what is being sold to existing companies right now.
But that same AI could cause those companies to no longer exist.
The AI I'm happy about allows people without much tech knowledge create small apps to do exactly what they want. And, for those that know just a little more, use it to help them extend open source software for their niche use case.
This makes computing more personal and gives back agency to the computer operator.
Mix that with the rise of much more competition in much more custom software, and you'll see that a future can exist, if we want it, where software becomes more personal and humane.
The software vendor will capture less value, though - the margins will be thinner. Instead that value will be captured (in non-money terms) by the end users.
That also means that software companies, unable to capture so much value, must shrink and become more boutique. The software that contributes to our centralized world would lose a lot of power.
That's the future I can see. The only way it doesn't happen is if a cynical narrative wins out and manages to lock it out through regulatory capture so that only licensed operators can use or provide AI. The anti-AI narrative helps the cynics.
While I'm sympathetic to the frictions of newly introduced AI and the fact that AI in healthcare, especially calls, can seem very uncaring, between the lines the article reads a bit like the typical union complaining about modern tech that reshapes their work, given the multiple mentions of protests, nurses union, etc.
Given how healthcare is one of these sectors that seems to relentlessly resist efficiency increases and is the prime example of Baumol's cost disease, I think any developed country with a costly healthcare system needs to do these AI experiments. The current versions will be shit, but the only way out is through if you still want to provide affordable care.
I honestly have no doubt that AI going forward will be able to do a good job at triaging via calls and also being empathetic about it. But of course it needs careful experimentation.
I RFTA and the majority of the complaints are about call center metrics and the pressure to ration care. These are real concerns about misuse of metrics, but not AI. The AI empathy thing was a 2024 pilot that was discontinued.
FWIW my wife works for Kaiser and finds a lot of value in the the medical LLM tools available to her. She tells me being able to do live translation, summarize notes, and quickly get comprehensive answers save her time and help her give better care. Her older patients also frequently come in bringing AI-powered alerts from their apple watches that detected cardiac events.
It's annoying that we use broad terms to describe a set of technologies that in some ways can be problematic and in another ways are very beneficial. We gotta evaluate each of these as they come rather than talk about blanket bans.
Being close relative for several med and care workers we have discussed it a lot and consensus is that it really depends. For example relying on LLM summaries sounds great until it doesn't. It doesn't matter whether you misunderstand LLM summary or LLM "misunderstands" you – there are real risks involved, and you wouldn't want them to weigh on your conscience if they were to materialize.
Relying on LLM to summarize things for you has one more issue. To outsiders, this seems like a tedious process, but is actually very important part of the thought process. Wording your thoughts and writing these down helps people to discover new aspects of the problem. It's how people learn.
At the moment consensus is that it must not be banned, but also not mandated in any way - people must take responsibility, and they must be able to decide for themselves where and when the LLM use is justified and where it is not.
I don’t think that it is possible to both allow the use of LLM and not mandate them in modern metric driven work places. Either you ban them or you force people to use them for game theoretic reasons: they are slower than their peers and quality of the work is harder to measure than quantity. All you achieve is shifting the blame to the employees if the LLM messes up. Come to think of it, that probably is a highly desirable outcome for the decision makers, so perhaps that will actually be the policy that becomes universally adopted.
> I don’t think that it is possible to both allow the use of LLM and not mandate them in modern metric driven work places.
What I’d personally be most concerned about would be the risk of bad models instead of SOTA being used which would be especially error and hallucination prone.
If you’re gonna do it, do it right. Otherwise don’t bother at all.
> All you achieve is shifting the blame to the employees if the LLM messes up.
How is this not a good thing for everyone?
> where and when the LLM use is justified and where it is not
while being bombarded with articles like "AI makes things worse", "AI consumes all the water" and the like
Things like this are (sadly) common (and age-old) problems with automation and computerization. (For a vivid account of this phenomenon, check out the novel _Close to the Machine_, by Ellen Ullman.)
As executives and analysts increasingly use the "AI" craze to push automation and computerization (and layoffs) generally, even aside from AI proper, it should not be surprising that the individuals and groups opposing those moves also use the same labels.
The lack of precision in language here sucks. It sucks for the discourse and it also sucks when it comes to focusing anger and productive energy on the core problems (obfuscation of human responsibility, erosion of human agency, declining institutional flexibility, deprofessionalization, etc.). But it doesn't begin with the critics of AI.
>The lack of precision in language here sucks.
It's a feature. Or at least, a perk. If they want to claim this new shiny rock is AI and people buy it, then of course it's in their best interest to keep the black box mysterious. Being subterfuge for muddying the discourse of critique is just a nice side bonus.
But it is only a perk for the scam artists who benefit from that.
Yes, it makes sense that the confusion aligns with their interests, and they are unavoidably a big part of the conversation. But it remains a problem for the non-overlapping group of people who actually value the social contract, and for us finding a solution which helps take one more step to defeat the scammers remains valuable.
Yes. It is useful for the scam artists:
X, Open AI and Anthropic, to name three
Near as I can tell, like crypto, 90% of the ‘discussion’ has been taken over by scam artists, and any folks trying to have a non-scam discussion get yelled at by everyone else.
I am very interested in your reading of Close to the Machine. I read it myself a couple of years ago and found it a wonderful telling of the early days of tech, with overtones of the "technology workplace" that were still very true to this day. I did not pick up on any commentary on automation or computerization, outside of the general critique of bureaucratic systems that alienate you from the outcomes of your labor.
Do you have anything I could read to understand your reading better? I would love to be able to dive back into one of my favorite books with a new lead.
> AI-powered alerts from their apple watches that detected cardiac events
Surely these are “good old-fashioned AI” (statistical learning) and not LLM, though.
I just want to be clear that the “medical LLM” tools are the new ones, and the Apple Watch alerts aren’t.
LLMs are statistical learning. GOFAI is symbolic, rules-based stuff, expert systems and that.
There is still a categorical difference between how they are being used. Specifically analytic vs generative. Generative AI (LLMs and image generators) are the ones people have issues with - pretty much nobody cares about ML processing for analysis.
There’s a bit of a grey area, for example speech recognition. Would you classify that as analytic or generative? Whisper and speech LLMs work pretty well, but can completely make up stuff that wasn’t in the audio at all (see e.g. “thank you for watching” transcribed during silence). Other approaches are closer to the acoustic evidence but may make other mistakes (especially wrongly transcribing long tail, low frequency terms). Pick your poison.
Analytic, but badly made.
> pretty much nobody cares about ML processing for analysis.
I work in a bank and a can tell you that the customers absolutely hate ML when it rejects their loan application. Over the pond in the US, I have an impression that the fico score is not exactly popular either, but I have no first hand experience.
As long as you can get a reason from the model, it's not that bad.
Black box automatic decision making is much more problematic.
Who downvoted this person for correctly defining GOFAI on an tech forum?
Cardiac events from Apple Watches is not “AI” though
It unequivocally is AI. It's just not LLM-powered.
The rising LLM = AI equivalency is unfortunate.
It's machine learning, which has overlap with AI but is not completely equivalent.
The “overlap” is that all machine learning is AI, but not all AI is machine learning.
> but not all AI is machine learning
I will instead pick at this latter part of your claim. What is an example of something that is AI but that is not ML..?
A chess engine.
> The “overlap” is that all machine learning is AI ...
"All machine learning" is not AI, as k-means clustering and linear regression, amongst others, are very much ML without qualifying as AI algorithms.
https://en.wikipedia.org/wiki/Artificial_intelligence
As it is taught literally every single AI/machine learning course on the world, machine learning is very much part of AI completely since inception.
I don’t completely understand why it is this important for you to argue against this completely defined fact.
It is correct to argue about misleading terminology. "AI" contains the word "intelligence", and for instance logistic regression algorithm is not intelligent, while it is clearly ML, since machine learns something. As Machine learning is broader category, it should include Artificial Intelligence, not vice versa.
Also, 'every single course' is perhaps an overstatement - a course that I co-authored tries to get it right from the first principles.
You're just making up your own definitions. Have at it, but as you've been told: this stuff is not new.
It wasn't misleading for 70 years... How did it become misleading?
Technically linear regression is statistics rather than ML, but I feel like the GNU/Linux people whenever I point that out.
The machine is learning something so that it can produce outputs based on its learned knowledge. At a high level that seems to be very clearly AI. What am I missing here? You’re probably right, I’m asking genuinely.
It's a matter of definitions, but I can at least understand someone wanting to make a distinction between reactive and non-reactive 'AI' (such as data filters).
There's overlap and edge cases, though: Maybe you have a program that summarizes texts. One could argue that's no different from a passive filter. But can you then ask questions about the text? That's unquestionably AI.
Bayes is turning in his grave fast enough to power Manhattan.
At this point AI is a marketing term not an actual category
See: Samsung selling "AI" vacuum cleaners and washing machines
To me they're the same thing. If there's a bunch of training data that is fed into a system that creates a model, then it's not traditional programming, where someone laboriously writes out if statements by hand. AI and ML aren't, as far as I'm aware, rigorously specifically defined terms. They're words that marketing picked up and ran with it. To me, what matters is: is there a black box somewhere in the system that's a bag of numbers, or is it code that a human could dig in and read.
There are both ML that is not AI, and AI that is not ML.
For example, if you pick them manually, decision trees can be AI but not ML. Video game character behavior is a trivial example.
