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AI Is No Match for the Quirks of Human Intelligence
- danbmil99 5y agoThe pattern I've seen over many decades is to say "computers can't do X", then when computers do X, they move the goalposts and say well, X wasn't really that hard, it didn't require the kind of intelligence humans have. A short list of examples: Chess Driving Go Human level bipedal locomotion Facial recognition The list goes on.
- dx034 5y agoDriving isn't solved though. There are very limited areas where computers can drive. Apart form that, driving is done entirely by humans. Driving would be a task where AI could become hugely important and help to solve labor shortages (see UK right now). But it's not nearly there yet. Apart from that, I don't see anything in that list that would make a big impact on humanity. Solving Chess and Go was impressive, but it doesn't really change people's lives. And facial recognition seems to have more malicious use cases than ethical ones. And bipedal locomotion has improved but is it really solved? Are there robots that can reliably perform the range of motion that humans can? There are some very expensive robots that can jump or run but that's only a small part of what humans can do. From my subjective observations, there's very little automation in the physical world. It's all still done by humans. No matter if it's picking up trash, stocking supermarket shelves, driving buses and trucks or delivering the mail. Many of those (maybe except for driving) are extremely simple tasks for humans, they haven't been reliably solved by machines or are far more expensive than hiring humans.
- willbudd 5y agoHumans haven't solved driving either though.
- leroman 5y agoIf you were to postfix any “AI” criticism with “yet”, it would make the point being made more legitimate.. We don’t know what we don’t know..
- thedudeabides5 5y agoand while we will certain learn more later, we may never learn it all https://en.wikipedia.org/wiki/G%C3%B6del%27s_incompleteness_theorems https://en.wikipedia.org/wiki/G%C3%B6del%27s_incompleteness_...
- potatoman22 5y agoI somewhat understand how applies to math, but is it generalizable to life?
- thedudeabides5 5y agoWhat else is AI than math applied to life. If Godel binds on math in general, it aught bind especially well to math applied to a (constantly evolving) reality.
- supercanuck 5y agoWhy? We can't predict the future.
- ObamaBinSpying 5y agodang, thanks for the shadow ban
- drcode 5y agoIt's odd to take an anecdote about what a person did thousands of years ago (assuming Archimedes actually existed, I suppose we have decent evidence) and use that as the gold standard for how the human mind functions.
- chmsky00 5y agoAssuming there is a gold standard for intelligence, acting as if we can replicate what it took a universe millions of years to stumble into, by etching into silicon some algorithms that have meaning to us specifically, then seeing that as an autonomous experience acquiring organism is odd.
- sdenton4 5y agoChess and Go were beaten, and the AI goalpost had to move /somewhere/...
- CaptArmchair 5y agoFirst, there's plenty established historical evidence that supports Archimedes existence. I'm not sure why you doubt this. Second, the article uses the story of Archimedes Principle as one of several examples to illustrate in an digestible manner what an "Insight problem" is, how it differs from a "Path problem", and how that difference impedes AI from matching human intelligence. At no point did the author presume that Archimedes "Eureka!" moment is a "gold standard" by which to compare the performative functioning of modern day, digital based AI. Third, consider that this blogpost / essay is target a wider audience beyond the field of artificial intelligence. As the impressum in the footer of the site reads: > Illuminating the bold ideas and voices that make up the MIT Press's expansive catalog. We publish thought-provoking excerpts, interviews, and original essays written for a general reader but backed by academic rigor.
- leesec 5y agoThere is nothing special about human intelligence. We will have smarter computers in our life time and I'm willing to place bets.
- antegamisou 5y agoWhy have you decided to triviliaze human brain understanding? Except if you believe you have discovered a way to boost IQ.
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- pjmorris 5y agoHere's a possibly related bet I have with a friend: "If, in ten year's time (from March 2021) self-driven cars outnumber manually-driven cars on the US roadways, I will buy you dinner. (and vice-versa, he buys if they don't.)" I think it's a reasonably harder task than playing chess for assessing whatever it is we mean by 'intelligence' and my bias is that the difficulties remain under-appreciated by the technical optimists among us. But I could be wrong. What sort of bets are you willing to place?
- leesec 5y agoThat sounds like a commercial acceptance bet rather than a technology one but yeah I would take the same bet. But I'd bet by 2031 driving a car will not be the peak of AI.
- pjmorris 5y agoSure, there are technological and commercial (and regulatory, and, and, and...) aspects to the bet. The thing I'm after in my car bet is that I'm using 'replaces humans at something that requires intelligence' as the bar to clear for what you describe as 'smarter computers in our life time.' Can you give a purer example of a bet that would demonstrate what you believe here?
