As a contributor to several ML projects, I am happy the mainstream media and 'thought leaders' haven't found out and picked on early projects like OpenCog or DeepDive. We could've seen a tremendous amount of pseudoscience BS that would've undermined important initiatives.
What you wanted to know about AI
41–50 of 165 posts
Re: What you wanted to know about AI
#42Earlier quoted context omitted.
If people had started to worry about the long-term effects of carbon output before it was already widespread, a lot of the damage it has caused could have been limited. I don't see what's irrational about trying to solve problems before they become problems, rather than trying to do damage control after the fact.
You aren't getting the comparison. It's akin to someone back then worrying about the long-term effects of steam/water vapor. You don't know if vapor is actually a problem, or will become one, and you don't have any data in any field to back up your concerns.
Which would have been perfectly reasonable.
When pharma companies produce a new drug which appears to have a positive effect, they don't know that it will cause problems and don't have any data to back up any concerns.
So do they rush full-steam-ahead into the unknown? Do you unleash the drug to whomever wants it, without regulation? No, of course not; you approach with caution, you hold clinical trials, you collect data as you go and you look for potential problems before the drug is widespread.
Arguably a similarly controlled approach would have helped in the case of carbon output and will help in the case of AI. It's not about fear mongering or preventing progress, it's about discussing ways to approach with caution and solve problems (and minimise the damage they cause), if and when they arise.
Re: What you wanted to know about AI
#43When I started school, my dream was to figure out a theory to underpin a grand unified model of artificial intelligence. Imagine my disappointment once I started studying the subject in detail. Most functional AI nowadays consists of algorithms that are carefully tuned to solve a very specific problem in a narrowly defined environment. All the research nowadays is pushing the boundaries of a local optimum. Right now,…
What concerns me is not Skynet; what concerns me is the exasperating over-confidence that some people have in our current AI capabilities, on Hacker News and elsewhere.
Yes exactly!!
Each AI winter is preceded by unrealistic expectations. If the unrealistic expectations this time are resoundingly fearful, I worry that the next AI winter will be even worse - like create legislation and basically kill the field worse.
Re: What you wanted to know about AI
#44To me, algorithmic trading and investing is already a pretty big scary AI proposition. And it's happening all over, for real profit. Privatization and algorithmification (or whatever) of large scale human decision making seems like an enormous change. And the computers don't have to "think" in order to do this. The next step in this scenario would be policy decision making based on AI techniques. Statistical measurin…
"policy decision making based on ... statistical measuring" is > 2000 years old. The modern version based on a mathematical understanding of statistics & sampling, as opposed to collecting aggregates large enough that you can just treat the error as 0, is ~80 years old.
Yeah, it's quite fascinating. Like the "Cybersyn Project" in Chile. [0]
Project Cybersyn was a Chilean project from 1971–1973 (during the government of President Salvador Allende) aimed at constructing a distributed decision support system to aid in the management of the national economy. The project consisted of four modules: an economic simulator, custom software to check factory performance, an operations room, and a national network of telex machines that were linked to one mainframe computer.
Re: What you wanted to know about AI
#45A lot of respected AI researchers and practitioners are writing these "AIs are really stupid" articles to rebut superintelligence fearmongering in the popular press. That's a valuable service, and everything this article says is correct. Deepmind's Atari network is not going to kick off the singularity. I worry that the flurry of articles like this, rational and well-reasoned all, will be seen as a "win" for the noth…
It doesn't attempt to engage with the arguments of Stuart Russell, Nick Bostrom, Eliezer Yudkowsky, and others who are worried, not about current methods, but about what will happen when the time comes -- in ten, fifty, or a hundred years -- that AI does exceed general human intelligence. That's because it would be arguing a straw-man. So there is no reason to engage the argument.
I'm not sure I understand what you mean by "straw man" here. The usual meaning is that to attack a straw man means to argue against a position that no one actually holds, but which is easier to attack than your opponent's actual position. The concerns about the long-term future of AI are real, actual beliefs held by serious people. At this point there's a respectable literature on the potential dangers of unconstrained, powerful optimizing agents; I linked a couple of examples. These arguments are well thought through and worth engaging.
By contrast, this article and many others are implicitly arguing against an actual straw man position, the position of "let's shut down AI research before it kills us all in six months", which no serious person on either side of this debate really holds (though it's understandable how someone who only read the discussion in the mainstream press could come to think this way).
Re: What you wanted to know about AI
#46Earlier quoted context omitted.
The global warming comparison isn't very good. We had the capabilities for carbon output 50 years ago and it has slowly been increasing. But we don't yet have an AI. So there is no need to warn anyone, except out of irrational fear. Once we actually get it, it would make sense to start warning about its applications, so it doesn't get out of control. If I apply your analogy correctly, then warning about AI now, is th…
If people had started to worry about the long-term effects of carbon output before it was already widespread, a lot of the damage it has caused could have been limited. I don't see what's irrational about trying to solve problems before they become problems, rather than trying to do damage control after the fact.
