What do you mean by bearing no real responsibility for its actions? If I use a model to accomplish a task and it fails, I use something else to try to accomplish the task. If it's my responsibility to complete the task, it can't be the model's responsibility unless I've agreed to some sort of guarantee from the provider.
If the provider says "the model will always be right or your money back" then the provider has got responsibility. If there's no guarantee, there's no responsibility on their part, just on the person whose job it is to try and solve a problem with the model.
The "dream" that these labs are mostly selling is the ability for capital to subscribe to their AI for cheaper than it costs a human to do some task. Not to have a "human + AI hybrid where the human is responsible". It's what the whole AGI valuation is based off of, in that scenario, with no human oversight, the agent they lease has to be responsible for the task?
It's not really a dream though? You can subscribe to their AI right now and complete many tasks for cheaper than it would cost to pay a human to do those tasks. Another person can do the same thing but also keep a human in the loop. You and the other person may compete in the market for whatever your product or service is, and you both might do very well or one of you might do better than the other because of a whole host of different reasons. Nothing in the process of developing and selling access to a more advanced LLM requires the customers to do away with human labor, nor does it require them to offer the LLM service with a guarantee that it will never make any mistakes. So far the LLMs have always made lots of mistakes and the companies sure keep making a lot of money.
Right now I think it's still a dream for a few reasons, not the least of which is that all of this goes to shite if you have mass unemployment in a country with more firearms than people legally allowed to own them, a plurality of the population that treats wealth as an indication of personal virtue, and an elite that more-or-less refuses to offer any further evolution of the social safety net past what it was in 1970.
> Nothing in the process of developing and selling access to a more advanced LLM requires the customers to do away with human labor,
That's the hook, though. You acknowledge this yourself:
> You can subscribe to their AI right now and complete many tasks for cheaper than it would cost to pay a human to do those tasks
Businesses exist primarily to make money. It's an iron-clad rule that one must spend money to make money. If they have to spend less on humans to make the same amount of money, they'll do it. Furthermore, AI providers (especially hyper-scaling frontier model providers like Anthropic and OpenAI with insane operating costs) have every incentive to keep the price of their service as close as possible to the cost of the human. Ideally for them, you replace the human that cost $100,000.00 to employ by paying for a subscription that costs $99,999.99 while making the same revenues.
> So far the LLMs have always made lots of mistakes and the companies sure keep making a lot of money.
The clients, sort of. I know my team's velocity has increased. You can screw up with LLMs, like you say. OpenAI and Anthropic? lol no, they're massive furnaces for money, and will be until they can charge that $99,999.99.
> What do you mean by bearing no real responsibility for its actions?
If you give an "intelligent agent" offered by one of these model providers a task of updating the content of your website, and it updates it with inappropriate adult content, who incurs the cost of the machine's error? The model provider generally does not.
It it makes a mistake and deletes your website from AWS, who is responsible?
If it targets another website because it decides that it is "part" of your website and attempts to break into it, who is responsible?
In all of these cases, it's you. It would be the same if you downloaded an open model, ran it locally, and it happened to make the same catastrophic mistakes. The consequence to the provider is that if they offer a product that does these things, people don't buy the product.
In general, the person whose job it is to provide the company with a working, non-adult website and not hack into other websites is the one who would receive consequences for failing to meet those expectations.
The problem I see here is that ultimately, you'll have capital wanting to replace workers like others have said, and have someone roughly equivalent to a manager or vice president driving teams of agents to achieve business outcomes.
These tools can push out more results than a human can hope to evaluate in a business-sensitive, or even realistic, amount of time. You have to take it at its word that it did things right, and there's no real fear of failure or consequence on the behalf of the agent.
> If you give an "intelligent agent" offered by one of these model providers a task of updating the content of your website, and it updates it with inappropriate adult content, who incurs the cost of the machine's error? The model provider generally does not.
Something in your prompt led it to do that, is alex0015's point. The statistical odds of these frontier models screwing up to that extent are so impossibly low that it would almost have to be intentional or accidental negligence on the part of the prompt writer to accidentally have their agent write pornography to their website.
The burden of the mistake would have to fall on the person that gave the tool instructions, because it can't know that what it did was wrong. Wrong is subjective in this case. It only did what it did because you, figuratively speaking, encouraged it to.
Yes but I'd actually go even further than that. We've all had experiences where the model straight-up produces gibberish sometimes, right? It's happened to me with a badly configured harness on a local model, and even also on frontier models like when you used to ask them something innocuous about the seahorse emoji.
