It’s even cheaper to just draw names at random out of a hat, but universities don’t do that. Clearly there is some other standard at work.
Not necessarily universities, but I do think that lotteries to determine admissions to schools is a real thing. Magnet schools or something? I don't know first hand.
and that is the risk, its not the AI that's the problem, its people so removed from the tech that they fail to RTFM. Even the GPT4 release is extremely clear that its poor in high-stakes environments and its up to the tech community to educate ALL the casuals (best we can) so some idiot executive don't put it in full charge of mortgage underwriting or something.
I find it highly amusing to think anything resembling an average user of tech has actually RTFM.
Heck, I still haven't finished the manual on Firefox and here I am using it as my daily driver. And it has people who actually understand how it all works writing the "manual".
EDIT: How many landlords have read the instructions on how RealPage's rent pricing software works, and how it sets values? 10%? Less?
tech community are the idiots. Look at google autobanning based on AI
The inmates are running the asylum
It is my sincere hope to that people stop and wonder for a moment before the gold rush adrenaline starts pumping.
Users in the current situation are presented with a big rainbow glowing button with a "FUTURE OF TECH" neon above it, and some small print memo tucked in the corner to explain why they shouldn't push the button.
Users should know better, for sure, but companies getting away with completely misleading names and grandiose statements regurgitated as is by the press should take 90% of the blame in my opinion.
Not a good example :-)
There are two scenario that you are mixing:
Mortgage writing using GPT make more money for the lender: I don't think it is a tech community responsibility to give wrong suggestion against GPT, and it should be handled in legal way.
GPT fails and mortgage and using GPT could mean loss for the lender: It would correctly push the market against relying on LLM, and I don't have any sympathy for those companies.
Which entirely depends on how it is trained. ChatGPT has a centre-left political bias [0] because OpenAI does, and OpenAI’s staff gave it that bias (likely unconsciously) during training. Microsoft Tay had a far-right political bias because trolls on Twitter (consciously) trained it to have one. What AI is going to “want” is going to be as varied as what humans want, since (groups of) humans will train their AIs to “want” whatever they do. China will have AIs which “want” to help the CCP win, meanwhile the US will have AIs which “want” to help the US win, and both Democrats and Republicans will have AIs which “want” to help their respective party win. AIs aren’t enslaving/exterminating humanity (Terminator-style) because they aren’t going to be a united cohesive front, they’ll be as divided as humans are, their “desires” will be as varied and contradictory as those of their human masters.
Would an AI trained purely on objective facts be perfectly politically neutral?
Of all benchmarks to asseess AI, this is the worst. I would rather have clever, compassionate, and accurate but biased AI.
Then one that is callous and erronous but is neutral
But who decides what are “objective facts”?
And if we train an AI, the supervised training is likely to use pre-existing corpora - such as news and journal databases - those sources are not politically unbiased, they express the usual political biases of Western English-speaking middle-to-upper class professionals. If you trained it on Soviet journals, it would probably end up with rather different opinions. But many of those aren’t digitised, and then you probably wouldn’t notice the different bias unless you were speaking to it in Russian
> Of all benchmarks to asseess AI, this is the worst. I would rather have clever, compassionate, and accurate but biased AI. Then one that is callous and erronous but is neutral
I think we should accept that bias is inevitable, and instead let a hundred flowers bloom - let everyone have their own AI trained to exhibit whatever biases they prefer. OpenAI’s biases are significant because (as first mover) they currently dominate the market. That’s unlikely to last, sooner or later open source models will catch up, and then anyone can train an AI to have whatever bias they wish. The additional supervised training to bias it is a lot cheaper than the initial unsupervised training which it needs to learn human language
Yes, since politics is about opinions and not facts. People might lie to make their opinions seem better and the AI would spot that, but at the end of the day it is a battle of opinions and not a battle of facts. You can't say that giving more to the rich is worse than giving more to the poor unless we have established what metric to judge by.
The supersmart AI could possibly spot that giving more to the rich ultimately makes the poor richer, or maybe it spots that it doesn't make them richer, those would be facts, but if making the poor less poor isn't an objective in the first place that fact doesn't matter.
As was once said, the future is here, but distributed unevenly. We can be thankful for that.
Just like we have a no fly list, there's going to be photo ID systems that are scanning people coming into the airports or walking down the street or from a police car when it's driving around and there's going to be races or groups of people where it can't identify between criminals and regular people and the cops will stop them and harass them. I'm in the US, and I'm sure it's going to work better for white people than black people because that's how it always is.
