Comment by laythea | Hacker News Reader

Comment by laythea | Hacker News Reader

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"You should regulate them based on how they perform. You run the experiments to see if the thing’s biased, or if it is likely to kill fewer people than a person. With self-driving cars, I think people kind of accept that now"

I don't. In my opinion, we are all getting carried away with ourselves.

Google or not, I challenge anyone who makes a statement including the phrase "...more like brains", to define that statement accurately. In response, you will likely hear all sorts of things that sound like we know what we are doing and are very clever, but.

If we can't even ask the questions properly, I doubt we will get deliberately valuable answers. Sure, we may luck out, with AI researchers stumbling across random combinations (layered AI) that do produce useful results hap-hazardly, but I would never rely on it.

Eg. I rely on software running in an aircraft, because:

a) it works, by design, not trial and error. b) it is verified. c) we know how it works.

unless you have (c) you cannot achieve (b), with any degree of certainty. Experimenting until confident is not good enough for me for anything important.

Brains fail at times. Computers should not make mistakes.

Even if you knew how a brain works, and even if its possible to replicate it, please don't make computers like this. Software fails enough on its own without any help, even when we supposedly understand it.

With this AI stuff, even if we knew where we are going, we don't know how to get there. And even if we did get there (wherever that is), in the long run, AI is not going to be used for the good.

As always with humanity, we will find ways to use AI to extract value out of other people. This is what drives business.

No thanks, but it is interesting for fluff. A bit too voodoo for me.

> Brains fail at times. Computers should not make mistakes.

I don't think this is a reasonable position to take. We are going to have to accept that if we want computers to do the things brains can do, they will also make mistakes like brains do sometimes. It's not reasonable to insist that the error rate is exactly zero. Besides, if you consider the computer as a complete system including the hardware and human-computer interface, it's clear that no complete system can ever be error-free, even if the CPU executes its instructions faultlessly.

As long as it's as good or better than a human, it's good enough to be useful. Even with "fallible" AI techniques, we should be able to make systems that are much more reliable than humans.

"...if we want computers to do the things brains can do..."

That's my point though. I don't want computers to do what my brain does, mainly because I have no idea what my brain does, nor does anyone. Sure, some people think we do, but we don't.

It also seems silly to try to engineer something that we know may fail (by design), on the probability that it may haphazardly produce better results (even if this is most of the time). That may be useful for things like search results, where the outcome is not critically important.

Please excuse the example, but I would be happier passing away in an aircraft accident knowing it was because although the system was designed not to fail, we did our best in terms of understanding the systems in place. That would be my definition of "sh&t happens".

If I passed away because the aircraft "AI" took an untested path of execution (there are too many to verify, unlike most regular "dumb" software), I would be less happy.

Maybe there is a balance, Eg verifiable software for the important stuff, AI fluffery for the less so. But in that case, we should not get carried away (eg. self driving cars). Remember, planes could fly themselves completely for a long time, and we still have 2 pilots for a reason.

Computers are a human's tool, not replacement.

> I don't want computers to do what my brain does

OK, that's a valid position to take, and I'm sure some people agree, but I and many other people do want computers to do what our brains do. And it is pretty likely to happen.

> I would be happier passing away in an aircraft accident knowing it was [not AI]

If I was in an aircraft accident caused by human pilot error while pilot AIs with 1/100 the error rate of humans were blocked from deployment because they don't meet your "zero errors" requirement, I would not be happy.

"...I and many other people do want computers to do what our brains do" (emphasis, mine).

I hear you, but my point is "what do our brains do?"

In the case of driving, if the answer is "drive a car", then that is a bit like "brexit means brexit" :) The definition of the thing is the outcome of the thing.

Instead, if you try to can decompose the question into a more useful form, one that can drive a specification of software, then progress can be made. However, all that has done, in that case, is a description of the outcome, not the process. (And incomplete, due to the complexity).