What I'm arguing is that yes, it's your fault if you misprompt the model and it does something catastrophic. It's also your fault if you prompt it correctly and it does something catastrophic anyway due to some other glitch beyond your control.
The whole discussion started with the point that OpenAI could be financially responsible for damages if their models cause problems for users. If my job is to design a system that works, and instead my system doesn't work, it's my fault regardless of whether I used no LLM, a local LLM, or OpenAI's LLM. Depending on whoever's in charge of doling out consequences, I might get away from it with zero, light, or heavy consequences. But at all levels, I can't reasonably expect to deflect blame onto the model itself.
If future jobs are simply reduced to liability scape goats (or more appropriately reverse centaurs) for management to pin things on then I'm taking up goose farming.
That's more-or-less what you are now, especially if you work at a company like Meta where 1) the guy at the top holds majority control of the company's shares and 2) keeps making massive, expensive mistakes either by accident or design.
Developers build apartments where they can make money from them, in other words where they can rent them for enough that they'll make back their investment. It's very expensive to build housing, so the only way to make the investment back and have low rental prices is to try to make the building costs as low as possible. A big part of those costs is the price of land.
Or, the only places to build houses with reasonable costs are in areas that weren’t already built out with very expensive houses.
Which will tend to be less desirable areas, by definition.
One approach, of course, would be to also make existing houses less expensive/desirable. Notably, wealthy people tend to have the resources to fight efforts to do that.
The other approach is to expand what land is available to build on. I understand that in the UK, farmers consider it a lottery win if they get planning permission for some of their farmland to become housing.
Despite what many in the UK think about it "being full", this is mostly an illusion from how cramped are the parts in which the houses are allowed to go; the country as a whole is mostly undeveloped.
(There are of course other considerations, with "why did you build on a flood plain?" being one of the failure modes in the UK).
Well, letting people build houses right next to freeways and/or on things like earthquake faults or flood plains is what is being done here. Which is, uh, also a problem. Since those people are now at much higher risk, eh?
Building on farmland has national security concerns (as countries are slowly realizing), as the country ends up dependent on foreign food imports after awhile. Can't grow food effectively when there is a subdivision there instead eh?
In most high demand areas (which are the ones everyone is complaining about, generally), all the decent land (or even just 'normal' land) is already developed.
Bonus - next time around, even the flood plain land might be 'too expensive' to develop on, and folks will only be able to afford houses at the dump, or in a swamp, or the like. Yay.
> The other approach is to expand what land is available to build on. I understand that in the UK, farmers consider it a lottery win if they get planning permission for some of their farmland to become housing.
I've seen that mentality in other parts of the world. The thing is that agricultural land is often protected because it is good agricultural land. It is literally the reason why the cities were built where they were built, since that land provided for the cities. Unfortunately, good agricultural land also tends to be easy to build on and we have a tendency to ignore features that may make it a poor decision to build on. (Such as the flood plains you mentioned.)
Isn't offering app-exclusive deals adjusting pricing for an individual? I feel like that's the whole point of the service. You download the app and get something for it.
Offering frequent customers discounts or free things is a practice as old as the ages. The thing that companies are trying now is the opposite. They profile you and decide how much you can and are willing to pay based on your wealth, lifestyle, and other factors, then charge you as much as they humanly can.
I literally had my internet provider try this. I was moving and went to sign up for internet at my new address so I'd have overlap and not be without internet for any amount of days. Went to their website, saw the prices, called them up.
Well, they informed me that for "me personally" they wont' give me the prices listed on the website. Instead, the only option is a much higher price. I suppose I wasn't supposed to see those lower prices. I hadn't gone to their website in years and presumably the cookies got wiped, because after I logged in and went back to the website all the prices were gone, and it just said I had to call to get a price.
Airlines have also famously tried this, and the practice is spreading. It's consumer hostile and unethical.
I've had multiple accounts with McDonalds and over time, the discounts get worse and worse.
The hook you on the cheap Big Mac Meals, or $1 McFlurry, then over time they discover you actually enjoy Big Macs, so they give you less rewards for Big Macs, as you were likely gonna buy a Big Mac at full price anyways.
If you don't visit for a while, they'll notify you of a discount personalized to you, which is just on the edge of reasonable/worthwhile. You'll head to the store and spend money you would of otherwise not.
In the long run, the data tracking is designed to make you THINK you are saving money, but you are actually worse off! There is a grace period where rewards are good, you earn points and bonus points and you break even, but after a while it goes into a manipulative state to extract every cent from you.
