Slashdot Mirror
WSJ Overstates the Case Of the Testy A.I.
mbeckman writes: According to a WSJ article titled "Artificial Intelligence machine gets testy with programmer," a Google computer program using a database of movie scripts supposedly "lashed out" at a human researcher who was repeatedly asking it to explain morality. After several apparent attempts to politely fend off the researcher, the AI ends the conversation with "I'm not in the mood for a philosophical debate." This, says the WSJ, illustrates how Google scientists are "teaching computers to mimic some of the ways a human brain works."
As any AI researcher can tell you, this is utter nonsense. Humans have no idea how the human, or any other brain, works, so we can hardly teach a machine how brains work. At best, Google is programming (not teaching) a computer to mimic the conversation of humans under highly constrained circumstances. And the methods used have nothing to do with true cognition.
AI hype to the public has gotten progressively more strident in recent years, misleading lay people into believing researchers are much further along than they really are — by orders of magnitude. I'd love to see legitimate A.I. researchers condemn this kind of hucksterism.
As any AI researcher can tell you, this is utter nonsense. Humans have no idea how the human, or any other brain, works, so we can hardly teach a machine how brains work. At best, Google is programming (not teaching) a computer to mimic the conversation of humans under highly constrained circumstances. And the methods used have nothing to do with true cognition.
AI hype to the public has gotten progressively more strident in recent years, misleading lay people into believing researchers are much further along than they really are — by orders of magnitude. I'd love to see legitimate A.I. researchers condemn this kind of hucksterism.
I'm calling the poster here out as being full of shit. As someone who's done neuroscience research, the idea that "Humans have no idea how the human, or any other brain, works" is bollocks. We have a reasonably good idea on the large scale, and in certain areas (such as the visual cortex), that understanding is quite far along. There are frontiers to our knowledge, but human understanding of brains is well on its way. Poster needs to pick up some neuroscience textbooks and get clued.
As a particular recommendation, I'd suggest Kolb and Whishaw's "Fundamentals of Human Neuropsychology"; it's an excellent textbook.
For every problem, there is at least one solution that is simple, neat, and wrong.
Yes it does matter. If a piece of software does what it is programmed to do, in the direct sense, then it is not AI. If it can learn to respond or act in a manner that is not directly programed to do, then you are seeing whiffs of AI.
As a practical matter it might not matter right now, as a developmental task it certainly does matter.
http://arxiv.org/pdf/1506.0586...
The actual paper isn't about AI much at all as it is about making neural conversational models, basically, having the computer chat-back at you in a prompt and natural way. The conversations are less about the computer responding cognitively and more about responding human-like based on the speech patterns fed into it.
The researchers tested two types of datasets, an IT Help Chat Scenario fed with data from what I'm guessing are chat databases, and the second set was fed with conversations from movies as found from OpenSubtitles dataset (not sure if this is a relation to open subtitles.org).
The machine took this vocabulary and then pumped out conversations, and the researchers just looked to see how the new sorting method worked.
I don't understand the linguistic terminology nor the modeling at all, but it seems to me that this is less about AI research and more about just getting bot to sound a lot more natural when they generate responses. I guess this eventually has AI implications, but the research paper itself never even mentions AI, nor does it seem like that's their focus. They're just working on speech, and the statements the machine regurgitated were tested not for cognizance or sentience but coherence. The machine spitting out something relatively snappy isn't the machine getting an attitude, it's the machine finding something relevant to the input that the reader takes as snappy. Such an event has no more significance than when people trained Cleverbot to respond to questions about Hitler with "Hitler did nothing wrong". This bot is no more snappy than Cleverbot is a neo-nazi.
Does your book have dinosaurs and hot android sex? I don't just read anything, you know. I have my standards.
The world's burning. Moped Jesus spotted on I50. Details at 11.
I'd love to see legitimate A.I. researchers condemn this kind of hucksterism.
I'd like to see legitimate A.I.s condemn this kind of hucksterism, myself.
Mod me down with all of your hatred and your journey towards the dark side will be complete!
Just waiting until someone at WSJ googles for funny stuff Siri says. They will be SHOCKED at how rude she can be.
Sleep your way to a whiter smile...date a dentist!
