CONSCIOUSNESS & RAY KURZWEIL

[work in progress]   CComputers do not have to be conscious to be smarter than humans. The AI gang will win the race to superhuman computers, and perhaps immortality.  

There is a race on to unravel and understand consciousness.  Stuart Hamerofff and Roger Penrose are high profile scientists who are in the forefront of leading edge thinking.  Hameroff points out that the each axon in the brain circuity contains pods of microtubules (maybe 10,000 in each pod) raising the complexity by at least 5 orders of magnitude.  IBM on the other hand is on a mission to map the brain [see link].

the AI [link] folks are continuing to be under attack.  After all, AI is just that:  Articificial Intelligence.  And most certainly not robust enough to even mimic consciousness. BUT WAIT:   Listen to Ray Kurzweil.  Kurzweil has made predictions.  Kurzweill is a prophet.  Kurzweil is also an inventor.  See article 3 below on his unbelievable inventions  (more to come)

(1) 2045: The Year Man Becomes Immortal By Lev Grossman Time Magazne

On Feb. 15, 1965, a diffident but self-possessed high school student named Raymond Kurzweil appeared as a guest on a game show called I've Got a Secret. He was introduced by the host, Steve Allen, then he played a short musical composition on a piano. The idea was that Kurzweil was hiding an unusual fact and the panelists — they included a comedian and a former Miss America — had to guess what it was.

On the show (see the clip on YouTube), the beauty queen did a good job of grilling Kurzweil, but the comedian got the win: the music was composed by a computer. Kurzweil got $200. (See TIME's photo-essay "Cyberdyne's Real Robot.")

Kurzweil then demonstrated the computer, which he built himself — a desk-size affair with loudly clacking relays, hooked up to a typewriter. The panelists were pretty blasé about it; they were more impressed by Kurzweil's age than by anything he'd actually done. They were ready to move on to Mrs. Chester Loney of Rough and Ready, Calif., whose secret was that she'd been President Lyndon Johnson's first-grade teacher.

But Kurzweil would spend much of the rest of his career working out what his demonstration meant. Creating a work of art is one of those activities we reserve for humans and humans only. It's an act of self-expression; you're not supposed to be able to do it if you don't have a self. To see creativity, the exclusive domain of humans, usurped by a computer built by a 17-year-old is to watch a line blur that cannot be unblurred, the line between organic intelligence and artificial intelligence.

That was Kurzweil's real secret, and back in 1965 nobody guessed it. Maybe not even him, not yet. But now, 46 years later, Kurzweil believes that we're approaching a moment when computers will become intelligent, and not just intelligent but more intelligent than humans. When that happens, humanity — our bodies, our minds, our civilization — will be completely and irreversibly transformed. He believes that this moment is not only inevitable but imminent. According to his calculations, the end of human civilization as we know it is about 35 years away. (See the best inventions of 2010.)

Computers are getting faster. Everybody knows that. Also, computers are getting faster faster — that is, the rate at which they're getting faster is increasing.

True? True.

So if computers are getting so much faster, so incredibly fast, there might conceivably come a moment when they are capable of something comparable to human intelligence. Artificial intelligence. All that horsepower could be put in the service of emulating whatever it is our brains are doing when they create consciousness — not just doing arithmetic very quickly or composing piano music but also driving cars, writing books, making ethical decisions, appreciating fancy paintings, making witty observations at cocktail parties.

If you can swallow that idea, and Kurzweil and a lot of other very smart people can, then all bets are off. From that point on, there's no reason to think computers would stop getting more powerful. They would keep on developing until they were far more intelligent than we are. Their rate of development would also continue to increase, because they would take over their own development from their slower-thinking human creators. Imagine a computer scientist that was itself a super-intelligent computer. It would work incredibly quickly. It could draw on huge amounts of data effortlessly. It wouldn't even take breaks to play Farmville.

Probably. It's impossible to predict the behavior of these smarter-than-human intelligences with which (with whom?) we might one day share the planet, because if you could, you'd be as smart as they would be. But there are a lot of theories about it. Maybe we'll merge with them to become super-intelligent cyborgs, using computers to extend our intellectual abilities the same way that cars and planes extend our physical abilities. Maybe the artificial intelligences will help us treat the effects of old age and prolong our life spans indefinitely. Maybe we'll scan our consciousnesses into computers and live inside them as software, forever, virtually. Maybe the computers will turn on humanity and annihilate us. The one thing all these theories have in common is the transformation of our species into something that is no longer recognizable as such to humanity circa 2011. This transformation has a name: the Singularity. (Comment on this story.)

