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- Hacker News
- I fully agree that companies are doing this, not their "agents", and that companies are responsible for the damages they do.
But I don't think the average person with their $20 subscription to whoever is the primary source of revenue. Enterprises fund most of it by buying API keys and making those fancy chatbot buttons on their sites that nobody clicks, as well as some internal business automations if I had to guess.
If it was just average people with $20 subscriptions funding all this (keep in mind, most people using AI services do not pay for it), by now, all these AI companies would have gone bankrupt.
by createful - If you brought down prod and deleted customer data and told them Claude did it, you’d still be the one in trouble. So they do know how to hold people accountable for actions taken by AI.by fwlr
- I would go farther and argue that companies don't make decisions either. They are also not people (legal nonsense notwithstanding). Individual actual humans make decisions and they're the ones who should be held accountable.by foreigner
- This is a category error antithetical to the whole industry.
While I agree with the author in sentiment; if you trace back this argument - it boils down to “AI shouldn’t be a thing”. Knowledge work is application of intelligence to make decisions - decisions about what to put in code, decisions of what to purchase, legal decisions, forecasting decisions etc.
If you say - an AI should never make decisions as it can’t be made accountable - then using AI for knowledge work shouldn’t happen - and this is antithetical to the industry. It is naive to think that anyone can delegate to an AI while fully foreclosing decisions and achieve any kind of productivity gain - as productivity is decision-making.
Which is not to say the author is wrong; they have a coherent position - just argued at the wrong generality level AFAIK.
by Mentlo - Yet decisions are still made by abstract entities such as "companies" and not the individuals working for them. So that blame can be diluted and deflected in a very convenient manner for CEOs. Just find someone to fire, but keep doing the same thing.
Instead of "Anthropic submits false tip to police", I'd prefer "Anthropic employee John Smith deploys an agent that submits false tip to police". Of course, John Smith will be able to then say "I did so as ordered by my superior, Ms Sue", and so on, with a very clearly established chain of liability.
A corporation and an AI are not very different in many aspects, except one of them is very favourably treated by law, almost as a living person.
by edwcross - I love the term "decision laundering", but this is describing a classic poor management trope.
A bad manager takes personal credit when things go well and finds a scapegoat when things go bad. A good manager gives credit when things go well and takes responsibility when things go bad.
It's wrong to scapegoat the agent. You, the human who executed the agent, made the decision to execute it. You gave it credentials, and set up insufficient guardrails. Don't scapegoat the agent for your poor decisions.
Likewise, it's good to have humility when you get great results out of agents. Yes, the agent made the good results happen. It's OK to tell people that your choice of agent is amazing and did an incredible job. In any half-decent work culture, that should rub off on you as well.
by solatic - Computers can make decisions: Almost everyone reading this will have a implemented an if-else statement or equivalent control flow. That is a decision made by a computer on data it receives at runtime. You can argue that it's different, because we fully understand the logic of such a statement, whereas LLMs are closer to a black-box. But at Turing observed, in practice we are frequently surprised by the output of complex algorithms, even those we have authored ourselves. The more difficult the task, the more complex the algorithm we need to achieve it, and the more unexpected behaviour can emerge from it. In that way, LLMs are just the latest, highest point on a rising line of algorithmic capability and complexity.
We can (and should) try to improve AI safety and alignment, but perfect safety is probably impossible without losing the capabilities that make AI unique. Black-and-white positions that insist anyone creating or using an AI is responsible for anything it does wrong under any circumstances are also unrealistic. AI is a general purpose technology, and we have always accepted that it is not practical for suppliers to envisage and constrain every downstream use: Car manufacturers cannot prevent every instance of mechanical failure, nor can they stop cars being used in crime.
by sobiolite - It's not so much that it can't make a decision, but that whoever allowed it to make decisions is ultimately responsible for them.
Decision laundering is a great term. There is ultimately a human who gave the program free rein. You can't say "sorry my car hit you, it's not my fault" especially when the person driving works for the car manufacturer too.
by roncesvalles