If people had started to worry about the long-term effects of carbon output before it was already widespread, the Industrial Revolution would have been strangled at birth (the road from wood fires to solar panels leads through coal-burning steam engines; refuse to ever burn coal in large quantities and the chain is broken), and we would have stumbled around banging the rocks together until evolution optimized general intelligence out of existence or the sun autoclaved the biosphere.
Nothing in the world is more dangerous than premature attempts at safety.
Re: What you wanted to know about AI
#47Earlier quoted context omitted.
"policy decision making based on ... statistical measuring" is > 2000 years old. The modern version based on a mathematical understanding of statistics & sampling, as opposed to collecting aggregates large enough that you can just treat the error as 0, is ~80 years old.
Yeah, it's quite fascinating. Like the "Cybersyn Project" in Chile. [0] Project Cybersyn was a Chilean project from 1971–1973 (during the government of President Salvador Allende) aimed at constructing a distributed decision support system to aid in the management of the national economy. The project consisted of four modules: an economic simulator, custom software to check factory performance, an operations room, an…
Cybersyn was kind of a joke; it was a Star Trek set hooked up to telexes where aides manually aggregated information in the same way leaders get their briefings the world over.
Re: What you wanted to know about AI
#48When I started school, my dream was to figure out a theory to underpin a grand unified model of artificial intelligence. Imagine my disappointment once I started studying the subject in detail. Most functional AI nowadays consists of algorithms that are carefully tuned to solve a very specific problem in a narrowly defined environment. All the research nowadays is pushing the boundaries of a local optimum. Right now,…
The key to self-driving cars is to realize that they don't have to be perfect - they just have to be better than us. It's not that the AI driver so good - it's that human drivers are SO BAD! I agree with you that AI is a pipe dream but I do think self-driving cars will succeed. I don't think the computers will ever match our judgement but it's trivially easy for them to beat us on attention span and reaction time, which will make them better drivers.
Re: What you wanted to know about AI
#49There's some good comments about some new AI tools; it's a shame that the article's premise is a straw man. The fears of machine superintelligence are based on the belief that true AI is just around a corner. After all, we’re so advanced and the progress is only accelerating, it’s probably a few years away, at most. Analogously, public figures started warning us about climate change, so it must be just a few years be…
How about this instead: Current AI technologies give us no insight about the probability of an AGI Because that is exactly the point. We can't look at what we have built today and extrapolate that AGI will come from it. All anyone can do is speculate wildly on AGI just as they were able to in 1956 [1]. The difference is that we see automation/computing as ubiquitous (smartphones/computers in 2015), rather than around…
Well, yes, but that's still a straw man. It's not as if Hawking and Gates and so on saw an Atari-bot and on that basis came to worry about AGI. Current AI technologies shouldn't update our estimates much about AGI, unless they push us way off of Kurzweil's (or someone else's) chart.
I do agree that we lack evidence of a broad community of AI experts who have been able to make good predictions, which potentially puts AI research even behind economists! Nonetheless, we'd expect there to be a period between "wild guessing" and "good and reliable models"; Gates and Hawking either think we're in that middle ground, or they think the risks are considerable enough that it's worth pushing towards it now.
Re: What you wanted to know about AI
#50Earlier quoted context omitted.
It doesn't attempt to engage with the arguments of Stuart Russell, Nick Bostrom, Eliezer Yudkowsky, and others who are worried, not about current methods, but about what will happen when the time comes -- in ten, fifty, or a hundred years -- that AI does exceed general human intelligence. That's because it would be arguing a straw-man. So there is no reason to engage the argument.
I'm not sure I understand what you mean by "straw man" here. The usual meaning is that to attack a straw man means to argue against a position that no one actually holds, but which is easier to attack than your opponent's actual position. The concerns about the long-term future of AI are real, actual beliefs held by serious people. At this point there's a respectable literature on the potential dangers of unconstrain…
at this point there's a respectable literature on the potential dangers of unconstrained, powerful optimizing agents, of which I linked a couple of examples.
There isn't really though. Superintelligence, while an interesting book, doesn't do much more than pontificate on sci-fi futures based largely on writing from Yudkowski. Bostrom gives no clear pathway to AGI. Neither does Yudkowski in his own writings or Barrat (Our final invention). By the way Super intelligence is kind of an offshoot book from Global Catastrophic Risks.
All of them take these interesting approaches, WBE, BCI, AGI etc... and just assume they will achieve the goal without looking realistically about where the field is or how it would get there.
So what they do is they say: We are here right now. In some possible fantasy world we could be there. The problem is they can't draw the dots between them.
For example, find me someone who can tell me what kind of hardware we need for an AGI. Can't do it, because no one has any idea. What about interface, what is the interface for an AGI?
Even better (this was my thesis project): What group would have a strong enough requirement that an AGI would be required to build? Industry, Academia, Military? Ok great, can they get funding or resources for it?
etc...
Note, I am not saying that there is no potential that AGI could be a problem. The point here is that nobody has firm footing to say that it will definitely be a huge risk and that we need to regulate it's development.
There are actually people calling for legislation to prevent/slow AGI development - see Altman's blog post and many of the writings on MIRI. So that is what I am rallying against.
We need more development into AGI not less.