The difficult thing to keep sight of when you're talking about the Singularity is that even though it sounds like science fiction, it isn't, no more than a weather forecast is science fiction. It's not a fringe idea; it's a serious hypothesis about the future of life on Earth. There's an intellectual gag reflex that kicks in anytime you try to swallow an idea that involves super-intelligent immortal cyborgs, but suppress it if you can, because while the Singularity appears to be, on the face of it, preposterous, it's an idea that rewards sober, careful evaluation.

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People are spending a lot of money trying to understand it. The three-year-old Singularity University, which offers inter-disciplinary courses of study for graduate students and executives, is hosted by NASA. Google was a founding sponsor; its CEO and co-founder Larry Page spoke there last year. People are attracted to the Singularity for the shock value, like an intellectual freak show, but they stay because there's more to it than they expected. And of course, in the event that it turns out to be real, it will be the most important thing to happen to human beings since the invention of language. (See "Is Technology Making Us Lonelier?")

The Singularity isn't a wholly new idea, just newish. In 1965 the British mathematician I.J. Good described something he called an "intelligence explosion":

Let an ultraintelligent machine be defined as a machine that can far surpass all the intellectual activities of any man however clever. Since the design of machines is one of these intellectual activities, an ultraintelligent machine could design even better machines; there would then unquestionably be an "intelligence explosion," and the intelligence of man would be left far behind. Thus the first ultraintelligent machine is the last invention that man need ever make.

The word singularity is borrowed from astrophysics: it refers to a point in space-time — for example, inside a black hole — at which the rules of ordinary physics do not apply. In the 1980s the science-fiction novelist Vernor Vinge attached it to Good's intelligence-explosion scenario. At a NASA symposium in 1993, Vinge announced that "within 30 years, we will have the technological means to create super-human intelligence. Shortly after, the human era will be ended."

By that time Kurzweil was thinking about the Singularity too. He'd been busy since his appearance on I've Got a Secret. He'd made several fortunes as an engineer and inventor; he founded and then sold his first software company while he was still at MIT. He went on to build the first print-to-speech reading machine for the blind — Stevie Wonder was customer No. 1 — and made innovations in a range of technical fields, including music synthesizers and speech recognition. He holds 39 patents and 19 honorary doctorates. In 1999 President Bill Clinton awarded him the National Medal of Technology. (See pictures of adorable robots.)

But Kurzweil was also pursuing a parallel career as a futurist: he has been publishing his thoughts about the future of human and machine-kind for 20 years, most recently in The Singularity Is Near, which was a best seller when it came out in 2005. A documentary by the same name, starring Kurzweil, Tony Robbins and Alan Dershowitz, among others, was released in January. (Kurzweil is actually the subject of two current documentaries. The other one, less authorized but more informative, is called The Transcendent Man.) Bill Gates has called him "the best person I know at predicting the future of artificial intelligence."(See the world's most influential people in the 2010 TIME 100.)

In real life, the transcendent man is an unimposing figure who could pass for Woody Allen's even nerdier younger brother. Kurzweil grew up in Queens, N.Y., and you can still hear a trace of it in his voice. Now 62, he speaks with the soft, almost hypnotic calm of someone who gives 60 public lectures a year. As the Singularity's most visible champion, he has heard all the questions and faced down the incredulity many, many times before. He's good-natured about it. His manner is almost apologetic: I wish I could bring you less exciting news of the future, but I've looked at the numbers, and this is what they say, so what else can I tell you?

Kurzweil's interest in humanity's cyborganic destiny began about 1980 largely as a practical matter. He needed ways to measure and track the pace of technological progress. Even great inventions can fail if they arrive before their time, and he wanted to make sure that when he released his, the timing was right. "Even at that time, technology was moving quickly enough that the world was going to be different by the time you finished a project," he says. "So it's like skeet shooting — you can't shoot at the target." He knew about Moore's law, of course, which states that the number of transistors you can put on a microchip doubles about every two years. It's a surprisingly reliable rule of thumb. Kurzweil tried plotting a slightly different curve: the change over time in the amount of computing power, measured in MIPS (millions of instructions per second), that you can buy for $1,000.

As it turned out, Kurzweil's numbers looked a lot like Moore's. They doubled every couple of years. Drawn as graphs, they both made exponential curves, with their value increasing by multiples of two instead of by regular increments in a straight line. The curves held eerily steady, even when Kurzweil extended his backward through the decades of pretransistor computing technologies like relays and vacuum tubes, all the way back to 1900. (Comment on this story.)

