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Comment by mdavidn | Hacker News Reader

It's not that dissimilar to the sophisticated, non-deterministic failures already introduce over time by humans.

It will be interesting to see. People are already involved in business-critical processes, and they have a far-from-100% success rate. You can see this with self-driving cars; 0.00001% of the time, they decide to swerve into oncoming traffic for no reason. But they can't get drunk! So whether or not that's a win is something that only time can tell. (People will be outraged, because no person would ever do what the AI did, but what matters are the numbers in aggregate. One could also argue; why should I have to put up with this when I never drink and drive? It's a good point and involves philosophical discussions about free will and all that.)

I guarantee people will be mad when an AI chatbot denies their insurance or customer service claim. But I have a friend who works in customer service and it feels like half her job is correcting the mistakes other customer service agents made. If the first line support was AI, would it change much, other than not paying people to make a bunch of mistakes?

Again, it's going to be painful while we try it out and get the data. It feels like it's going to be worse, and individual anecdotes will make each fuckup seem even worse than it is. But it seems inevitable that we're going to get the data. The only way to get VC writing software right now seems to be by tying your company to AI. That means a lot of experiments are about to leak out into the world. We'll learn a lot.

> People will be outraged, because no person would ever do what the AI did, but _what matters are the numbers in aggregate._

That is an opinion, not objective fact.

If Grandma June accidentally hits the accelerator, jumps the curb and kills a kindergartener, we can throw her in prison. She is held accountable for her actions.

https://www.upi.com/Top_News/US/2011/01/25/Woman-83-gets-3-y...

If Grandma June is sitting in her "self-driving" car and it spontaneously accelerates, jumps the curb and kills a kindergartener, what can we do? Who is held accountable?

Something something "fix the problem, not the blame", but accountability is part of fixing a problem. Improving numbers in the aggregate is good, but it is not (and should not be) the sole matter in discussion.

https://en.wikipedia.org/wiki/The_Ones_Who_Walk_Away_from_Om...

This is really not the dilemma it is often portrayed as. You can extend this problem to any instance where a man-made inanimate object kills someone, which we have centuries of precedent for. If a bridge collapses and crushes a schoolbus full of children it's not like we throw our hands up in confusion - there is a very developed legal process that will determine the whos and whats of accountability and punishment.

It isn't a new problem, it's something that every court handles on a daily basis. Rebar or autoregression, the core legal elements are the same.

That is a strange example, because usually we don’t put people in prison for accidents unless there is specific type of gross negligence (e.g., drunk driving) or malicious disregard for life and safety.

> Anderson decided to plead guilty to vehicular homicide because she did not want the family of Karla Campos to endure a trial.

Maybe the woman knew that it would be revealed that she was drunk or had been told that she didn’t have the capability any more to drive safely, but she did it anyway. Without knowing all the facts, pleading guilty for an accident seems like a bizarre choice.

We can try to provide decent transportation infrastructure with feasible alternatives to driving so that Grandma June doesn't have to operate a 2 ton death machine to live her life, but maybe that's getting offtopic.

That's the great part about AI, because computers don't make mistakes, you can launder whatever biases you want through an objective and rational computer.

We already have this today when anti-theft alarms go off at stores as you exit with your paid purchase. You're presumed guilty because someone didn't disable the tag since the robot can't be wrong.

This is such an excellent way of concisely expressing a major fallacy I see whenever I talk about AI/modeling/etc. (I.e. “it isn’t racist it’s just numbers” and other nonsensical takes). I’m borrowing this language for the future.

Meanwhile, human judges, juries, parole boards, etc are racist as hell and have no update algorithm...

That's a hopefully fixable organization problem. I think the closest we should let AI get to judicial decisions is suggested ranges. There still needs to be a person a decision traces back to, who's not just passing through what the computer says.

Ha. Human problems never get fixed, just moved around. There's nothing new to help get the racism or of the justice system - a core piece of the problem is that there are only disincentives for mercy and no checks whatsoever on individual biases. We still have a racist system in the US sixty years after the civil rights movement, and I don't see anything changing that anytime soon.

Tech problems sometimes get fixed, and occasionally either eliminate a class of human problems or create new ones. It's the only thing that changes... Rejecting tech wholesale means embracing the status quo.

There should absolutely be a human where the buck stops. But... "fixing an organisation" involves calling people racist. Then screwing their careers. That should carry a heavy emotional burden. It should involve anger and pushback.

"Some weights in an algorithm are wrong" seems a much less fraught problem.

and we have had racism algorithm in legal services.

Look up the term of art "mathwashing".

Cherrypicked raw death counts are a lobbyist measuring scheme, not social science.

For example, if self-driving cars end up being prone to hitting children darting out on to city streets in new and unpredictable ways, then you have created impediments to the growth and development of children that did not previously exist. Would this be balanced by enhanced safety in other situations? Maybe.

These are complex topics like whether and how long schools should have stayed closed during COVID. Balancing the death and disability effects largely falling on adults vs. the educational interests of children.

"what matters are the numbers in aggregate" is the opposite of cherrypicking. One of those numbers would be the level of danger around children.

The unitless number for driving into oncoming traffic wasn't supposed to be a real stat.

No, it is dissimilar.

Humans learn over time.

Humans have social pressures.

Humans have explanatory rather than merely predictive models about what they do.

Deviations by humans from expected standard behavior often produce better rather than worse results.

The list goes on.

The philosophical question is whether "social pressure" and "reward function" are the same thing.

For one person, at one point in time, sure, even though it'd be a quite complex one. But with an AI used by a thousand companies to replace one team member each, they're replacing a thousand of different "reward functions" with just one across all of them. A huge advantage of humanity is that we have different people, from different cultural and social backgrounds, all with social and personal norms and values that vary over time for each and every person, and telling an AI "imitate a pirate" or "answer without any biases" is not going to replace that.

Humans are not expected to be infallible. Computers are.

This expectation causes a lot of other problems, and will cause problems here too.

That's true but humans are, or at least should be, accountable. When the AIs start making/contributing to impactful decision it will be hard to determine who to consider accountable for them (if something bad happens as a result).

> It's not that dissimilar to the sophisticated, non-deterministic failures already introduce over time by humans.

It's not dissimilar at all, just significantly faster and now in the hands of anyone with a laptop.

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