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For constrained domains the GOFAI approach is a winning strategy.

there is nothing intelligent or even interesting about the brute force approach.

the dominant paradigm in AI research has largely “moved on from GOFAI to embodied, distributed intelligence.” And Faustus from Cincinnati insists that as a result “machines with bodies that experience the world and act on it” will be “able to achieve intelligence.”

The new, embodied paradigm in AI, deriving primarily from the work of roboticist Rodney Brooks, insists that the body is required for intelligence. Indeed, Brooks’s classic 1990 paper, “Elephants Don’t Play Chess,” rejected the very symbolic computation paradigm against which Dreyfus had railed, favoring instead a range of biologically inspired robots that could solve apparently simple, but actually quite complicated, problems like locomotion, grasping, navigation through physical environments and so on. To solve these problems, Brooks discovered that it was actually a disadvantage for the system to represent the status of the environment and respond to it on the basis of pre-programmed rules about what to do, as the traditional GOFAI systems had. Instead, Brooks insisted, “It is better to use the world as its own model.”

although they respond to the physical world rather well, they tend to be oblivious to the global, social moods in which we find ourselves embedded essentially from birth, and in virtue of which things matter to us in the first place.

the embodied AI paradigm is irrelevant to Watson. After all, Watson has no useful bodily interaction with the world at all.

The statistical machine learning strategies that it uses are indeed a big advance over traditional GOFAI techniques. But they still fall far short of what human beings do.

“The illusion is that this computer is doing the same thing that a very good ‘Jeopardy!’ player would do. It’s not. It’s doing something sort of different that looks the same on the surface. And every so often you see the cracks.”

Watson doesn’t understand relevance at all. It only measures statistical frequencies. Because it is relatively common to find mismatches of this sort, Watson learns to weigh them as only mild evidence against the answer. But the human just doesn’t do it that way. The human being sees immediately that the mismatch is irrelevant for the Erie Canal but essential for Toronto. Past frequency is simply no guide to relevance.

The fact is, things are relevant for human beings because at root we are beings for whom things matter. Relevance and mattering are two sides of the same coin. As Haugeland said, “The problem with computers is that they just don’t give a damn.” It is easy to pretend that computers can care about something if we focus on relatively narrow domains — like trivia games or chess — where by definition winning the game is the only thing that could matter, and the computer is programmed to win. But precisely because the criteria for success are so narrowly defined in these cases, they have nothing to do with what human beings are when they are at their best.

Far from being the paradigm of intelligence, therefore, mere matching with no sense of mattering or relevance is barely any kind of intelligence at all. As beings for whom the world already matters, our central human ability is to be able to see what matters when.

But, as we show in our recent book, this is an existential achievement orders of magnitude more amazing and wonderful than any statistical treatment of bare facts could ever be. The greatest danger of Watson’s victory is not that it proves machines could be better versions of us, but that it tempts us to misunderstand ourselves as poorer versions of them.

human beings evolved big brains not to understand the world, but to understand each other.

Not only is a good picture, even a mental one, worth at least a thousand words, but many scientists themselves think in these terms.

Though metaphors are useful in trying to understand complicated scientific ideas, they have their pitfalls.

Consider another famous scientific metaphor, the evolutionary biologist Richard Dawkins's idea of the "selfish gene." This is a brilliant and simple way to explain that natural selection relies on the self-perpetuation of genes that promote higher rates of survival. But for some critics, it suggests an intentionality that is absent in the process of evolution. Others worry that it implies an immoral world where selfishness wins out.

When used effectively, an apt metaphor can enhance the real purpose in writing about science for the public: provoking interest and a desire to learn more.

“We’re at the beginning of a 10-year period where we’re going to transition from computers that can’t understand language to a point where computers can understand quite a bit about language.”

E-discovery technologies generally fall into two broad categories that can be described as “linguistic” and “sociological.”

The most basic linguistic approach uses specific search words to find and sort relevant documents. More advanced programs filter documents through a large web of word and phrase definitions.

The sociological approach adds an inferential layer of analysis, mimicking the deductive powers of a human Sherlock Holmes

Like all animal brains, human brains are not general-purpose universal learning machines, but, instead, are intricately structured suites of instincts optimized for the environments in which they evolved. To harness our brains, we want to let the brain’s brilliant mechanisms run as intended—i.e., not to be twisted. Rather, the strategy is to twist Y into a shape that the brain does know how to process.

there is a very good reason to be optimistic that the next stage of human will come via the form of adaptive harnessing, rather than direct technological enhancement: It has already happened. We have already been transformed via harnessing beyond what we once were. We’re already Human 2.0, not the Human 1.0, or Homo sapiens, that natural selection made us. We Human 2.0’s have, among many powers, three that are central to who we take ourselves to be today: writing, speech, and music (the latter perhaps being the pinnacle of the arts). Yet these three capabilities, despite having all the hallmarks of design, were not a result of natural selection, nor were they the result of genetic engineering or cybernetic enhancement to our brains. Instead, and as I argue in both The Vision Revolution and my forthcoming Harnessed, these are powers we acquired by virtue of harnessing, or neuronal recycling.

Although the step from Human 1.0 to 2.0 was via cultural selection, not via explicit human designers, does the transformation to Human 3.0 need to be entirely due to a process like cultural evolution, or might we have any hope of purposely guiding our transformation? When considering our future, that’s probably the most relevant question we should be asking ourselves.