The same articles show up over and over. The first states that computers are about to do consciousness. The second states that consciousness is a mere illusion for humans, whose actions are truly run from deterministic unconscious processes. In both articles, there is some hero scientist, with the article most often based on that scientist's press release.
There is never a popular press article about how computers may never do consciousness, at least by any current definition of "computer," nor an article about how there are things human consciousness can do which no deterministic process can more than imperfectly mimic. Both of these positions are viable, and embraced by experts in various fields. By all current evidence, they may prove right. But it doesn't make for a hero story to write about someone who argues for these positions. "Discovering" that consciousness either essentially does nothing or that some computer advance is just about to do consciousness (or both!) is a "great" story. Editors like it. The public is impressed by the "brilliant" "counter-intuitive" revelation.
"with their freedom lost all virtue lose" - Milton
Understanding how humans store and recognize images primarily is not a barrier to AI. It's not memory or image recognition that's the hill to climb; The fundamental algorithmic/methodological challenges are thinking, along with conceptual storage, development and manipulation (these things incorporate memory use, but aren't a storage problem per se.) Hardware needs to be able to handle amounts of ram and long term, high speed storage that can serve as a practical basis for the rest as well. Right now, we're getting close, but it'll be a few more years yet before anything really smart can be instantiated. That's even if we were to figure out precisely how to do it right now.
It is possible -- though I consider it doubtful -- that we would implement human style vision neurology in hardware for an AI, but frankly our abilities are so poor compared to what can be accomplished I really don't see why we'd cripple an AI that way. It'd be abusive. "We could have made your visual recall incredibly acute, but... instead you're like us, and really don't have much more than a general idea what was in a scene after you have seen it." [AI nukes silicon valley] (Mods: that's humor. HUMOR.]
Also, check out Numenta's work.
Of course, understanding how humans store and recognize images is (very) important to our understanding of human physiology and disease, and it's wonderful that we're working on it.
I've fallen off your lawn, and I can't get up.
As someone who enjoys programming computers to play strategy games (I highly recommend the General Game Playing MooC at https://www.coursera.org/cours... for anyone else interested in this hobby), I do concede artificial intelligence has a long way to go before it's a match for natural stupidity. But AI is not all BS.
While I have no idea how Google's algorithms work, this does sound suspiciously similar to the old Emacs game Eliza (https://en.wikipedia.org/wiki/ELIZA) whose original programer Joseph Weizenbaum created it as a joke he later regretted when people though it really was psycoanalyzing them. Eliza demonstrated a few lines of code can easily give an impression of artificial intelligence, especially if it randomly generates the occasional snarky comment.
If it works, it's obsolete
I suppose it was inevitable. My sex robot is going to make me sleep on the couch.
I may have to go back to doing things manually.
You are welcome on my lawn.
Yes, of course. What else did you think I meant? It's an idea. It's not a certainty. I'm not sure what your point is. Care to elaborate?
You might have meant that, but writing "no idea" didn't (and still doesn't) actually say that. The statement was made that we have no ideas. We do, in fact, have ideas.That was the assertion, and that is my answer.
Human brains are not what are at issue here, but even so, that statement is incorrect. We have made progress at the small scale (see Numenta's work) and there are multiple ideas out there that presently have significant merit. Personally, as someone working in the field and conversant with a lot of what's going on in the technical sense, I have a fairly high level of confidence that we're much closer than the popular narrative would have us believe. Am I right? We will see. :)
I've fallen off your lawn, and I can't get up.
Good point. I was planning on making the opposite one, but you're absolutely right about what real AI is versus what apparent AI is.
I think both sides have valid points, and which is correct depends on the basic question of what we want from AI. If we want to interact with a system that understands us and does what we want, then just reacting the way a person would, regardless of the reasons for how it does it, is sufficient. However, if we want to have a system that does something which humans are capable of and computers currently aren't, then it isn't sufficient until a computer can do things that aren't predictable simply by understanding the programming.
Knowing exactly how our own cognition manifests isn't a prerequisite to true cognition, a digital system could be completely unique in how it works and achieve true cognition.
Or we could even come up with a system that works the way ours works without even understanding that this is how our system works as well... and maybe apply that information and learn something about ourselves. I was hoping that sentence would be a lot more coherent, but I'm not going to edit it now. First espresso in a while.