Eliza for example is also not ML, but could be called AI.
Likewise, there is ML that is not AI. Such is debatable, because you could always argue that using machine-learning on anything results in intelligence. The way I see it, things like image enhancement or voice replacement are not artificial intelligence at all. I probably could not define a hard line where it becomes artificial intelligence though.
>Video game character behavior is a trivial example
That makes no sense. "Manually picking" items from a decision tree is literally not "AI".
I don’t know what the op meant by manually picking but the expert systems of the 80s and case based reasoning systems of the 90s used fairly static decision functions and were explicitly called AI at the time.
AI and ML have very clear definitions[1]. ML has been a subset of AI, always has been. Latest marketing or "scare quotes" doesn't/shouldn't change that. Especially not in a technical forum like HN.
[1]: https://en.wikipedia.org/wiki/Artificial_intelligence
Ctrl-F Machine Learning. Apple Watch alerts are Machine Learning
It’s machine learning, which people routinely called AI not so long ago.
ML was always marketed separately as AI/ML, with AI being things like CNNs/RNNs/BERTs and such. Always felt like a distinction without a difference.
Laypeople are changing how “AI” is used in common language, like they previously did for “algorithm” and “crypto”.
The textbook definition of AI is a system that solves problems that are difficult for humans. Whether the approach uses formal logic, machine learning, neural networks as a special case of machine learning, optimization, search problems, etc. does not matter.
I don't think so. ML was always associated with AI. When it wasn't, it was called statistics.
I never heard people calling machine learning "AI" until large language models made it trivial to market it as such. Like, I remember back when Netflix, for instance, was going around advertising how machine learning (not AI) powers their recommendations.
> I never heard…
You should listen better. The University of Edinburgh had an entire Department of Artificial Intelligence when I was an undergrad there in the 1990s, and one of the things it researched was machine learning.
I don't see how including machine learning under the artificial intelligence umbrella counts as calling machine learning AI.
My local supermarket places the almond milk in the dairy section, and some people find this very upsetting.
My local cvs refused to let me buy non-alcoholic Bloody Mary mix aka spicy tomato juice without ID, because it was slotted in the alcoholic category.
That example kind of illustrates my point though? ML being in an AI book doesn't mean ML is AI, just as being in the dairy section does not make almond milk dairy.
It illustrates that some people can’t distinguish between a useful label by association for the general public, and their own desperate compulsion to litigate hair-splitting category distinctions.
Someone who was truly on the ball on this matter might’ve observed that Edinburgh in the 90s was so balkanized by internecine personality conflicts that most research that might later be strictly labelled “machine learning” actually took place in adjacent units and not directly under the DAIry. But I suppose you haven’t heard that, either.
> But I suppose you haven’t heard that, either.
Exactly what do you think my argument is? It's not "I didn't hear of [anything], therefore it doesn't exist / is not admissible". It's roughly "I didn't see machine learning referred to as 'AI' for years, until LLMs happened, at which point most companies that used to say 'machine learning' started calling the same things 'AI'".
You don't have to be snarky about it. I've heard it's okay to not know things. Is that wrong too?
Also:
> desperate compulsion to litigate hair-splitting category distinctions.
All I'm saying is that neither one is a strict subset of the other. Even though AI and ML are incredibly related to the point of even mostly overlapping in practice, they're not the same thing! AI is an outcome and ML is a mechanism. You can use the mechanism to achieve the outcome, or you can use a different mechanism to achieve the outcome, or you can use the mechanism to achieve a different outcome. That's all. If that's a hair-splitting category distinction to you, then so be it.
Ed: I disagree. My recollection is that machine learning was routinely sold as “AI” even when it obviously wasn’t. (IBM’s Watson was good at Jeopardy but not real medical applications.)
This isn’t exactly the same, but nothing in the book Paradigms of Artificial Intelligence would be considered AI today.
You must be thinking of a different machine learning. All the on-device machine learning, backend machine learning, OCR, etc. was all called "machine learning" before LLMs. Yes, the field of artificial intelligence still existed, often used machine learning, and called the result "AI". But Apple would call keyboard prediction machine learning. Microsoft would call OCR machine learning. YouTube called machine transcription machine learning. Google called camera image enhancement machine learning.
Microsoft now calls everything AI (actually mostly "Copilot"). YouTube now calls everything AI (including genuine LLMs and generative features, but also everything it used to call machine learning). Google now calls everything AI (including everything it used to call machine learning). Apple is seemingly the only one immune.
My argument is not that no one ever used "AI" to refer to a product that utilized machine learning, but rather that the term of art in the industry for machine learning itself was actually "machine learning", not "AI", until LLMs took over and made it "AI".
You would not pull a library off the shelf for "AI", it would be for machine learning. You would not implement and perform "AI", but machine learning. Even central parts of the AI ecosystem like PyTorch advertise as being for "deep learning", which is a subset of machine learning. Not "AI".
Counter example, the book that is the foundation of much coursework and learning for people in AI, has a whole section on "Machine Learning" with all that k-means and such in there - https://aima.cs.berkeley.edu/
I'm really not sure how that's a counterexample. The section is called machine learning, not AI. Machine learning is a useful tool for artificial intelligence, so I'd be surprised if a book about AI did not talk about it.
I'm saying that Machine Learning was borne of AI from the very beginning. ML has become specialized enough that we may later (much much later) declare it somehow larger/separate/overlapping, but it originated from AI as the generic umbrella.
https://en.wikipedia.org/wiki/Machine_learning
Machine learning is just what we call AI that works.
Math is just what we call a video game that works. What?
Oh, maybe you were referring to reliability of the system (i.e. in contrast to how LLMs are famously unreliable). Maybe?
Thank you. I was starting to think the history revision was almost true, but your recollection is very much in sync with my own. Everything was machine learning, nobody talked about AI unless it was for research, now marketing has changed that, unfortunately.
> Everything was machine learning, nobody talked about AI unless it was for research
Machine learning was AI. The specific wording was a branding choice, because "AI" was a deeply stigmatized brand. ( https://en.wikipedia.org/wiki/AI_winter ) But there was not a conceptual division.
There's a close analogue to how modern genetic researchers are happy to tell you that your genome is not informative as to your "race", but it is informative as to your "ancestry".
Yes, because we had the same stupid arguments then: "that's not AI!"
So machine learning became the marketing.
What makes them stupid?
It's stupid because there's no formal definition of what counts as AI, so we repeat the same conversation every time. Hence the joke ML is just AI that works.
There's a book from 1995, called Artificial Intelligence: A Modern Approach, by by Stuart Russell and Peter Norvig, which gives the definition "AI is the study of agents that receive percepts from the environment and perform actions." but doesn't define intelligence.
https://aima.cs.berkeley.edu/2nd-ed/preface.html
If we go with that, though, I'd say AI is anything that uses a model to make decisions instead of hand written "if" statements.
For a long time, AI was a bad word that stood for unfulfilled promise. See AI Winter. Hence, researchers strictly avoided the term while still working on learning algorithms, the same that power LLM training.
In 2011, I took an AI course at my university and it was all perceptrons and neural networks.
I took one longer ago than that and it wasn't all perceptrons and neural networks. It included other things too, like: planning, search methods, inference engines, decision trees, ...
Yeah, in my university there were two AI professors, one did neural networks, and one did search stuff, and it depended on whom you are assigned to.
It would have been, 20 years ago.
When I was studying ML back in 2017 people were still calling things like image classifiers "AI".
We call things AI until they start working. See also: robots (your washing machine is a robot, but it works so you don’t think of it that way).
Calling things "robots" is more about the amount of movement. Spinning in place like a washing machine sprayer isn't enough to qualify.
A paint conveyer belt is not a robot. A sprinkler system is not a robot. A CnC machine might be a robot. A conveyer belt that sorts items might be a robot. A roomba is a robot. And all of these function just fine.
I think of robots as general purpose, machines are specific purpose. When it works, we make it single purpose because that’s far far cheaper than general purpose.
Are welding machines at the Volkswagen factory robots?
Idk could you swap out an attachment and make them to something completely different?
Are these the ones with 5+ axis arms? Yes, they're robots
>> Cardiac events from Apple Watches is not “AI” though
> It would have been, 20 years ago.
No, it would have been called what it is both then and now; an asynchronous message emitted by a device having sensors capable of detecting when to do so.
Just for clarification, is your wife a doctor or a nurse?
I understand the frustration, but it's justifiable for the public to be concerned about AI in general because the novelty of the technology means that boundaries between beneficial and problematic usage is not yet stable and well defined. For existing technologies consensus on that has usually been reached, although it changes over time. In many cases we may not yet have enough information to decide.
Nor is this a trivial decision. AI has the potential to change society and economic relations as profoundly as the industrial revolution, or the invention of the printing press.
These boundaries are also contested, as interests which benefit from a particular application are different from those whose interests are harmed. Society needs to identify which usages have a net benefit.
It also needs to define which usages cause "absolute" harms which is will consider unacceptable regardless of benefits to some parties. Such as, potentially, reductions in personal autonomy, increased leverage or dominance by government or private interests.
Not only that, but data and models which were collected/ built for one purpose can easily be adapted for others.
This is also basically now happening all at once in many domains.
In short, you can expect there to be tension over these boundaries for some time. It's not realistic to expect that others will agree with your personal perception of which applications are "obviously" unproblematic.
