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Scientists Increasingly Can’t Explain How AI Works

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Re: Scientists Increasingly Can’t Explain How AI Works

#181

Post by nanidin »

Spivak wrote: post #77
bombcar wrote: post #59

Earlier quoted context omitted.

Exactly, the Deep Blue's move explanations are boring - they all boil down to "based on the inputs and rules programmed, this line of moves has the best overall outcome to a depth of X" where X is however deep it goes. You can try to translate that to human methods of understanding, but that's not how the computer "thinks", and attempting to do that translation leads to misunderstanding. Kasparov may make moves becau…

I don’t think that’s weird at all, I think humans can intuitively grasp “I simulated 100,000 games starting from the current board state and going at most 50 moves ahead and in games where you did X you reached a strong position most often.” Is that a useful explanation for a human who is training a wetware ML model, not really. But it’s really understandable compared to trying to explain neural nets.

>in games where you did X you reached a strong position most often.

FYI in standard minimax, the search is for the move that leads to the strongest outcome - the "most often" bit doesn't factor into the decision making process.

Re: Scientists Increasingly Can’t Explain How AI Works

#182

Post by mdp2021 »

bobosha wrote: post #96
mdp2021 wrote: post #51

Earlier quoted context omitted.

A very critical core human activity is that of reflection. You should explain the point about «correcting for edge-cases and unknown-unknowns», which may not be clear.

Thanks, but enough neuroscience studies have shown that our decisions are for the most part, on autopilot, qv: Kahneman, Tversky et al. All our "explanations" are post-hoc rationalization i.e. reality is the narrative we tell ourselves. >You should explain the point about «correcting for edge-cases and unknown-unknowns», which may not be clear. Our learning is also for the most part Hebbian, from childhood through ad…

Let us take the «continuous learning system» that is «coached»: very hopefully, it will not be literally «to conform to societal norms»¹, but to understand why it is appropriate or inappropriate to «call [the] aunty» one way or another.

The «continuous learning system» is either heuristic - an investigator - or an "artificial fool", of dubious utility (what is the use of something that "just has an opinion"). That poses an entity that reasons in a foundational context: why this and that.

If Kahneman - which I unfortunately have not yet had the time to read, though I was able to taste a bit of his interview by Lex Fridman - supposed that something "ineffable" oriented Einstein towards determinism and Bohr to more open stances, it is for their scientific work, valid on foundational grounds, that we remember them - not for their leanings.

--

¹Already a bit contradictory, if in school they teach you critical thought, as they did here since primary.

Re: Scientists Increasingly Can’t Explain How AI Works

#183

Post by Zak »

FartyMcFarter wrote: post #7

> The people who develop AI are increasingly having problems explaining how it works and determining why it has the outputs it has. I don't think this is anything new. This was already the case 20+ years ago with chess-playing computers. In the mid-90s, Deep Blue was evaluating 200 million chess positions per second. How do you explain the resulting moves? Obviously we know they were the result of a deep minimax-styl…

Two things are new:

1. Machine learning is increasingly being involved in important decisions.

2. Deep neural networks have become a popular technique, and their results are particularly difficult to explain.

If you're a bank and your AI says somebody is likely to default on the mortgage they're applying for and you can't demonstrate that their race or a proxy therefor wasn't a factor in that calculation, they'll have a settlement and won't need a mortgage.

Re: Scientists Increasingly Can’t Explain How AI Works

#184

Post by NateEag »

belval wrote: post #95
mdp2021 wrote: post #87

Now for a small elephant which entered the room: the article recites that it would be > worth mentioning that the white-box / black-box terminology is in itself part of a long history of racially coded terms in science; researchers have pushed to change "blacklist" to "blocklist," for example Very plainly, the idea of "black-box" comes from the clear, basic and original, notion and experience that "in the dark, you c…

I guess it's the hill I'll die on, but these "white vs black" and "master slave" are inherently racist just make my head turn every time. blacklist came from BEFORE slavery in America. > According to the Henry Holt Encyclopedia of Word and Phrase Origins the word "blacklist" originated with a list England's King Charles II made of fifty-eight judges and court officers who sentenced his father, Charles I, to death in…

I think the concern is not that the word _is_ racist in origin, but that people whose lives have been irrevocably altered by racism and slavery may _perceive_ them as such.

An idea doesn't have to be true to cause someone suffering.

Re: Scientists Increasingly Can’t Explain How AI Works

#185

Post by kelseyfrog »

notahacker wrote: post #168
kelseyfrog wrote: post #141

This is good actually. It means that AI is becoming increasingly more like the human brain - also something we cannot explain how it works. Were we under some sort of pretense that AI would be explainable? What's the ancestry of that idea?