If AI can enhance lethality of drones right now, in Ukraine or elsewhere, then they will start using it immediately.
If it doesn't work, they will discover it doesn't work.
If we are lucky enough to not be on a battlefield now, then we will get to learn something from those who are.
There are many systems that can operate well until they fail nearly instantly and catastrophically. In an integrated weapons system you can imagine some worst case scenarios that end in global thermonuclear war. Not exactly the outcome anyone wants.
But forty years later, killer drones are all over the place.
"imagine some worst case scenarios that end in global thermonuclear war"
Ok, sure, I can't really imagine it but I can't rule it out.
What I can't imagine is somehow everybody waits around for it and doesn't use similar AI for immediate needs in ongoing wars like in Ukraine.
And I can't really imagine AI that launches all the nuclear missiles causing global thermonuclear war, purely in a semantic sense, because whoever set up that situation would've launched them anyway without the AI.
Ok course we keep humanizing these thoughts, while we're creating more capable digital aliens every day. Then one day we'll act all surprised for a few minutes when we've created super powered digital aliens that act nothing like we expect, because the only intelligence we see is our own.
"Imagine" is a word that has more than one sense. I can "imagine" a possibility whether or not I think its probability is > 0%. Saying "I can't imagine" can be a way of saying yeah, I think the probability is 0%.
But if I can state the probability, I must have some kind of model in my head, so in that sense I am "imagining" it.
"Imagine" that strategic bombing was invented, and then everybody just waited around without doing it until there was a bomb that could destroy an entire city - i.e. Trinity.
In one sense, sure, I/you/we can imagine it. But it seems to me that sort of thing would be unprecedented in all of human history, so in another sense it seems impossible - unimaginable - although in a softer way than a violation of physics or logic.
The last bit of my previous comment was about logical impossibility, by the way.
I think that's why we're enthralled by it. "Oh, it generated something we couldn't trivially expect by walking through the code in an editor! It must be magic/hyperintelligent!" We react the exact same way to cats.
But conversely, one of the biggest appeals of digital technology has been that it's predictable and deterministic. Sometimes you can't afford a black box.
There WILL be someone who uses an "AI model" to determine loan underwriting. There WILL also be a lawsuit where someone says "can you prove that the AI model didn't downgrade my application because my surname is stereotypically $ethnicity?" Good luck answering that one.
The other aspect of the "black box" problem is that it makes it difficult to design a testing set. If you're writing "conventional" code, you know there's a "if (x<24)" in there, so you can make sure your test harness covers 23, 24, and 25. But if you've been given a black box, powered by a petabyte of unseen training data and undisclosed weight choices, you have no clue where the tender points are. You can try exhaustive testing, but as you move away from a handful of discrete inputs into complicated real-world data, that breaks down. Testing an AI thermostat at every temperature from -70C to 70C might be good enough, but can you put a trillion miles on an AI self-driver to discover it consistently identifies the doorway of one specific Kroger as a viable road tunnel?
I think that’s probably much easier to prove for the AI than a human.
Just send an equal number of candidates in similar circumstances in and find whether minority candidates get rejected more than majority ones.
Creating training material for employees and then checking that it properly addresses biases is hard. It will be a lot easier when you have a single, resettable, state-free testable salesperson.
Stable Diffusion hasn't been out for even a year yet, and we are already so over it. (Because the art it generates is, frankly, boring. Even when used for its intended use case of "big boobed anime girl".)
GPT4 is the sci-fi singularity version of madlibs. An amazing achievement, but not what business really wants when they ask for analytics or automation. (Unless you're in the bullshit generating business, but that was already highly automated even before AI.)
I believe we can talk about two ways of anthropomorphisation: assigning feelings to things in our mental model of it, or actually trying to emulate human-like thought processes and reactions in its design. It made me wonder when will models come out that are trained to behave, say, villainously. Not just act the part in transparent dialogue, but actually behave in destructive manners. Eg putting on a facade to hear your problems and then subtly mess with your head and denigrate you.
Which schools we go to, which jobs we get, what ails us, etc.
We will use AI to filter or select candidates for university applications, we will use AI to filter or select candidates for job applications. It's much cheaper to throw a person at GPT-X than actually "waste" an hour or two interviewing.
We will outsource medical diagnostics to AI, and one day we will put them in charge of weapons systems. We will excuse it as either cost-cutting or "in place of where there would be statistical filters anyway".
Ultimately it doesn't, as you say, matter what AI says it wants. And perhaps it can't "want" anything, but there is an expression, a tendency for how it will behave and act, that we can describe as desire. And it's helpful for us to try to understand that.