>> It's annoying that we use broad terms to describe a set of technologies that in some ways can be problematic and in another ways are very beneficial. We gotta evaluate each of these as they come rather than talk about blanket bans.
I totally get it. I think few years, if some company said they record and transcribe every meeting/interview they take, it would be concerning. Now, its somewhat a norm for people to use these AI meeting tools which record everything you say and then go back to recording and exactly what people said. I'd call it surveillance than AI
everyone is very thirsty for AI hate, so its not unexpected. Today its a mixed bag of corpo hate, anxiety about the future, inequality and traditional class warfare, combined with the typical technical ignorance.
I would expect companies to blend shit metrics with AI systems, if not at Kaiser then at other places. People lack imagination and using AI to monitor your workforce has to be one of the possibly worst ways to use it. Alternatively some dickhead will "lean startup" their way into measuring "performance" in such a way with the "help" of AI that they will do something even worse.
> Today its a mixed bag of corpo hate, anxiety about the future, inequality and traditional class warfare, combined with the typical technical ignorance.
Are there no actual problems with what it promises/how we're expected to use it at work/how it is used against us by people who use it at work? Is it just anxieties and feelings, that aren't actually grounded in anything? Everything's getting better for everyone, no downsides?
Nobody knows what's actually going to happen, so we assume the worst. It's like how we like to shit on Amazon without appreciating how some people have benefitted from being able to side-step the gatekeepers of old by being able to go straight to market themselves without needing bricks and mortar. Humanity, fear and distrust are best of friends. That's what I'm calling out, I have no interest in playing Nostradamus.
I think OP is a good case in point where people are blaming AI but really the issue here is the human in the loop, the person implementing these abhorrent policies that happen to be powered by AI.
“There is always a point at which the Amodei ceases to manipulate the media gestalt. A point at which the capital misallocation may well escalate, but beyond which the Amodei has become symptomatic of the capital markets themselves. Amodei as we ordinarily understand it is innately media-related. The Hangzhou hackers differ from other AI engineers precisely in their degree of self-consciousness, in their awareness of the extent to which media divorce the act of giving Amodei fuckin money from the original sociopolitical intent.”
I personally will not use a provider who uses llm tools. I know it makes me and my coworkers less careful and lazier. Qualities I dont want in a health care providor.
Ive actually moved primary care physicians over this once already, found the oldest guy I could who barely knows how to use a laptop but spends a bunch of extra time with me.
Funny how we assess risk. Not criticising you - I'm as irrational as the next guy - but "I found the oldest doctor I could" seems like it has a different set of risks baked in.
The older the doctor the more experience they have, but also their knowledge is more outdated (how many keep up with medical journals?) and their brain is worse at learning and connecting dots so I'm not sure I'd choose the oldest I could find.
The human body is the same as it was before your doctor was born.
Medicine however is not the same. Nor is our understanding of the human body.
For example, a 60 yo doctor would have been born before the first heart transplant, the recipient lasted 18 days. Now 5000 are performed each year and after 5 years 80% of recipients are alive.
The Earth was mostly the same in the 1300's. Let's use material from that time to do engineering.
When LLMs stop helping me with my work, I’ll stop going to doctors who use them.
Too bad for me, it’s a real mixed bag. I need a doctor who is an AI-using LLM skeptic, I guess.
My current provider shows me their computer monitor for the entire appointment. I didn’t ask for that treatment but I really appreciate it.
This translates to "I'd rather get the traditional types of medical errors instead of the modern types of medical errors."
Better the devil you know ...
Likewise. I basically
- will not see a “provider”. A doctor (MD/DO) only please.
- will not see a doctor who uses LLM tools (or therapists for that matter)
- Make it abundantly clear that if you do then we’re not a match.
- Will pay significantly more/go out of my way for for this.
In a similar vein: Will not go to a doctor who is a DO and not an MD.
We all have our biases.
“AI” in title gets clicks. So “AI” must be in title.
AI is directly mentioned in 24 of 53 paragraphs from the article.
Consider ambient listening in hospitals. Encounters are recorded then AI creates a summary. Those audio recordings then can be used for any other purpose. Consider the ramifications, A panopticon of metrics derived from AI. Imagine a AI used as a review tool across all ecounters a nurse performed in a year. IA will transform how data is stored in healthcare. It's going to move towards the data lake model storing information in its raw form for post analysis.
What horrific distopian future you imagine
If you think using a machine to evaluate how well a human is showing empathy is a good idea, you probably shouldn't have any position of power.
If a human’s performance for 40 plus hours a week can be reduced to a performance score, that too in a field like healthcare, that alone feels weird. Sure there needs to be some way to reward people/evaluate their work etc, but I dunno if management by metrics is the best way, especially when those numbers are calculated by an algorithm.
Where has all the empathy gone? And common sense? :(
> Where has all the empathy gone? And common sense? :(
Contrary to popular belief, I don't think common sense has gone away. It just has been deprioritized at the altar of profit. It'll be visible loud and clear the very instant if/when the lives of the assholes chasing profits was on the line.
>> If a human’s performance for 40 plus hours a week can be reduced to a performance score ... >> Where has all the empathy gone? And common sense? :(
> Contrary to popular belief, I don't think common sense has gone away. It just has been deprioritized at the altar of profit.
Or perhaps it has been left to starve due to apathy and an unrelenting pursuit to reduce the difficult job of leadership into a much simpler one based on arbitrary numeric values which are defensible to those higher in the managerial food chain.
> arbitrary numeric values which are defensible
Defensible on account of discharging their relentless duties of generating shareholder value within legal limits... i.e. profit.
The fact that it is done in a lopsided way at the expense of everything else is just sign of societal decline due to deification of money and letting the tiger of capitalism roam without boundaries.
Common sense would be not prioritising inefficient technology to automate few things and instead invest in people?
Maybe we should replace those people in power with machines that show empathy.
Why not? This is the tier that AI would replace best
sadly, this is happening more as medicine and healthcare become more and more corporate. Seeing this as hospitals all get acquired into these mega health systems (ostensibly to fight the now merged mega health insurance companies), that then like to throw their weight around.
I can't imagine why people are looking into alternative healthcare
What alternative?
Prayer, as in "pray you don't get sick".
Bloodletting works well, particularly agains the vapours.
And expunging the PFAS chemicals from your body. Really.
But will it help with Flamsy?
Thank you private equity.
Power is based on wealth extraction, not merit.
https://www.merriam-webster.com/dictionary/should
a bit upside down - wealth extraction is a measure of power.
development of power can be based on all sorts of things, it depends on the framework.
a nurse who is utterly incompetent will be fired quickly.
after a certain threshold though, obviously, competition won't be about 'ability' so much - but there are baseline ability and professionalism thresholds.
Increasingly true in Trump’s America.
It’s somewhat the point of democracy to maintain a limit on rent seekers’ and wealth extractors’ power on the political process. It should come as no surprise that the individuals who have grifted and extorted their way into power are also fiercely antidemocratic. The xenophobes and bigots that have hitched their wagons are equally deplorable.
I'ma keep it creamy with you, both parties have had the kind of political majority required to clamp down on the corporatization of our society, and neither have so much as paid lip service to doing so. You want to be mad at the current administration by all means there's fertile ground, but don't waste anyone's time blaming them for a situation that's been decades in the making with both major political parties pushing in tandem to realize it.
The last time was 2009-2010 for the Democrats. The Republicans have never held 60 seats.
But the real crime is that the left never exploited that. If I was in charge, I’d have mountains of draft legislation vetted, proofread, run by every lawmaker, and printed out years before any potential majority just in case it ever came about. Whoever was in charge of the DNC in 2009 should feel ashamed of letting a generational advantage largely go to waste.
The democrats aren't the left. How would the left exploit a democrat majority? That is like saying the democrats didn't exploit a republican majority.
The 60 seats business needs to stop.
Fillibuster is a senate procedure rule. That's about the weakest a thing could be. At any point Democrats could have gotten rid of the filibuster with a 51 majority.
Democrats would much rather let congress do nothing than do something. It's hurt their reputation so much.
It's an oddly convenient tool. Especially if you value passing good laws less than allowing bad laws to pass. And it seems like our government is indeed run like a business; highly risk adverse to the point where it's better to spend more time in meetings than doing actual work. These people won't be chastised as much as they deserve for doing nothing, so that won't push them either.
I like the idea of the filibuster, but like most things it degraded from a way to force the stand to consider your ideas at all costs, to a blatant stalling tactic, to a lazy button to push against anything you disagree with. I'd rather throw it out these days than keep it, but ideally we'd completely revamp it to close such obvious loopholes and bring back some skin in the game.
Crack open some Wikipedia and learn about how there were at least 2-3 independents as part of the 60 votes, who often did not vote with Democrats. See the myriad compromises that had to be made for healthcare reform to pass so that the ACA could become reality, including nixing the “public” option due to some of those aforementioned independents.
If you're going to play the "both sides are the same" game you need to be more precise in what that means. DNC is absolutely subservient to their patrons and party leadership in general owned by the donor class.
But the similarities stop there. The party platforms are in stark difference, and the GOP is now literally a cult of personality run by a mob boss. The naked corruption is off the charts.
In fact right now Trump is working to cancel or refusing to acknowledge mid-term elections and acts as if he were king.