One of my reasons for optimism is that nature-harnessing technologies (like writing, speech, and music) must mimic fundamental ecological features in nature, and that is a much easier task for scientists to tackle than emulating the exhorbitantly complex mechanisms of the brain

Writing The Social Animal has been an exhilarating journey. “The scientists I’ve spent the last three years talking to are truth seekers, unlike people [in Washington]. They’re not technical materialists. They love Henry and William James. They’ve helped me see how the power of deep ideas changes the way you think. It was part of my idea to go down, down, down, to look at moral and spiritual creativity, the deepest issues. You learn the importance of culture, of history—some of the deep knowledge that comes from Plato and Aristotle. Philosophy and theology are telling us less than they used to. Scientists and researchers are leaping in where these disciplines atrophy—they’re all drilling down into an explanation of what man is.”

“I have the sense it’s a big intellectual moment. You feel the heat. It’s like Silicon Valley in the ’90s.”

he is planning a possible trip to Mauritania and has used Twitter to query his million-man follower group in search of expertise on the country — with good results.

He has used it also for something that blogs and columns just aren’t appropriate for, he said: publishing a hunch.

Twitter also enables writers to super-publish their work. A piece may be destined for NYTimes.com or the newspaper, but that doesn’t stand in the way of tweeting out a link to it.

If the item is really popular, Twitter is effectively pushing a cloud of links far beyond the reach of The Times’s Web site and print edition.

But there is more to it than gathering, understanding and publishing. Twitter, to hear Times staffers talk about it, is an environment. Inside, Mr. Carr said, “you can see what is getting heat and what is not.”

I have made an effort to create a persona out of what I report,” he said. “I am always looking for articles, interesting quotes and things that center around my domain. I think people expect that of me, and that is why they follow me on Twitter.”

Twitter, it seems apparent, enables journalists to report and publish actively in digital space. It allows them to create their own community. But this can become a self-limiting hive or, as Brian Stelter noted, “an echo chamber.”

molecular biologists were soon speaking of information, not to mention codes, libraries, alphabets and transcription, without any sense of metaphor. In Gleick’s words, “Genes themselves are made of bits.” At the same time, physicists exploring what Einstein had called the “spooky” paradoxes of quantum mechanics began to see information as the substance from which everything else in the universe derives. As the physicist John Archibald Wheeler put it in a paper title, “It From Bit.”

Does your house need a new coat of paint? Don’t bother, just enter it into your public database and you have a nice new mint green paint job that everyone will see. Want to redecorate? Do it with computer graphics. You can have a birdbath in the front yard inhabited by Disneyesque animals who frolic and play. Even indoors, don’t buy artwork, just download it from the net and have it appear where you want.

Got a zit? No need to cover up with Clearsil, just erase it from your public face and people will see the improved version. You can dress up your clothes and hairstyle as well.

Of course, anyone can turn off their enhancements and see the plain old reality, but most people don’t bother most of the time because things are ugly that way.

Some of the kids attending Fairmont Junior High do so remotely. They appear as "ghosts", indistinguishable from the other kids except that you can walk through them. They go to classes and raise their hands to ask questions just like everyone else. They see the school and everyone at the school sees them. Instead of visiting friends, the kids can all instantly appear at one another’s locations.

The computer synthesizing visual imagery is able to call on the localizer network for views beyond what the person is seeing. In this way you can have 360 degree vision, or even see through walls. This is a transparent society with a vengeance!

The cumulative effect of all this technology was absolutely amazing and completely believable

One thing that was believable is that it seemed that a lot of the kids cheated, and it was almost impossible for the adults to catch them. With universal network connectivity it would be hard to make sure kids are doing their work on their own. I got the impression the school sort of looked the other way, the idea being that as long as the kids solved their problems, even if they got help via the net, that was itself a useful skill that they would be relying on all their lives.

We survive because we struggle to be the fittest and also because we are really good at cooperation.

“temperament dimensions.” She writes that we have four broad temperament constellations. One, built around the dopamine system, regulates enthusiasm for risk. A second, structured around the serotonin system, regulates sociability. A third, organized around the prenatal testosterone system, regulates attention to detail and aggressiveness. A fourth, organized around the estrogen and oxytocin systems, regulates empathy and verbal fluency.

“subselves.” This is the idea that we are not just one personality, but we have many subselves that get aroused by different cues

the concept of duality, the idea that it is possible to describe the same phenomenon truthfully from two different perspectives. The most famous duality in physics is the wave-particle duality

“Shifting Baseline Syndrome.

emergence

path dependence. This refers to the notion that often “something that seems normal or inevitable today began with a choice that made sense at a particular time in the past, but survived despite the eclipse of the justification for that choice.

Einstellung Effect, the idea that we often try to solve problems by using solutions that worked in the past instead of looking at each situation on its own terms.

the Focusing Illusion, which holds that “nothing in life is as important as you think it is while you are thinking about it.”

Supervenience. Imagine a picture on a computer screen of a dog sitting in a rowboat. It can be described as a picture of a dog, but at a different level it can be described as an arrangement of pixels and colors. The relationship between the two levels is asymmetric. The same image can be displayed at different sizes with different pixels. The high-level properties (dogness) supervene the low-level properties (pixels).

the Fundamental Attribution Error: Don’t try to explain by character traits behavior that is better explained by context.

the distinction between emotion and arousal.

emergence

emergence.

We often try to understand problems by taking apart and studying their constituent parts. But emergent problems can’t be understood this way. Emergent systems are ones in which many different elements interact. The pattern of interaction then produces a new element that is greater than the sum of the parts, which then exercises a top-down influence on the constituent elements.