Kurzweil then ran the numbers on a whole bunch of other key technological indexes — the falling cost of manufacturing transistors, the rising clock speed of microprocessors, the plummeting price of dynamic RAM. He looked even further afield at trends in biotech and beyond — the falling cost of sequencing DNA and of wireless data service and the rising numbers of Internet hosts and nanotechnology patents. He kept finding the same thing: exponentially accelerating progress. "It's really amazing how smooth these trajectories are," he says. "Through thick and thin, war and peace, boom times and recessions." Kurzweil calls it the law of accelerating returns: technological progress happens exponentially, not linearly.

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Then he extended the curves into the future, and the growth they predicted was so phenomenal, it created cognitive resistance in his mind. Exponential curves start slowly, then rocket skyward toward infinity. According to Kurzweil, we're not evolved to think in terms of exponential growth. "It's not intuitive. Our built-in predictors are linear. When we're trying to avoid an animal, we pick the linear prediction of where it's going to be in 20 seconds and what to do about it. That is actually hardwired in our brains."

Here's what the exponential curves told him. We will successfully reverse-engineer the human brain by the mid-2020s. By the end of that decade, computers will be capable of human-level intelligence. Kurzweil puts the date of the Singularity — never say he's not conservative — at 2045. In that year, he estimates, given the vast increases in computing power and the vast reductions in the cost of same, the quantity of artificial intelligence created will be about a billion times the sum of all the human intelligence that exists today. (See how robotics are changing the future of medicine.)

The Singularity isn't just an idea. it attracts people, and those people feel a bond with one another. Together they form a movement, a subculture; Kurzweil calls it a community. Once you decide to take the Singularity seriously, you will find that you have become part of a small but intense and globally distributed hive of like-minded thinkers known as Singularitarians.

Not all of them are Kurzweilians, not by a long chalk. There's room inside Singularitarianism for considerable diversity of opinion about what the Singularity means and when and how it will or won't happen. But Singularitarians share a worldview. They think in terms of deep time, they believe in the power of technology to shape history, they have little interest in the conventional wisdom about anything, and they cannot believe you're walking around living your life and watching TV as if the artificial-intelligence revolution were not about to erupt and change absolutely everything. They have no fear of sounding ridiculous; your ordinary citizen's distaste for apparently absurd ideas is just an example of irrational bias, and Singularitarians have no truck with irrationality. When you enter their mind-space you pass through an extreme gradient in worldview, a hard ontological shear that separates Singularitarians from the common run of humanity. Expect turbulence.

In addition to the Singularity University, which Kurzweil co-founded, there's also a Singularity Institute for Artificial Intelligence, based in San Francisco. It counts among its advisers Peter Thiel, a former CEO of PayPal and an early investor in Facebook. The institute holds an annual conference called the Singularity Summit. (Kurzweil co-founded that too.) Because of the highly interdisciplinary nature of Singularity theory, it attracts a diverse crowd. Artificial intelligence is the main event, but the sessions also cover the galloping progress of, among other fields, genetics and nanotechnology. (See TIME's computer covers.)

At the 2010 summit, which took place in August in San Francisco, there were not just computer scientists but also psychologists, neuroscientists, nanotechnologists, molecular biologists, a specialist in wearable computers, a professor of emergency medicine, an expert on cognition in gray parrots and the professional magician and debunker James "the Amazing" Randi. The atmosphere was a curious blend of Davos and UFO convention. Proponents of seasteading — the practice, so far mostly theoretical, of establishing politically autonomous floating communities in international waters — handed out pamphlets. An android chatted with visitors in one corner.

After artificial intelligence, the most talked-about topic at the 2010 summit was life extension. Biological boundaries that most people think of as permanent and inevitable Singularitarians see as merely intractable but solvable problems. Death is one of them. Old age is an illness like any other, and what do you do with illnesses? You cure them. Like a lot of Singularitarian ideas, it sounds funny at first, but the closer you get to it, the less funny it seems. It's not just wishful thinking; there's actual science going on here.