I'm too young to remember this particular promotion (though I certainly ate a lot of fast food in 2004). Data grabbing can't be the only reason, though. It's so much more expensive now to pay a large staff at a restaurant that isn't busy most of the time. Raw materials are more expensive, labor and benefits are more expensive, and the result is a combination of higher prices and lower quality outcomes. If the outcomes were the same the prices would be quite a bit higher.
The only counterexample I can think of is In-N-Out, which is always packed with customers and always has a large and very busy kitchen staff.
In N Out has a much smaller footprint, so there is scarcity going for them. In a suburb of los angeles, there might be an in and out in your town or a neighboring one. There were sometimes a dozen or two McDonalds, BK, Carl's, Taco bell, Del Taco, Jack in the box, etc - multiples of each. 1 In N Out for 3-4 cities, but potentially 6-12 of each of the others.
I think that explains it. The singular Carl's Jr in a nearby city was always busy, for a similar reason. it closed during covid, for whatever reason, and the next nearest one is at least 2 hours away. Compared to the 6 McDonald's in my metro: 4 Taco Bell, 3 Whataburgers, 5 Wendy's, and 4 Open BKs out of 7 that were open prior to 2020.
The Raising Cane's is always packed to bursting, too, because there's only 1 in the area.
In my experience in white-collar and tech jobs since 2019, nobody I've ever worked with has been expected to be reachable after hours. Same goes for my wife, all tech jobs as well. If someone messages me and I'm online, I'll answer, and it's about 50/50 that they say "Oh you didn't need to respond this late, just work on this tomorrow!"
Unlike all the replies to you, this is why I'm very optimistic about the future of hobby blogs. I do a lot of ChatGPT-ing for several different hobbies, and I've found a lot of really interesting personal blogs from that. Way more than I was reading in the pre-AI era.
I'm very much not seeing the problems other people are assuming, like tons of LLM spam on Reddit being treated as fact by ChatGPT. Instead it really does seem, the more I use these tools, the better they are at surfacing real experiences written about by real people.
I'm right there with you for a lot of stuff. I ask a question and can be very confident that ChatGPT is citing sources, then sometimes I go read the sources. The more critical the information I'm looking for is, the more careful I am about this.
The other day though I was seeing how well it could pull details of its own conversations with me. It often does this pretty well for broad strokes of things - it remembers, largely, what cameras I have and use when I ask photography questions. It's never made things up here, but it does forget details, such as whether I've bought something or am just considering it. However, when I asked it for a specific interaction I thought I remembered, it gladly went along with my false memory and provided an affirmative answer. It was the first time I'd been caught in a serious hallucination with a frontier model (Sol High on the web chat interface) in a long time.
The article seems to be saying that lack of equity is worse than lack of innovation. Obviously we can strive for having both equity and innovation, but it really seems like the points made in the article are arguing that, for example, if there exists a discrepancy in what speeds are available to different people, this is worse than only the lowest speed being available to everyone.
The linked article from 1973 is very strange to read in 2026 and honestly it's hard to take seriously. It seems to actually argue that China and India should stop developing because development encourages dependence on energy. It says that machines are slaves that modern people are required to master?
The speed equity discussed in the linked paper has actually increased significantly as well. More people have cars, and more people can afford plane trips, and bicycle infrastructure is better all over the nation (the world, probably) compared to 1973. I agree with the general principle that cities should encourage diverse development so more people can choose not to use cars if they want, or if they don't have access to a car. In the paper, this would be achieved by somehow state limiting the amount of energy people would be able to consume per capita. I'm glad that world didn't come to pass.
Basically it sounds like the point of view of the article is that at some point the state should tell people they're not allowed to try to make a certain process more efficient in terms of time or resources, because that might drive demand for better productivity, which would be bad because it drives us further from nature and community. Some of the points intersect with beliefs I hold, but I strongly oppose this way of going about it.
The author is a socialist, quoting a socialist from 1973 whose ideas if implemented would've made everyone's lives worse. The idea that a lack of equity is worse than a lack of innovation is a core principle of socialism and it's the core reason why socialism is bad.
There's a great deal of demand for compute. Data centers are a very efficient way of providing that compute in a single place with limited resources. If computers were restricted to being slower and less efficient than they are now, people would build even more, and larger, data centers.
If the provider says "the model will always be right or your money back" then the provider has got responsibility. If there's no guarantee, there's no responsibility on their part, just on the person whose job it is to try and solve a problem with the model.
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