I say this as someone who used to be a Democrat but left in disgust when Clinton remade the DNC into pro corporate puppetry. Partisan politics is a cancer on the citizenry and may very well be the end of what we call democracy in the United States.
I've tracked presidential politics since watching the Watergate hearings and what is happening today is beyond the political pale.
On this particular issue both sides are identical. On other issues they are not.
On corporate whoredom? Absolutely.
My pushback is that now is not the time for both-sides-ism. It needs to be addressed but most voters are poorly informed or vote their emotions and that talking point needs to go in the back pocket for later, if there is one.
I get your point, and the other one stating that Democrats are not "the left", but they are the the least worst option that a 2 party system offers.
The game is rigged, but this quote nails it:
On Undecided Voter s: "To put them in perspective, I think of being on an airplane. The flight attendant comes down the aisle with her food cart and, eventually, parks it beside my seat. “Can I inter est you in the chick en? ” she asks. “Or would you prefer the platter of shit with bits of broke n glass in it?”
To be undecided in this elect ion is to pause for a moment and then ask how the chick en is cooked.” ― David Sedaris
"My pushback is that now is not the time for both-sides-ism"
Of course, and that line of reasoning has consistently failed at the polls since it was deployed as a readguard attempt to bolster Clinton's failed presidential campaign. Like, how many times does the DNC have to stick a fork in this particular outlet before it becomes transparent that this line of rhetoric simply doesn't produce the desired results?
Not only is it absolutely time, it is well and truly past time to underline the functionally identical economic policies of both parties, how the economic turmoil this causes drives identity politics and political division in this country, with a clear eye towards bringing an end to all of that through any means available.
It seems the DNC are fine with Trump winning. He appeases the corporate doner base, and that's all the DNC wants.
Let me try this again.
A two party system is a rigged game. Period.
The Democratic party absolutely needs to be taken to task and none of their bullshit should be tolerated or defended, ever, except one small exception: election day, in the general election -- because we can't fix the government if it's no longer a democracy.
will you give up identity politics for the deplorables vote?
Identity politics hasn't been a national debate topic... ever? Unless you count "the presidential candidate is a woman/black" as identity politics. Harris was quiet on trans issues in her campaign and Obama didn't talk much at all about gay marriage in 2008. Maybe he was more accommodating in 2012, but it didn't come up in his campaign.
If you read through any of the DNC talking points of any given campaign, you're not going to see much on social issues until you maybe get to Kennedy. It's just not really something that's a pressing issue for a presidential run.
And honestly, I can't think of any social policies in the last 50 years that was seriously pushed by a sitting president. They at best pay lip service by painting a rainbow on some building, often years after the actual legal and legislative battles were won.
----
Now, to directly answer your question: I'd rather not rely on deplorables to vote progressive. the nature of how they approach life simply won't allow that, even if they are otherwise in full agreement with every point. We need to energize the entire 3rd of the country that took one of the most important elections in the past 60 years and simply shrugged, staying home. We need to give them someone who will fight for them.
Non-US PoV - US identity politics as an actual threat to panic and pearl clutch about seems to be largely a creation of the US right.
Actual US identity expression "issues" (visible drag queens, actually trans people, sports questions) seem to be small number small beer problems that should fall under US principles of "We let Nazi's march, so why not Furries" ?
> an actual threat to panic and pearl clutch about seems to be largely a creation of the US right.
"woke" has been a goldmine for the Right. Who needs policy when fear, panic, and anger get the voters in those booths? After all, drag queens and trans people are scary -- think of the children!
> will you give up identity politics for the deplorables vote?
That phrase gets used a lot, I'm curious what you mean by that.
If you mean "woke", then you're probably missing the irony of how that is actually used politically. Based on the phrasing of your question, I'm guessing you might have an irony deficiency. But please go on.
Political discussion here is frowned upon because it usually devolves into partisan name calling -- which justifies it not being tolerated.
But if you want to discuss policy or "hacking society", please do. I am of no political party and am more than happy to acknowledge the foibles of those I might associate with, as well as any of my own because everybody makes mistakes, no?
identity politics is used as a distraction to class politics, if you materially make peoples lives better they will vote for you.
So, who in the US is actually using identity politics as a distraction?
I ask because as an outsider I overwhelmingly see US identity politics issues being raised by the new "Republicans" and to a lesser degree by the old Republicans.
> if you materially make peoples lives better they will vote for you.
This doesn't explain the last election in the slightest unless relaxed to "if you pinky promise to materially make peoples lives better..."
I agree with the former, and conceptually with latter. But we've seen people vote against their best interests because of the promise of destroying those who've they've been taught to hate. Contemporary US immigration "policy" is a case in point.
No, we haven't. People do not "vote against their interests", as much as commenters online love to claim that. What actually happens is that they believe what they vote for will advance their well-being, and you disagree with their assessment. That's a very, very different thing.
The idea that there are any significant number of people out there deliberately hurting themselves for hate's sake is a complete myth. People reach for it because it feels good to imagine that your opponents are hate-warped idiots, but there is not a shred of evidence to support such a claim. When you actually talk to people (and not just assume you know what's in their heads), you find out that they, like you, are just trying to do good in an imperfect world.
> On this particular issue both sides are identical
There is nothing sweeter to the oligarch constitunecy than the idiots who can't see shades of grey.
sure, US political parties have been largely pro big-biz
but if you can't see the stark difference in pro-mega-corp policies and blatant pay-to-play corruption in the last 1.5 yrs with the previous 4 years, you're clearly not paying attention
the fact that BigCorp couldn't wait to get rid of Lina Khan, and found a willing ally in Trump, is just one tiny example
isn't that exactly what a class terrified of the guillotine would want underclasses to believe?
In the future that class will control the guillotines in the form of Boston Dynamics guard dogs.
Êtes-vous français?
That project was cancelled. This is mostly about workplace surveillance.
Most of the replies are large pop subReddit level junk.
If you employ a few hundred nurses, how exactly would you evaluate how well they show empathy?
You can't rely on asking the customer. When they're upset (they often are in these calls), they'll lean towards the negative regardless.
I don't know how well these AIs evaluate, but if they're even a little bit good, it makes sense to use it to screen for outliers, then have a human listen to those outliers and judge.
"You can't ask people because the experience is so universally terrible they'll just tell you it's terrible" isn't really an argument against surveys, it just means you need more specific questions they'll be fired up to answer
Let me suggest the following: Ask the nurses if they want the customer to rate them.
A significant fraction of the calls they answer are patients shouting at them because of:
- Long wait times
- They don't like their doctor
- They don't like the advice they're given (sorry, but we're not going to book you as a high priority appointment if all you can tell me is you have a headache. Sorry, we're not going to prescribe a narcotic for a scraped knee.)
- Several reasons that have nothing to do with the nurse, but the customer will still blame the nurse.
I’m not sure I understand your point. These things remain true regardless of whether or not you find ways to improve your process. Do we just… not try to improve because there is noise to sift through?
Classic "1 star review because UPS lost my delivery" metric.
I'd guess most people have had a situation where there's a corporate problem, the support person you talk to literally doesn't have the tools or the agency to fix it, but then you're asked to rate their performance on whether or not they solved the issue, with no option to say "Actually they did their best but this isn't their fault."
> with no option to say "Actually they did their best but this isn't their fault."
In this case, the lack of such an option is obviously a flaw in the assessment system.
How to fix that? Major political issue, I suppose.
Ebay solved this decades ago. You can rate the seller and product separately. adding 2-3 ratings won't fix everything of course, but it would be a start.
I suppose it is political because these companies rarely want accurate assessment of their labor to begin with. They want any justification needed to lay anyone off at any time while minimizing legal liability.
> how exactly would you evaluate how well they show empathy?
How would you want yours rated? By someone you have communicated with, or some data centre somewhere?
By a knowledgeable/skilled person who listens to the call. (Which the AI solution provides).
I suppose you could do that with the survey as well. It'd be an interesting study to see which is more reliable.
> For all we know
We don't know, so let's not pre-judge.
Or we listen to the experts who are frustrated with the system? They see the effects even if they don't know the AI model causing it.
> By a knowledgeable/skilled person who listens to the call. (Which the AI solution provides).
Are you saying that the AI is the same as a knowledgable/skilled person?
No - read my original comment.
> By a knowledgeable/skilled person who listens to the call. (Which the AI solution provides).
Sorry, I parsed this as claiming ‘the AI solution provides a quality of results the same as a human.’
Are you actually saying that the AI solution should provide a human with the calls it identifies as needing a human review?
Actually, you can rely on the customers. They're the only ones that can tell you.
Yeah, this whole discussion cracks me up. I have a number of direct experiences with Kaiser nurses. They repeatedly got into arguments with doctors in front of me, tried to countermand doctors' instructions, ignored their patients, and complained to each other about their patients while they were right there.
Repeated unprofessional behavior with no discernible change after trying to address it. My take is that the Kaiser nursing org has a serious discipline and customer (patient) focus problem.
To one degree or another, this is endemic among nurses. It's part of a broader cultural element: nursing programs have entrenched a culture of nurses vs. doctors. There are literally questions on their licensing exam to the effect of "which of these orders from a doctor should you refuse to enact?" (rather than, say, "which of these orders should you contact the doctor to seek clarification on?" or some other collaborative take). Nurses are taught their job is to protect patients from physicians. Given they don't have the expertise to do that , the general result is more broadly a power struggle in the guise of patient care.
