[ISL]

Accountability is the biggest unaddressed challenge for AI implementation.

When one person is able to do too much too quickly, they can create more liability than they can accommodate if something fails.

It is essential that a human is responsible for the utilization of any AI output in the real world, but that is not enough. For our own sakes, we must find ways to minimize the tech-debt bankruptcy blast-radius of those who would utilize (knowingly or unknowingly) AI to create flawed systems upon which others rely.

An example: Jim vibe-codes an extremely popular micropayments app. He hires a few people and sees the company as the WhatsApp of money -- a few engineers and some agentic support staff. It pulls in a few million in VC money -- enough to draw in tens of millions of users. One day, a flaw in the infrastructure causes all of the users' unsalted banking information to be released.

Agentic AI allows that entire list of customers to be exploited rapidly, so the losses for society are in the tens of billions. Jim's company is immediately bankrupt, of course, but there are only a few million dollars to go around.

Today, most of Jim's incentives are to go ahead and build that app. The same is true for his few employees and a small VC contribution. There's not much capital at risk compared with the societal exposure.

How do we ensure that AI users are accountable not just for their actions, but for the size of the risk-exposure that they create?

[Forgeties79]

I have had multiple conversations on HN with people who fight tooth and nail, I mean really ready to die on their hill, because they believe they shouldn’t even have to vet what comes out of an LLM. It’s absolutely baffling to me. The most bizarre excuse is “it codes better than people,” which is not even remotely a given and needs a lot of qualifiers.

I understand there is a push/pull with regards to how much we should let them do, but to not even look at the results before you make them somebody else’s problem? It’s just selfish. There’s no other word for it. You are simply taking the work you were supposed to do it and dumping it on somebody else. These are probably the same people who get upset (rightfully so!) when somebody doesn’t proofread their article/blog before publishing it online.

Everybody wants to use LLM’s to cut corners on their work but nobody wants to be downstream of it. That simply doesn’t work.

[mlsu]

This is the whole point.

“Sorry, the AI said that you are not approved for this cancer treatment, it’s not going to be covered.”

“Sorry, the AI said that you were at the scene when the crime took place.”

“Sorry, the AI has flagged your account for inappropriate content.”

“Sorry, the AI says that you are too risky to lend to.”

…

[AlienRobot]

>In The Unaccountability Machine, Dan Davies argues that organizations form “accountability sinks,” structures that absorb or obscure the consequences of a decision such that no one can be held directly accountable for it. Here’s an example: a higher up at a hospitality company decides to reduce the size of its cleaning staff, because it improves the numbers on a balance sheet somewhere. Later, you are trying to check into a room, but it’s not ready and the clerk can’t tell you when it will be; they can offer a voucher, but what you need is a room. There’s no one to call to complain, no way to communicate back to that distant leader that they’ve scotched your plans. The accountability is swallowed up into a void, lost forever.[0]

This, but web scale.

- https://aworkinglibrary.com/writing/accountability-sinks

[tosti]

Computer says no, but worse.

[bot403]

Need an updated version of the skit. Oohhhh Claude says no....

[bonesss]

Don’t worry, they will provide human review.

[Spoiler: ‘human’ is the name of their LLM agent]

[zaat]

How is that any different from the pre-llm days, when Jim was using stackoverflow to build the largest crypto exchange in the world? Where's stackoverflow accountability?