Our aspirations for AI once included the assumption that intelligence involved the ability to explain its own thought processes... Settling for "computer programs with interesting output that don't know how they work but neither do we" seems like a step back. Many things are too complicated for us to parse without remotely approximating intelligence, like next month's weather.

> Our aspirations for AI once included the assumption that intelligence involved the ability to explain its own thought processes

Any idea who this idea traces back to? It would seem they were rather off the mark in their predictions.

Re: Scientists Increasingly Can’t Explain How AI Works

#186

Post by BuildTheRobots »

outworlder wrote: post #170
magic_hamster wrote: post #138

Earlier quoted context omitted.

I must be in the minority but I really dislike voice commands. Every time I try it I feel stupid talking to appliances. But even if I didn't mind talking to lightbulbs and thermostats it would still bother me for several reasons: I don't like being listened to by these corporations, I don't like exposing my electronics to the internet, and I still don't see how any of this stuff is better than flicking a switch.

> I don't like exposing my electronics to the internet, and I still don't see how any of this stuff is better than flicking a switch. That assumes you are close to the switch, that you have switches for all the things you want to do and that you are even free to operate said switches. I do agree if all you are doing is turning a device on and off, it isn't that helpful(it can still be as it allows you to do something…

> I know, because my devices are being monitored. If they start uploading data all the time I'll know about it. And I bet I'm not the only one doing that.

I had previously been pretty happy with this explanation until I got my hands on the new Pixel 7 where the transcription/live subtitles/translation is scarily accurate and completely offline. I'll believe they're not streaming audio out of the house and "listening to me" that way, but it would be easy to exfiltrate a very accurate transcription.

Re: Scientists Increasingly Can’t Explain How AI Works

#187

Post by mdp2021 »

jjk166 wrote: post #139

That's the point. If we had good and intuitive models of how a system works, we could simply write a program to calculate whatever result we were looking for. The purpose of AI is to look at data and find patterns that the human mind struggles to pick up thus allowing us to make accurate predictions without understanding the underlying rules. In the early days of AI when we were basically just practicing, we applied…

> The purpose of AI ... patterns

No. That is just some model of AI. I think I should advise following the publicly available MIT course of late Prof. Patrick Winston.

> as AI has graduated to the level where it can be used for real world applications

I am pretty sure we had applications in the '50s.

> it is successfully ... figuring out relations which are not only difficult to spot but also difficult to turn into an intuitive narrative

And we would like to know them, for many reasons. Because in some cases what we are looking for is the full solution as opposed to the conclusion; because we do not just trust advice blindly; because it is productive in the very engineering effort...

Re: Scientists Increasingly Can’t Explain How AI Works

#189

Post by zmgsabst »

gcanyon wrote: post #169
zmgsabst wrote: post #112

Earlier quoted context omitted.

Isn’t the media doing exactly that? They fixate on white racists while ignoring (eg) the Christmas parade attack — leading to society developing a bias in their beliefs about racism. I always take these criticism of AI as confession-through-projection of the misdeeds people have engaged in already.

I'm gonna need a cite and some statistical analysis to back up your "media is biased" claim. One data point on an event that I easily found reporting on isn't going to cut it.

Will FBI crime statistics do?

> In 2019, race was reported for 6,406 known hate crime offenders. Of these offenders:

> 52.5 percent were White.

> 23.9 percent were Black or African American.

https://ucr.fbi.gov/hate-crime/2019/topic-pages/offenders

White people don’t commit disproportionately many hate crimes — black people do. According to the FBI.

Re: Scientists Increasingly Can’t Explain How AI Works

#190

Post by mrguyorama »

visarga wrote: post #107
kybernetyk wrote: post #83

Who would have guessed that having a highly complex black box means you can't explain what's going on inside that black box... My pet theory is that this is the reason why Siri, Alexa and co. still are shit and haven't moved an inch forward since their inception. I like to play "sleep music" through Alexa when I bring my kid to bed. For his mid day nap it all works perfectly. But in the evening when I say the same ph…

> you can't explain what's going on inside that black box Do you have a better solution for speech recognition? We all know how well speech recognition works in reality, and we know language models can accomplish more complex tasks than setting your music and lights. These models are not state of the art, they are cheap versions for scaling up to millions of users. It's sad but we rarely get to see SOTA in a product.

My mom's $50 LG flip phone from 2000 did voice control better than any of the "assistants" from nowadays. Classical, non-ai methods work really really well if you are allowed to constrain the expected vocab, and with how little these voice assistants are actually capable of doing, constraining the vocab and showing users the actual phrases expected will make the user experience much better.

Stop pretending to be general purpose AI and making an utter fool of it, and produce a product and functionality that actually works for the users.

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