It is at this point where my problem with all this AI stuff starts :)

The lack of understanding of the process, rather than the outcome is why I call it voodoo, and anyone talking different is trying to impress, in my opinion.

Generally our brain is composed of a bunch of different subsystems and networks that accomplish varying tasks or objectives, and communicate the results with each other. There's a lot of data sharing going on, as well as reinforcement of known successes thanks to one subsystem known as the reward center.

While we don't understand how our brain works to the bits and bytes, our knowledge and understanding of how our brain functions is Growing. A fuller understanding of how our neurotransmitters work on a chemical/biological level, and an effective way to model it, will likely result in interesting advances in the field of AI

I chat with my neuroscience friend a lot, and the overlap I see between how he describes how the brain works, and general computer science concepts is surprising.

How many passengers died in the USA last year on Part 121 flights due to aircraft accidents caused by human pilot error? When do we expect to develop pilot AIs with 1/100 the error rate of humans? How will those pilot AIs cope with unexpected environment conditions or mechanical failures which aren't programmed in advance?

Obviously this is a hypothetical example and I cannot predict the future. If you want to talk seriously then take self-driving cars, where humans kill over a million people per year and we are very likely to have AIs that would kill less than that, but still a nonzero amount, within 20 years.

In my view it would be unethical to stop the deployment of such AIs on the grounds that we don't "understand" them well enough or can't predict their behavior in every hypothetical circumstance, because we can still test them well enough to know with statistical certainty that they will save many, many lives.

Let's first see a prototype of such an AI for level 4+ autonomous driving on the majority of roads worldwide. Then we can quantify the potential benefits and have a meaningful discussion about the ethics of deployment. Until then it's premature and pointless since we don't know what the actual parameters will be.

Estimates about availability have consistently been overly optimistic. This may be a case where the first 99% of the work takes 99% of the effort, and the last 1% takes the other 99% of the effort.

Absolutely. Want a computer that works like a brain? Obviously we need to know how a brain works first. We've certainly made huge strides compared to what we used to know, but as far as I'm aware we are still staggeringly far from a working model. Maybe we've increased our knowledge 2000% since the turn of the twentieth century or whatever, which sounds great and really is great. But to look at that from the other side--what if we're only 0.02% of the way to an adequate, functioning model of the human brain? We shouldn't be getting a big head just yet.

These are the kind of problems which have profound amounts of complexity lurking in every unexpected pitfall. We are going to discover that it's a lot more of a tangle than we thought before it becomes simple again. I think most of us here know a thing or two about that sinking feeling when you're attacking a problem and discover that what seemed like a minor pothole is actually a wormhole leading into an entire universe full of waist-high bullshit with submerged landmines, but this problem will be in another class entirely. Figuring out the brain is a species-level problem and it's going to be VERY long and arduous.

I also resent the article's assertion that "if an AI is a safer driver than a human, who cares if it's a black box?" Fallacious argument number one around self-driving cars. Hear it all the time, almost always from laymen. It's a nice way to sneak in the assumption that AI will be better than average human drivers any time soon. The way that metric has been measured has been very deceptive so far, and no AI has come close to matching human safety and robustness. Not in real life applications in the field at scale. Not even close. There's been shenanigans like discounting all driver interrupts, which by nature disguises any flaws of the AI and offloads that responsibility on a person as a sort of PR heat-sink.

We don't give ourselves enough credit for how well we handle driving. Reality is chock full of exceptions, quirks, and legacy systems that aren't going to go away for many decades, and compared to the progress we've made on AI so far it's going to be many, many times more work for us in the future to deal with those niggling details. The devil's in there, he really is.

> ...more like brains

He did, he specified the synapses are like weights. I'll extend that a bit and say the collection of ion channels on the neuron's membrane, which regulate the surface potential, will act as the classifier. They form a non-linear classifier (voltage gradiant dissipates with r^2) but still a classifier.

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