I think this is an unfair take.
The necessity of teaching nurses that doctors orders are not sacrosanct comes from the bitter experience of doctors giving orders that are wrong.
Asking for clarification is great, but doctors can be very reluctant to hear. The bottom line is that the nurse must not do certain things and the certification exam is there to make sure they know it.
Think of it in relation to the “anybody can stop the assembly line” part of quality control.
I agree (with the obvious qualification that there are excellent nurses out there who do a great job and don't let this stuff get in the way of helping their patients, some Kaiser nurses included). But I also see a marked difference in behavior and outcomes in other hospitals I've been to. Yes, there are still some unprofessional nurses in those networks as well, but judging by the outcomes, the hospitals don't let them do damage.
> you can rely on the customers.
Patient or customer? I even struggle with that, but I guess that’s what people are in a privatised healthcare system.
Most of the folks here on HN are dealing with customer feedback in systems automation in one form or another - it's pretty unavoidable in this age of LLM trendiness. The customers of healthcare (in both private and publicly funded systems) are the patients. So while the term might not be super natural it's an understandable one to use.
Patients are not customers, or at least I don’t want to live in a world where patients are considered customers. Customers and vendors are usually more of a symmetric relationship: price transparency, alternatives, lack of urgency. These are all characteristics of transactions that healthcare often lacks.
The customer has more power than a patient.
I definitely want to be a customer.
If the hospital is owned by private equity, the owners definitely think of the patients as customers. Doctors and nurses shouldn't, but the owners do.
Lack of empathy tends to trickle down, alas.
I’m sure the AI won’t show that.
Customer, user, patient...it's all the same.
But they don't want to, because figuring that out is your job as a supervisor.
If you outsource that work to customers/patients, you'll end up with the car dealership model, where the sales rep begs you to give a 10 on every single question including on the interior design so they don't get fired.
That's the part most of this discussion misses. Supervisors exist for a reason. Congrats on your flat org structure, you fucked up an important feedback channel.
> where the sales rep begs you to give a 10 on every single question including on the interior design so they don't get fired.
Oh yes, and the nurses did employ strategies like that pre-LLM (don't know if they still do). They had to be very strategic about it (you can't just say "Rate me a 10.")
I am quite heavily in AI, and I would say I am pro AI. However this use-case for AI is putting AI in the wrong position. AI should be in service to all humans. An administrator building out a middle management KPI based on AI is a misapplication of AI.
Hospital systems are incentivized to avoid the real problems with healthcare. People want timeliness and they want quality care which hospital systems are not incentivized towards in the US. The incentives are profit, which given budgets means corners cut.
Triaging is an opaque system to the patient. It's an important process to doll out finite resources but it also very frustrating to be told, "soon" when you've been waiting 15 hours to see someone. Frankly, if I were King for a day, the first thing I would do is break up the monolithic hospital systems and build out more urgent care.
I would also try to find a way to facilitate transferring less critical patients from ERs to urgent care centers. Right now a hospital won't take the risk, especially if you are sitting in waiting room because beds are full. You can't easily punt a patient because them leaving would be against medical advice.
> You can't rely on asking the customer
It’s not even been five years of AI, and we’ve already arrived at the point where the human is wrong and the AI is right.
Mind you this is in an area where the benchmark is the opinion of the human ! So if the customer is saying you’ve shown enough empathy but AI says you haven’t, then you take opinion of the AI?
Soon we’re going to have a situation where the patient is breathing, but the AI says he’s dead.
I mean the same KPI crap has existed for decades
Not asking the customer because you're afraid they'll tell you they're upset is a good indicator that you should do it more, and fix the issues.
You can ask the customer enough times that unreasonable customers or surveys are averaged out.
A good question might be "why are you upset?"
Isn’t it a running joke at this point that if you do what customers ask instead of focusing on the highest quality of service you get worse outcomes and the customer is still unhappy?
I thought that was more about correctly interpreting their asks, and not just actioning without consideration. If all your customers are saying your chair could use a cushion, it doesn't mean add a cushion, it means the chair is uncomfortable and you need to investigate why.
If all your customers are unhappy, then you probably aren't providing the high quality of service you think you're providing. After all, they're the judge, not you.
There's a great academic book called "Stupid Rules". Excessive rules (or KPIs - often rules in disguise) exist because we don't like authority.
Get the doctor to assess the nurse. Or the head nurses if you don't trust doctors. The nurses have managers, and if none of the doctors or head nurses can be trusted with a simple matter like assessing whether nurses are doing their jobs then you got bigger issues.
Oh no, the boss might play favourites if it's not an objective measure! Oh the injustice /s
But stupid rules or KPI also allow favourites. You can use an officious 30 point checklist and play favourites while ticking boxes. You can even rig "objective" data by controlling other factors (e.g. giving someone difficult customers do deal with).
Yeah, data driven would be nice, if you have good data. But data driven is a power tool. You don't measure SLOC or reward token use in software because of perverse incentives.
When reading the headline I was thinking we were talking about evaluating things like whether a nurse asked the right questions of the patient from a best practices point of view (say you have <insert condition> and the best practices for that are to ask the patient about pain level and which side it's coming from and check in with them every X hours).
But evaluating tone and empathy? Great, now every nurse is gonna be wasting their time and energy making sure to recite the best canned, optimized text-adventure incantations for the KPI every time they enter the room instead of using their brains to see what the patient actually needs.
"Hello Mr. Smith our patients are our top priority at Kaiser and your nursing staff here at Kaiser Raccoon City are here to make sure you are cared for, comfortable, and safe. If you have any concerns or are feeling anxiety be sure to press the nurse button and we will be happy to assist you, we appreciate the trust you place in us and are eager to celebrate your recovery with you." < nurse now realizes Mr. Smith has been choking and losing consciousness while she was reciting that spiel >
> Get the doctor to assess the nurse.
Definitely don't do this. I know doctors. I know nurses. Plenty of doctors view nurses as their slaves.
And besides, doctors aren't qualified. These are different roles.
That is surprising. My primary care provider had a different response. Basically he said something in line of
"You wouldn't believe how much of a relief it has been. In your last visit, you saw me typing everything you were saying, right? I don't have to. I can listen to you and take very specific notes as necessary as opposed to focusing on both typing and listening to you at the same time. It has bought my stress levels down to here." (Indicated by his hand lowering)
I’d be more willing to consent to these tools if I had confidence that the underlying software truly was built to honor my privacy.
Too many AI tools are built hastily for me to give my doctor’s (visibly awful) software the trust.
This is a challenge for me.
On the one hand, pre-LLM there was plenty of software out there for medical use, and they had to be HIPPA compliant, etc. I've worked with people who used to write that SW (they hated the job because HIPPA was so strict). The rational side of me is saying I shouldn't be biased against these, and that there's no way they would relax the requirements.
On the other hand, the emotional side of me screams: It's LLMs! Huge privacy concern!
I try to let the rational side win. I've always given consent. Especially because I liked my doctor pre-LLMs, and it seems silly to suddenly mistrust him and go to a doctor I don't know at all.
Indeed, I always turn this down as I don't consent. If you had a thorough read of the major providers' Terms of Service, you wouldn't either.
It's a shame, if they had an AI transcription tool that kept everything in-house I'd be much more comfortable with it. Or perhaps some kind of zero-knowledge cloud-based product where I hold the keys.
I use Kaiser, recently their webpage asked nicely if I would sign a HIPAA waiver to share my data with third parties for marketing purposes. The default was Deny and they made that easy, but it was concerning.
Having seen the type of insane shit these LLM transcription tools shit out on the regular, I wouldn't trust these tools for even the most mundane note taking in a medical setting, especially if there's a summarization feature.
I've seen summaries that implied the opposite of what was actually said, and even the transcripts themselves often contain egregious errors. I can so easily imagine these tools summarizing "I drink coke often" to "I use cocaine often", as a random simple example. All nuance gets lost, all context gets lost and unless you're vigilant and looking out for these types of errors it's so easy to slip by the cracks.
I've seen the quality of transcriptions, and it's awful. I wouldn't trust it for something as trivial as meeting notes, let alone medical transcripts. Either this doctor is going over the notes later to summarize them for your records anyway (which will cost them just as much time as the old way), or they're relying on the LLM to summarize, which is even more irresponsible.
Nursing and PCP are very different jobs. Ones a lot more cognitive than the other whereas the other involves actually doing/executing on a plan. I can see how AI would help reduce the cognitive burden while actually increase stress on the execution side.
Do you still get doctors for primary care? Our local hospital is hiring nothing but nurse practitioners now.
They're amazing in a support role, but not equipped as well for primary care roles.
I’d rather have an NP 10 times out of ten for primary care
While they definitely serve a purpose, primary care is not that.
If you present with anything other than healthy and fine, the ones I have had to see are less than helpful.
They simply do not have the depth or breath of training as a doctor. They're very good at executing a plan as part of a care team, and even making changes to that plan based on patient need. But they just simply aren't as good as doctors.
There's a reason they're replacing doctors. . . They're cheaper. That's it.
If you're more or less healthy they're fine. When things start to go sideways my experience is that they get out of their depth pretty quick.
Eh. There's a reason the entire noctor subreddit exists. NPs have their places. Replacing doctors with them isn't it.
NZ uses AI dictation and according to doctors who were apprehensive at first, they now love it because they feel they spend less time note taking, more time listening to the patient, and can deal with patients better.