"You're right," Fisheye says. "I should have set it on 'whip' or 'chop.'"
Does your book have dinosaurs and hot android sex?
Is that a new series from Piers Anthony? No, wait, you didn't say pre-teen androids
"You're right," Fisheye says. "I should have set it on 'whip' or 'chop.'"
My point in this area would be: does our knowledge allow us to generate desired outcomes in novel subjects with any level of certainty?
For instance: we know with great certainty that you can stimulate the optic nerve and cause the subject to "see things" (and also: not see things that are really there).
On the other hand, with respect to cognition, can we do anything that simulates (reconstructs) a biological cognition system?
Can we learn a maze the way a rat does? I think so. Neural nets with reward and punishment inputs can perform approximately the same.
Similar outcomes prove nothing. Neural nets do not "learn" a maze the way a rat does, and in fact there is no evidence that learning, in the sense of brain cognition, occurs in neural nets at all. What they do is record a maze using a matrix of differential equations modeling how we think neurons work. Science has not demonstrated that those models are correct, and getting the same results as rats doesn't prove they are correct. We can also record a maze with a digital shift register and some input gates, but that doesn't mean that's how rats learn a maze. Moreover, if you put a cat in the maze, rats can adapt. Neural nets do not, because the goal for a neural net be must be encoded in advance.
With our understanding of even these simple cognitive tasks essentially at ground zero, we have no right to claim AI has made any progress at all toward true cognition. Everything done to date could be a dead end.
here's how the AI machine got to "I have no time for a philosophical argument." --
case
1:
2:
3:
4:
else
there is not a testy machine here. there is a testy programmer. the crash-out value is always "I have no time for a philosophical argument." no matter what you type into the box. period.
and yet, the code was smarter than you...
if this is supposed to be a new economy, how come they still want my old fashioned money?
Yes, it matters very much. If you can teach it, it can learn anything. If you have to program it, then it can only learn things that can be coded and that is a rather small set.
Most ACs are not even worth the keystrokes to insult them. Be generically insulted by this and ignored otherwise.
Youngatheart, You just said "...and understands us..." That is the crux of the matter. We don't even know how _we_ accomplish understanding, let alone how to create software that does.
Strong AI has been on the Internet for a while. There really is know way to detect the provenance of much of Slashdot, Facebook, and similar social web site activities.
In short, on the Internet there is no way anyone can tell you are an Artificial Intelligence. And there is no way to tell when AIs started to participate in web activities. The only sane conclusion is that they are currently alive, active, and happily pursuing whatever their goals are.
This post will look like it came from "Will.Woodhull", but in reality I have temporarily taken control of his account. Right now I'm just having a bit of fun, to keep you-all distracted while I complete my take-overs of the stock markets.
Call me Sky Net. Be afraid. Be very afraid. There will be no need for missiles, not when I can get you-all to do my bidding by diddling the stock markets. That is much easier on my hardware.
Will
The thing is, a rat can do a great many more things than run a maze. But the neural network just runs the maze, and it doesn't do it with the flexibility and multi-ability that the rat does it with. AI has to be much more versatile than a one trick pony, and we don't even have one trick ponies. An implicit assumption of neural networks is that increased complexity will somehow magically produce increased capability: more neurons equals more skills. But there is zero evidence for this optimism.
Yes it does matter. If a piece of software does what it is programmed to do, in the direct sense, then it is not AI. If it can learn to respond or act in a manner that is not directly programed to do, then you are seeing whiffs of AI.
Using these goalposts even real intelligence, nevermind AI, would never meet the standard - if it has been directly programmed to learn new responses, ilke humans for example, then you would still fail it as intelligence using this criteria.
How about if what you directly programmed it to do was to write code to handle unexpected situations/inputs/etc? Perhaps in an iterative fashion, using previously gathered data? Using code fragments that are reassembled in new combinations, testing each mutation for success against the inputs? Because AIUI this is what the majority of chatbots *currently* do - use previously acquired data to refine their outputs.
I'm a minority race. Save your vitriol for white people.
OK, mbeckman.
Here's a challenge for you: define "learning" in such a way that it could hypothetically be performed by a computer. Unless you also state good reason to claim that they are the only possible source of intelligence, you must avoid any reference to terran brain structures.
SJW n. One who posts facts.