- pjmorris 5y ago
- paul7986 5y agoIf true then robot cars are scarier then I've thought ... AI is going to be able to process the right scenario to avoid a deadly crash within the first decade or more of market adoption or the programmers are going to learn and ship bug fixes for each person their prior code killed? *I'm always downvoted for this thought but is this not the true way forward with robot cars? Those who downvote me think the first batch of market adopted robot cars and their AI is perfect and is not going perform the wrong scenario ... people arent going to be killed by these things?
- esalman 5y agoWell, autonomous cars are able to detect obstacles on an narrow lane. That is nowhere near general intelligence.
- paul7986 5y agoI wonder how they do on the L.A. freeway with average traffic that goes to heavy and average again where there's a police chase happening in a torrential downpour... im sure more scenarios that happen in life at once can be added on ... yet don't worry the AI knows all the millions of scenarios on top each other and will be able to handle it like an attentive human driver would in such situations.
- bdamm 5y agoIt's a legitimate question but the mechanism of how it works is completely wrong. Many people will be killed by any given mass market implementation of self driving cars. Those people will be killed by crashes that a human could not have avoided, people will be killed by errors few humans would make (e.g. "plowing into an overturned truck at full speed") and people will NOT be killed by facets of the system that humans cannot replicate (never tired, never drunk, never angry). Dozens, hundreds, or even thousands of people will die between "bug fixes". The only metric needed here is to determine if the system as a whole performed better or worse than a fleet of typical people. We know what the accident rate is for a fleet of typical people (for now) and it is pretty bad. People also occasionally drive into obvious trucks for no known reason. People are inattentive. People are emotional. People rush. People ignore things they shouldn't or react too late to things they should. The bar to operate more safely than people is high, but not impossibly high. In response to market changes, world changes, and continued investment, code will change but also input training samples will change, labeling technology will change. Those changes will result in a measured change in the fleet's performance. There will be cases where a single death results in some code change. Early on there will be many such cases. But as time goes on, those cases will become less and less frequent, as the cases where specific code points are needed become not only unnecessary but even an impediment to the proper mapping of world features to behavior output.
- avereveard 5y agoAt some point we started calling nonlinear regression AI and now we're spending inane amount of energy explaining that this AI is not really AI. well, no shit.
- hdjjhhvvhga 5y ago"We" in your sentence are not the same groups of people.
- YinglingLight 5y agoThat Archimedes story is great Comms. Outing a crown (King) as a fraud by the displacement of water (Info).
- bingohbangoh 5y agoAt what point does the current AI hype machine crash? It feels like these startups all sell solutions to the top 20 or so companies, competing for a very limited market. It's table stakes for everybody else, an "all-or-nothing" achievement for AI. By contrast, even a small amount of connectivity improved things dramatically for huge swaths of industry. That's how the internet started small and grew up. AI seems to rely on being everything or being nothing. There's no small victories.
- SavantIdiot 5y agoI can't speak to cloud deep learning, but edge NN's have two practical applications: anomaly detection and object defect detection. (Keyword spotting is completely stalled. I've been watching Arm-based companies work on keyword spotting for years and they are still 80% accurate in a real setting, which is like talking to an old person with hearing issues.) Anomaly detection (vibration analysis, audio anomalies) are working fairly well. Same goes for assembly lines where defective parts are booted off, and NN's don't improve that much over traditional methods. The hype machine is all the big sexy stuff. GPT, Protein folding and Alpha Go are truly amazing. But I haven't seen a big step-function in deployable NNets (github-ready) in years. Which given the number of people researching this I expected a linear progression. What have we seen since UNet, MobileNet, SSD, Yolo, BERT, ResNet150, Inception ... ? That's worrisome, but it also could be the pendulum swing while people figure out exactly why these NN's work the way they do. I think we need to wait another 20 years, which means lots of hype money will dry up, but I don't think it will vanish. The efficiency of neural nets as a general function approximation might not be super high accuracy, but it is amazing to see such a simple construct perform with such speed.
- bingohbangoh 5y ago> edge NN's have two practical applications: anomaly detection and object defect detection Do you have any links to companies working on this? I also haven't found any real innovations since adversarial neural networks in ~2016, which roughly fits in with your timeline. Not sure what happened to Geoff Hinton's Capsule networks, that looked like it was going to be a big thing at the time. This is admittedly a very hot take though.
- melenaboija 5y agoI sometimes try to think about the "fast process" mentioned as intuition which I see as a fast likelihood estimation we do based on our previous knowledge. Which also make me think what role plays memory in our intelligence. BTW, I don't have much idea about the subject.