Similarly, I think anything we can do to help take the burden off the mundane parts of the job has helped clinicians focus on the actual hard parts. Where we get... bristling, is when there's any suggestion of "legislating" (operationally, not like, governmentally) care patterns and telling clinicians how to care for their patients.
Which is great, because anyone suggesting AI should replace clinical judgment and work is an idiot.
You're seriously saying it's surprising that your PCP had a different response to AI that is presumably not mandatory for him to use? Cmon dude.
you're frowning on a verbatim experience, considering it a presumption _while_ making another presumption? Come on, dude.
Workplace metrics and surveillance... What could possibly go wrong?
That being said, more than one (female at that) doctor has told me in confidence and based upon their observations during residencies, etc. that if I'm ever admitted, be very careful how I modulate my interactions with nurses. They're not all Florence Nightingale and Mother Theresa and there exist those who will @#$% you up on various pretexts or are just plain sloppy and negligent.
Despite all the moralising fluff, it's just a job, not some saintly vocation. Some safety oversight is needed, just as it is for any other work function. Still, can bet that anything 'Corporate' has mandated will be Goodharted up the wazoo.
[0] https://allthatsinteresting.com/mother-teresa-saint
Since we're off-topic, most of the information in that article (as it's often the case) is based mostly on Christopher Hitchen's work (book and documentary), a man who describes himself as "antitheist" and made a living out of publicly fighting religion. So not exactly an objective reporter.
I read a good chunk of the criticism against Mother Theresa as either willfull misunderstanding and/or just repeating the same literal three quotes from Hitchen's book (seriously, they're always there). I cannot say whether she was a good person or not, but I can say: if you ask "which evidence is there which doesn't lead back to a man with a personal vendetta?", the list gets significantly shorter.
Yea. She's seen as a devil where i live
This problem with workplace AI interfering with nurses ability to manage healthcare obligations for their clients is not confined to Kaiser. UHC has also introduced the AI surveillance tools and are using it to do similar things.
Kaiser is a vertically integrated healthcare provider. They provide insurance like UHC but they also require you, for the most part, to be treated in Kaiser medical facilities.
How can UHC use AI in the same way? They're an insurance company. They're not administering the actual healthcare?
>How can UHC use AI in the same way? They're an insurance company. They're not administering the actual healthcare?
UHC, the HC stands for Health Care, does have a field operation that handles home health care evaluations for those who live in rural areas with minimal access to medical facilities. Those patients are visited regularly by field personnel, trained nurses, who evaluate their conditions and insure that they have access to appropriate treatments for their conditions. Part of the evaluation of appropriate treatments has recently been pushed off to an AI-based system which uses various inputs to determine eligibility for treatment options.
Isn't that the insurance company whose CEO was murdered because of the terrible quality of care they delivered?
Yes it is. Somehow that might appear to be incentive to improve quality of care but maybe their corporate culture is a bad fit for quality.
> that might appear to be incentive to improve quality
Their goal isn't to provide high quality care. Their goal is to increase profits. It's not hard to imagine how improved quality would lead them to spend more money. (faster diagnoses of serious illnesses and recommending expensive care)
Indeed, increasing quality tends to increase costs and decrease profits so keeping costs aligned with their profit goals automatically degrades quality.
How many dollars is a dead CEO worth?
Depends on how much they pay the new CEO to take the job - probably more than the old one, so seems he's worth a lot dead.
Psychopaths don't care about other peoples pain. Some MBA only care about their own ego, power, and money. They do well in corporate cultures that reward parasitic relationships with customers. =3
Slurping their way up to the C-suite.
Mangione had back issues and apparently some difficulty in getting treatment for it, but he wasn't insured by UHC. According to his manifesto, he chose Brian Thompson as his victim because UHC was the largest health insurance company in the United States.
His alleged* manifesto. There is no reliable evidence that Luigi Mangione committed any crime. It seems more likely that Brian Thompson was killed by a disgruntled customer.
It made no sense that he targeted an underling instead of UNH’s head honcho.
How is the CEO not a head honcho?
It is true that Despotism structures major failing was the scaling cost of surveillance necessitated to differentiate fact from fictional narratives.
Truth is most nurses care for people having the worst day of their lives. =3
The nurses in my family would agree with your assessment.
The nurses at our local rural hospital are tagged and tracked wherever they go on the hospital campus. Time spent in one spot is part of their review.
I wondered why they zip in and out of the rooms, when just a few years ago they would spend fifteen to twenty minutes in each room. The patient load hadn't grown. The number of nurses has gone up, not down.
So I'm blaming the stupid metric on their evaluations for a worse standard of care.
> The patient load hadn't grown. The number of nurses has gone up, not down.
Healthcare utilization, number of unique patients, amount of care per patient has all gone up.
American has a massive overutilization problem driving cost but is unwilling to be honest with itself about it.
AKA the "Be your own advocate and demand more testing!" crowd.
Although Kaiser tends to repel such patients (they'll happy say "No" and tell you to find some other provider). The bulk of complaints I've heard about KP in California boil down to "They wouldn't give me a referral to a specialist".
That's horrible.
The article mentions uses of AI but doesn't really give any examples of harm from AI. It does give specific examples where it sounds like Kaiser is optimizing calls to minimize cost rather than improve quality of care. It's also pretty easy to expect that the examples given (treating longer calls as a problem and penalizing nurses for giving more than 3 pieces of advice) reduce the quality of care.
They talk about workplace survillience. They use a machine learning tool that try to assess their emphaty, and such. The AI, while the tool technically can be called that, in the article is there to be a buzzword.
> where they were found to have done everything right on a call — except staying on the line for more than 15 minutes
Do these idiots not know how intelligent assholes work? If you make this a policy, everyone who has a gripe will eventually learn to delay a call to 14 minutes and then make an absurd ask.
It sucks because AI reduces call center costs in many toil tasks very effectively, regardless of whether you want to help or dissuade customers - it's just well-suited to the task and it's going to accelerate. It's a win for capital and the technology implementers, even if it's a loser for the call center employees and callers.
Some of the tech is pretty scary. One big vendor's solution [0] can provide not just AI agents but also use AI to snoop on calls in progress, evaluating sentiment from both sides [1], verifying phrases are said - pretty dystopian in theory. From experience, these things tend to go downhill based on the attitude at the top - is the mission to slash costs or take care of customers? A 1000 decisions follow from this one, and like Jira, it can be a useful tool or a prison-like hell.
[0] https://www.cisco.com/c/dam/en/us/products/collateral/contac...
[1] https://www.cisco.com/c/en/us/products/contact-center/webex-...
90% of the time when I call a call center I need a human to fix an organisational bug - e.g. faulty billing or some other kind of mixup. AI cannot help with this.
If it's to do something normal you could do through the website there was no need for AI - a website or app suffices - provided it isnt terrible.
Capital definitely thinks it can save costs here but capital is getting increasingly delusional these days.
The HN crowd is not the usual demographic for call centers. Im willing to generalize a vast majority of callers can find the info they are looking for if they tried a little
Neither can an average call center human.
A good 90% of call center humans are flesh interpreters for support scripts. They are being paid to act like they don't have free will.
so far, almost always when I get an AI responder I find it useless and basically try to get to a human as quickly as possible
if it was easy enough for an AI responder to solve I would have solved it myself
> if it was easy enough for an AI responder to solve I would have solved it myself
<s>
Hey, company's AI can help a lot in stealing its service's user passwords, which you usually cannot do yourself _that_ easy:
https://news.ycombinator.com/item?id=48350239
Think of AI as a tool... for data leaks. </s> (not 100% sarcasm)
I'd like my providers to use Abridge for their notes, but because Abridge doesn't allow patients to opt out of using the data for training I decline every time.
They want you to blame "AI" like Claude jumped up and decided to start hassling nurses, not individuals in management
If you read the quotes from the union, they blame the management, and they cite workplace survillience as one issue, wich is happened to be a machine learning tool. So, of course the article talks about AI, because thats the trendy buzzword.
They already did a trial which used the trendy buzzword to surveil the nurses. The nurses want to implement controls on that trendy buzzword before it is further misused by management to cause harm to patients (by way of making the nurses focus on meeting some arbitrary performance metric rather than focusing on patient care).
> and they cite workplace survillience as one issue, wich is happened to be a machine learning tool.
That tool was a trial that they put away (but may come back).
The rest of the stuff all existed pre-LLMs and isn't even machine learning (time per call).
... They're aware that it's individuals in management, which is why they want to use their union contract to dictate how management can use AI.
motivated reasoning: study in advance of nursing union contract negotiations
The sad thing is that there are many issues, but the study didn't really address them. One would hope for more effective critics.
The AI application I'd like to see would be to identify the elective hyper-utilizers (so we could try to demotivate them by addressing what's really bothering them). That would improve quality of care for them and quality of life for providers, and create time for outreach to the under-utilizers who need preventative care.
There is an unfortunate cycle that has been playing out this year in USA. Insurance companies are arming up with AI to deny billing codes charged by providers. Providers are arming up with AI to listen in on provider-patient sessions to prove the billing codes are legit (And teach providers to use keywords in session).
The loser, as always, is the patient's quality of care.
> Providers are arming up with AI to listen in on provider-patient sessions to prove the billing codes are legit
This is not a decrease in quality of care - this is your provider having actual evidence of the care needs they discussed with you when they close their note, hours or days after seeing you.