- cratermoon 5y agoThe gold standard for thinking about the limits of AI is the work of Herbert Dreyfus, specifically the books What Computers Can't Do: The Limits of Artificial Intelligence published in 1972, and the revised What Computers Still Can't Do: A Critique of Artificial Reason, published in 1992, and Mind over Machine, from 1986.
- Blammar 5y agoPerhaps you meant the fool's gold standard?
- cratermoon 5y agoIf by that you mean that AI hype is fool's gold, yes.
- yk 5y agoThere's an entire genre of articles which argue that computers can never do X, because X is ill defined. Thing is, half of the time X is only ill defined because the writer neglects to define X well, and for the other half, that the writer can't define X well is no proof that it is impossible to define X well. Here however, if the take the argument of representations in a technical sense, then since a neural network topology is just data we can fit along with the rest of the network, it's just wrong. Or if we take a slightly more charitable interpretation, observing robots, from time to time they can get to really surprising solutions, so at least one would need to distinguish between a numerical algorithm finds a surprising solution and 'insight.' Now, I actually don't want to be too hard on the article, I think it is genuinely interesting hodgepodge of facts about human cognition, I just think it should be rewritten without the computers will never do X thesis.
- glenstein 5y agoCompletely agree. The history of this dates back to philosopher Hubert Dreyfus, who, observing the halting progress of text recognition research at the time, and made open ended declarations that computers can't do X. He said computers couldn't compete at human levels in chess because chess required "insight." This claim did not age well. I find these to be confused, hodgepodgey, not clearly centered on any coherent argument, and often just plain shallow and wrong while masquerading as deep insights. I am glad that, at least, the recent advances in AI are repudiating this genre, or at least forcing articles to add new caveats as to why recent advances don't count.
- betenoire 5y agoI don't disagree necessarily, but humans seems capable of solving problems even when when they are poorly defined by understanding the some implicit context. Sure if we encode all the context, the computer can solve it too, but isn't that fundamentally what the article is trying to convey? That we haven't really taught computers to read between the lines yet?
- LdSGSgvupDV 5y agoIn my experience of developing Custom ChatBOT, X = business model or internal process which contain logic or work flow. For short, X = logic.
- m3kw9 5y agoWe have a way of allowing every variable that we perceive from past to present to affect our thinking(output). AI neural nets are 1 dimensional in comparison
- YeGoblynQueenne 5y ago>> Psychologists have found that people make different choices when presented with the same alternatives, depending on how the alternatives are described. Encapsulated into an old joke: Two monks, both avid smokers, go to the pope for spiritual advice. The first monk goes in, then after a while comes out looking dejected. The other monk asks him: "What happened? What did he say?". "He said no: we are not allowed to smoke during prayer". The other monk smiles and nods knowingly. "Let me try" he says. He goes in. After a while he comes out smiling triumphant. "Wow, he said yes?" asks the other monk, amazed. "What did you say to him?" "I said: Holy Father, are we allowed to pray while we smoke?".
- dane-pgp 5y ago> different choices when presented with the same alternatives I've never been comfortable with the assumption from the social sciences that people don't change their preferences when confronted with seemingly unrelated extra options, the principle known as Independence of Irrelevant Alternatives[0]. Now it seems that there is an even weaker assumption, which perhaps should be called Independence of Relevant Alternatives, which is also not a reasonable axiom to hold. The assumption could be expressed as "A person's preference for X over Y guarantees their preference for X' over Y', whenever X' is an equivalent option to X and Y' is an equivalent option to Y." [0] https://en.wikipedia.org/wiki/Independence_of_irrelevant_alternatives https://en.wikipedia.org/wiki/Independence_of_irrelevant_alt...
- pyinstallwoes 5y agoAnything that has state involved in a known boundary of conditions, AI will always best human's. Human's are really good at generating rules that create dynamics of play. Whenever that set of rules is inscribed in a form of notation, AI will best it. Human's create notation, AI consume it. This can be mutually beneficial. AI depend on human's illogical-logic for breaking novelty thresholds, and human's depend on AI for doing better at logic. AI solve a very important problem of the human condition that has a huge attack vector on reason and logic. If we can somehow find harmony with AI where it doesn't become a risk of manipulating the source of debugging logic & reason then it'll be a very nice match!
- ketanip 5y agoI am really new to this AI game and I hear it from many people that it is the future and some say it is the hype. I think the future is on middle ground, but I'm not sure what that middle ground it can any one tell from their experience and/or expertise what that middle ground is ?