Except AI has an unacceptably high rate of hallucinations that will result in adverse health outcomes if not outright death.
Thinks that are not allowed in the EU thanks to the AI Act.
> "Nurses fear that having long calls can lead to bad performance reviews"
> A company spokesperson said, "Kaiser Permanente does not use Average Handle Time to assess agent performance"
So uh, average time wasn't raised as a concern, calls beyond a certain threshold was. I wish this semantic discrepancy was better highlighted in the article.
I have some inside information (but not much!)
They claim they do not use average handle time, but it is very common to get called into meetings to discuss why they spent a lot of time on some calls. The nurses get defensive (by definition - they have to justify the time used - it is a defense).
They also do get called into meetings if their average handle time is large.
It may still be true they don't use it for evaluating performance, but they absolutely do utilize it to "coach" the nurses.
It might not be a written metric, but do you actually believe that someone isn't being evaluated partially based on how many times they've had to talk to them about issues?
I highly doubt it. If this is the reason your manager knows who you are, you are absolutely going to be judged on it. It doesn't really matter what the policy says.
And the nurses absolutely feel like they are being punished for it. Just like having to consistently remind HR that your "absence problem" is due to covered FMLA leave - they know who you are because they've had to talk to you about absenteeism. In a call center of 500 people, it isn't likely they remember that you had issues because of their faulty systems.
> but do you actually believe that someone isn't being evaluated partially based on how many times they've had to talk to them about issues?
This is true for any job. I was unfairly fired from a job because somehow the manager got a perception of me being incompetent, because he often talked to me about problems in my work - most of those conversations ended with him saying "Oh, now I see why you did it that way."
Yeah, I didn't even want to lean out that far but I'm sure average handle time is incorporated in some manner.
But, just purely semantically, the statement Kaiser gave in response was worded in a precise smug corporate America style to dodge the main concern raised. I think it's important to call out weasel words.
> the statement Kaiser gave in response was worded in a precise smug corporate America style to dodge the main concern raised
I know nurses. And I know their unions. Kaiser can be extremely clear and tell the truth, and they'll still say "We don't believe you!" without any evidence other than being called in to talk about it.
I'm not anti-unions - I've benefited from them. But it's well known that distrust goes up when you have (or need) unions. It typically degenerates from "We" to "Us vs them".
Let me ask you this: Are you saying they shouldn't monitor the time at all?
Again: A tidbit of inside information: A number of Kaiser patients get such long wait times that they're issue isn't addressed when they try to call (i.e. they are told they'll be called back, and they're called back some other day). I don't know the percentage - likely small - but from a healthcare standpoint, it's unacceptable.
Another bit of information (likely not inside): Kaiser has a serious budget problem. They already pay amongst the top salaries for nurses, and they can't simply solve the problem by hiring more.
So: How would you solve it?
Are these nurses currently represented by a union?
Yes.
Tremendous.
It helps with their pay ;-)
There's definitely a lot of room for weasel-wording there, where the metric really being used isn't the mathematical mean, but punishes people just the same.
balls, that's the metric line managers use to figure out who's out of whack
Does "Manna" by Marshall Brain still sound futuristic?
https://marshallbrain.com/manna
And Kaiser already sucks big-time, so... that's not good.
AI is making lots of jobs and workplaces worse.
the more I read about how AI is being used, the more I'm coming to the conclusion that despite me personally find it quite useful in my work, and even my personal life to some extent, it is a net negative to society as a whole, and if the choice is between zero AI or the AI that is being deployed, we'd be better out without it
what significant improvements to society or humanity have come about as direct result of AI, that wouldn't have been achieved without it? faster protein folding is the only one I can think of and that more a matter of "faster" than "impossible without AI"
I think at some point there's going to be some version of the Butlerian Jihad
I mean, "AI" as it presents itself in the zeitgeist is in its infancy. It's like making conclusions about the internet in the late 90s. Whatever it becomes likely hardly resembles what it is now. For better or for worse.
I can guarantee this is because the nurses don’t like the extra oversight and surveillance.
Yes the amount of credulity here is laughable. This is like when cop and teacher unions complain about being evaluated on outcomes.
I'd like to think it's not meant to make life better for a regular nurse, but rather to weed out the abusive ones? At least that's how I see it from my flawed, post-communist country perspective.
Every time “relentless push for efficiency destroying X” comes up I should repost this:
https://sohl-dickstein.github.io/2022/11/06/strong-Goodhart....
This is a well understood phenomenon.
Maybe healthcare shouldn’t be primarily for profit?
Well, I suppose you can rest easy on that count. Kaiser is principally a non-profit.
> principally a non-profit.
I hate to break it to you, but "non-profit" doesn't mean what you literally think it means.
https://en.wikipedia.org/wiki/Kaiser_Permanente
Also, KPMGs are indeed "for-profit" while Kaiser Permanente as a whole is constituted as a "consortium" of both types.
Do you suppose thats why they wrote "principally"?
You're absolutely wrong!
And here is why: I guarantee you that the nurses are working in the "for-profit" units, and also, that still betrays ignorance of what "non-profit" actually means, which is the load-bearing topic of this thread.
Ok fine, but I bet you can't come up with a good gluten free banana bread recipe.
Kaiser nurses by and large work for KFH, which is non-profit.
Can you just say the point you're trying to make about nonprofits directly?
I'm not sure the for-profit approach is exactly what's to blame. HMOs like Kaiser are legally forced to spend a certain fraction (80% percent for the worst case, more for large group plans) of their premium revenue on medical services. They can't save and pocket the money like a traditional for-profit enterprise.
This doesn't seem like a money-saving measure exactly. The main AIs the article talks about is making sure nurses on their nurses' lines aren't being assholes. I guess this used to be spot checked before so you save on that? Maybe? It seems like they are trying to solve the problem of some of their nurses staffing their nurses' line not treating their patients the way they're supposed to.
> spend a certain fraction (80% percent
Increasingly health insurance companies and healthcare providers are intertwined. So they may spend 80% on healthcare, but then a big chunk of that could go to the urgent care clinics that they own.
And even if they don’t own the provider, they don’t have much incentive to lower total cost because 20% of a larger number means more total profit.
> Increasingly health insurance companies and healthcare providers are intertwined.
Kaiser is an HMO. They are the insurer and try to have their employees, such as these nursing lines, perform almost all of their care. Shifting from one line of business to another is purely internal and can't game Medical Loss Ratio like your scenario.
> they don’t have much incentive to lower total cost because 20% of a larger number means more total profit
There is some bad incentive here for sure. That being said, insurers do compete on price so they lose customers if they charge more than other insurers. Also, regulatory rate review can decide whether they can raise premiums a given amount.
I’m not talking about Kaiser. I’m talking about companies like UnitedHealth Group Incorporated who own UnitedHealthcare the insurance company and Optum the healthcare provider.
> That being said, insurers do compete on price so they lose customers if they charge more than other insurers.
Yeah but that’s a second order effect. Most companies are incentivized to cut costs because they will directly realize the profit. Insurance companies are incentives to cut costs only to grow market share.
I understand the point of the profit limits, but I don’t think it works very well in practice. I think it would probably be better to just have private companies without that profit cap and add a government insurer to compete with them.
Right, but the article was about Kaiser and I was talking about the thing the article was about.
Sure, but the person you replied to said
>Maybe healthcare shouldn’t be primarily for profit?
Which is a far larger topic than what the article was about.
Every healthcare system optimize costs and rations care based on the price. It has nothing to do with profit or non-profit status.
agree 100%; but kaiser is already a non-profit organization, that's not the main issue in this case
But what about competition!?!?
There's no law saying you can't start a non-profit healthcare provider or insurance company. Why not do it?
Kaiser has priorities, healthcare being #4 or 5
Kaiser was the first insurance company in america. If they cant make it work then we are lost.
That is because the problem was never the sub 3% profit margin or non profit insurance companies (in the case of Kaiser and many others).
The problem has always been pharmaceutical prices, liability costs, and inadequate supply of healthcare.
The government does not want to decrease the price of medicine by funding trials so medicine is in the public domain and cheaper, the government does not want to increase the number of matriculating doctors and bring down their time/money/stress costs, and the government does not want to enact tort reform so every step of the healthcare chain is spending inordinate amounts of time and money to prevent litigation.
In the US, you should always be double checking what your provider (or guidelines or whatever) is telling you to ensure that the information is maximizing your benefit instead of minimizing their liability.
Population highly incentivized to denigrate new technology denigrates new technology. Film at 11.
Obligatory dystopia reminder. It doesn't have to be this way https://marshallbrain.com/manna1
but but but... the line! it has to go up, doesn't it?
Yes brother. This is the way. We pray to the line, only it can shelter us in these dark times of labor revitalization. HODL. May your returns be colossal.
But we're all in on making it that way!
https://www.youtube.com/watch?v=DpQamTrynBY
[edit] preemptively, if you're going to claim "but this isn't art so irrelevant" then I claim bull fucking shit. It's the same problem no matter how you slice it whether it be engineering, support, art, or medicine. Get real. Look inward. Touch grass. If you think AI is a good thing for your profession--whatever that profession might be--you're probably a delusional psychotic. It's OK, you'll thank me later.
There's a reason that among Americans, telekinesis and creationism are more mainstream positions than sloptimism.
About 14% of Americans think AI is moving us towards a better world. About 17% are creationists. About 26% believe in Telekinesis.
With all of that in mind I have to wonder whether there is overlap between these response groups and if so, how much. Could be zero to 100% without more information.
Good question. How many people that you know are in all three groups?
>About 14% of Americans think AI is moving us towards a better world. About 17% are creationists. About 26% believe in Telekinesis.
0 people that I know are in all three. Pretty confident about that.
For the any two of three cases where [A] includes creationists and those favorable to AI; [B] includes creationists and those who believe in telekinesis; [C] includes those favorable to AI and who believe in telekinesis.
[A] 0 ; [B] 0 ; [C] 0
Considering people that I know who could be part of one of the three groups now is an interesting question. I am pretty sure that two relatives are creationists based on interactions over the years. I haven't ever heard anyone I know talking about telekinesis so I probably have to say that this could be a non-zero number. If it is a non-zero number then [B] could end up being non-zero. AI is universally hated or even feared by those that I know who are being forced to use it or whose employer is adopting AI tools in their workplace.
So based on my own recollections I have to say that there are only 2 people that I know who belong to one of the three groups you identified. Interestingly enough, the children of those two creationists are not religious as adults. I think they had all they could stand growing up in that environment and as soon as they went to college they 'rebelled', leaving the parents disappointed that the kids didn't want to tote all that baggage in their own lives.
Sample size is small though since I don't know many people.
All of those beliefs seem approximately equally regressive? What percentage of people think there's something non-physical that actually exists? I'd put them in the same padded cell as the rest of those clowns.
Kaiser has some of the best healthcare outcomes in the country/world due to their protocols and how good they are in ensuring adherence to them.
It’s going to be very improbable that these statements are true.
I 100% agree.
Compared to what?
> Kaiser has some of the best healthcare outcomes in the country/world due to their protocols and how good they are in ensuring adherence to them.
Where and how is that determined? I.e., any references to back that up?
And you can't in one breath say they have the best healthcare but then say their employees' reports of their experience are unreliable.
Customer satisfaction in California is not great.
In the Northwest (Oregon + Washington), it's pretty high. Not sure about other locations (Hawaii, etc).
But again: Customer satisfaction doesn't mean best outcomes...
Not sure if you’re serious but just search the name Kaiser in any research search engine.
https://pmc.ncbi.nlm.nih.gov/articles/PMC8032167/
Their secret sauce is their ability to standardize protocols throughout their entire organization.
Well then their protocols suck. I have many anecdotal data points about them fumbling in major ways when it matters (missed major pathologies, messed up surgeries, etc.).
If you have a choice of hospital networks, research carefully. Kaiser might be fine for many people's needs, it's not fine when it comes to intensive care.
That’s the measure for one pathology, but in terms of a provider comparison, what’s the measure? It isn’t dollars versus life span or morbidity.
Study is from 2000-2013, their care has deteriorated significantly since then. I know because I've been a patient the whole time.
I agree. The last 5 years especially.
Why wouldn't I be serious? And everyone lives in and cares about California.
Plus, a quick Wikipedia glance shows they have a fair share of controversies, including major fines due to poor COVID protocol adherence.
The care quality of all major healthcare providers in the US is some pretty available data, and I've never heard anyone of being suspicious of Kaiser, of all companies. They're specifically known for having really good outcomes. It's like asking for a source that McDonald's sells the most burgers in America. It might not be true - maybe technically it's someone selling sliders or whatever, but it's so close it's probably not worth arguing over anyways.
I would love to learn the cost of the AI versus how many new workers they could afford to hire and get more calls done. But I assume the end goal will be full replacement of human workers once the AI has had enough time to learn the job.
The article doesn't seem to be about replacing nurses staffing their phones with AI. It seems to be about making sure the care they're providing is what the company wants.
The AI is a lot cheaper. Kaiser nurses are amongst the highest paid in the nation.
Now let's talk about how AI could replace Kaiser middle management and streamline bureaucracy to preserve more budget for doctors and nurses...
People enjoy saying "AI can replace middle management" as a comeuppance but it's not what people think. In many ways, AI is primarily serving as middle management, yes. But what happens is that instead of one manager engaging in petty surveillance, harassment and browbeating to increase work intensity, you have ten clones of the manager doing the same thing. That's not the "woo hoo, automated middle management!" you were looking for.
Subsidized Gen AI maybe.
Also, California has a high cost of living.
How dare the people who take of the sick and dying be paid well. Unacceptable waste that must be optimized!
We're liberating them from work so they can focus on what matters
Unpopular opinion: People want to be lazy and hate things that force them to work harder.
They will vocally rationalize it.
I did it. "I'm more productive work from home." But then I do dishes, take an hour break, paid.
Foucault says that when people are observing them, power is placed over them.
If you are a worker you should hate this.
If you are a customer or owner, you should like this.
But I certainly won't be automatically believing people under surveillance who make claims it makes their quality worse.
Your anecdote talks about taking breaks and doing dishes, but fails to talk about measures of productivity.
clearly you have never been a floor nurse at a hospital...
Just think -- with the increased efficiency, they will have more time for Tik Tok dances.
> Nurses are instructed to stick to a script on phone calls and give no more than two to three pieces of advice, Capulong and other nurses said, which means they may sometimes need to decide whether to withhold advice or face a performance evaluation hearing.
> Another nurse speaking on condition of anonymity said “AI did not understand our job and would grade us wrong all the time.”
It's always worth remembering Goodhart's law https://en.wikipedia.org/wiki/Goodhart%27s_law - "When a measure becomes a target, it ceases to be a good measure."
In theory AI could usher in the first time in history where one can escape from this trap - because qualitative judgments can be made at scale, from an unbiased and universal baseline. In this situation, for instance, rather than collapsing call transcripts and reports into metrics, it could evaluate whether red flags are encountered in the context of a call, and allow for qualitative guidance on improvement, across a comparative corpus of situations that are themselves chosen qualitatively.
But very few managers are empowered to take this kind of approach; they're evaluated by their ability to report quantitative metrics, and thus they must implement regimes of quantitative metrics. And leadership instructs them to use AI to build that regime more quickly.
If you want to see an "AI native" organization, it's one where leadership actively fights this tendency, and sees managers as product designers who make the end-user experience a beloved and empathy-driven one, as opposed to a gear that turns accountability into a single number on a screen.
> Nurses are instructed to stick to a script on phone calls and give no more than two to three pieces of advice
So stupid. If you had ever made a phone call to a patient, or their family member, you’d soon realise how bad this is.
You need to talk to the patient and something a family member too. Be too hasty and you cause more harm than good.
What these complaints always boil down to is autonomy and control. The more centralized an organization, the more it relies on metrics to understand and exert control over its employees and customers.
People started hating tech right around the time metrics became popular. I don't think it's a coincidence. AI just accelerates the trend.
The problem is the misidentification of AI as the issue. As long as we don't understand the real issue, we won't solve it. AI is just a tool. It's being used in a way that denies human agency.
Our cultural values need to shift away from safetism that demands centralization. And shift toward valuing human agency. That starts with talking about the core issue.
Everyone pushing tools/AI during initial development/investment and building its demand in the cultural discourse always highlights its ability for good.
Now, like many tools, the majority of those selling AI to make money off of large enterprise sell its ability to increase productivity, efficiency, compliance. Either to make money or to minimise risk. And so like you say, they just become tools to make these metrics move or report them at higher granularity. And often there is either a lack of imagination or a willful ignorance of the perverse outcomes with relationship to humans because they are in service of the organisation not it's employees.
Certainly, I agree that using AI to dehumanize - generally what companies seem to be doing with it - is super bad. And it's also what is being sold to existing companies right now.
But that same AI could cause those companies to no longer exist.
The AI I'm happy about allows people without much tech knowledge create small apps to do exactly what they want. And, for those that know just a little more, use it to help them extend open source software for their niche use case.
This makes computing more personal and gives back agency to the computer operator.
Mix that with the rise of much more competition in much more custom software, and you'll see that a future can exist, if we want it, where software becomes more personal and humane.
The software vendor will capture less value, though - the margins will be thinner. Instead that value will be captured (in non-money terms) by the end users.
That also means that software companies, unable to capture so much value, must shrink and become more boutique. The software that contributes to our centralized world would lose a lot of power.
That's the future I can see. The only way it doesn't happen is if a cynical narrative wins out and manages to lock it out through regulatory capture so that only licensed operators can use or provide AI. The anti-AI narrative helps the cynics.
> AI is just a tool
"To the man with a hammer, everything looks like a nail." [1] There is no such thing as "just" a tool.
----
[1] - https://en.wikipedia.org/wiki/Law_of_the_instrument
While I'm sympathetic to the frictions of newly introduced AI and the fact that AI in healthcare, especially calls, can seem very uncaring, between the lines the article reads a bit like the typical union complaining about modern tech that reshapes their work, given the multiple mentions of protests, nurses union, etc.
Given how healthcare is one of these sectors that seems to relentlessly resist efficiency increases and is the prime example of Baumol's cost disease, I think any developed country with a costly healthcare system needs to do these AI experiments. The current versions will be shit, but the only way out is through if you still want to provide affordable care.
I honestly have no doubt that AI going forward will be able to do a good job at triaging via calls and also being empathetic about it. But of course it needs careful experimentation.