For example, it's well known that one cause of the physical degeneration associated with aging involves telomeres, which are segments of DNA found at the ends of chromosomes. Every time a cell divides, its telomeres get shorter, and once a cell runs out of telomeres, it can't reproduce anymore and dies. But there's an enzyme called telomerase that reverses this process; it's one of the reasons cancer cells live so long. So why not treat regular non-cancerous cells with telomerase? In November, researchers at Harvard Medical School announced in Nature that they had done just that. They administered telomerase to a group of mice suffering from age-related degeneration. The damage went away. The mice didn't just get better; they got younger. (Comment on this story.)

Aubrey de Grey is one of the world's best-known life-extension researchers and a Singularity Summit veteran. A British biologist with a doctorate from Cambridge and a famously formidable beard, de Grey runs a foundation called SENS, or Strategies for Engineered Negligible Senescence. He views aging as a process of accumulating damage, which he has divided into seven categories, each of which he hopes to one day address using regenerative medicine. "People have begun to realize that the view of aging being something immutable — rather like the heat death of the universe — is simply ridiculous," he says. "It's just childish. The human body is a machine that has a bunch of functions, and it accumulates various types of damage as a side effect of the normal function of the machine. Therefore in principal that damage can be repaired periodically. This is why we have vintage cars. It's really just a matter of paying attention. The whole of medicine consists of messing about with what looks pretty inevitable until you figure out how to make it not inevitable."

Kurzweil takes life extension seriously too. His father, with whom he was very close, died of heart disease at 58. Kurzweil inherited his father's genetic predisposition; he also developed Type 2 diabetes when he was 35. Working with Terry Grossman, a doctor who specializes in longevity medicine, Kurzweil has published two books on his own approach to life extension, which involves taking up to 200 pills and supplements a day. He says his diabetes is essentially cured, and although he's 62 years old from a chronological perspective, he estimates that his biological age is about 20 years younger.

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But his goal differs slightly from de Grey's. For Kurzweil, it's not so much about staying healthy as long as possible; it's about staying alive until the Singularity. It's an attempted handoff. Once hyper-intelligent artificial intelligences arise, armed with advanced nanotechnology, they'll really be able to wrestle with the vastly complex, systemic problems associated with aging in humans. Alternatively, by then we'll be able to transfer our minds to sturdier vessels such as computers and robots. He and many other Singularitarians take seriously the proposition that many people who are alive today will wind up being functionally immortal.

It's an idea that's radical and ancient at the same time. In "Sailing to Byzantium," W.B. Yeats describes mankind's fleshly predicament as a soul fastened to a dying animal. Why not unfasten it and fasten it to an immortal robot instead? But Kurzweil finds that life extension produces even more resistance in his audiences than his exponential growth curves. "There are people who can accept computers being more intelligent than people," he says. "But the idea of significant changes to human longevity — that seems to be particularly controversial. People invested a lot of personal effort into certain philosophies dealing with the issue of life and death. I mean, that's the major reason we have religion." (See the top 10 medical breakthroughs of 2010.)

Of course, a lot of people think the Singularity is nonsense — a fantasy, wishful thinking, a Silicon Valley version of the Evangelical story of the Rapture, spun by a man who earns his living making outrageous claims and backing them up with pseudoscience. Most of the serious critics focus on the question of whether a computer can truly become intelligent.

The entire field of artificial intelligence, or AI, is devoted to this question. But AI doesn't currently produce the kind of intelligence we associate with humans or even with talking computers in movies — HAL or C3PO or Data. Actual AIs tend to be able to master only one highly specific domain, like interpreting search queries or playing chess. They operate within an extremely specific frame of reference. They don't make conversation at parties. They're intelligent, but only if you define intelligence in a vanishingly narrow way. The kind of intelligence Kurzweil is talking about, which is called strong AI or artificial general intelligence, doesn't exist yet.

Why not? Obviously we're still waiting on all that exponentially growing computing power to get here. But it's also possible that there are things going on in our brains that can't be duplicated electronically no matter how many MIPS you throw at them. The neurochemical architecture that generates the ephemeral chaos we know as human consciousness may just be too complex and analog to replicate in digital silicon. The biologist Dennis Bray was one of the few voices of dissent at last summer's Singularity Summit. "Although biological components act in ways that are comparable to those in electronic circuits," he argued, in a talk titled "What Cells Can Do That Robots Can't," "they are set apart by the huge number of different states they can adopt. Multiple biochemical processes create chemical modifications of protein molecules, further diversified by association with distinct structures at defined locations of a cell. The resulting combinatorial explosion of states endows living systems with an almost infinite capacity to store information regarding past and present conditions and a unique capacity to prepare for future events." That makes the ones and zeros that computers trade in look pretty crude. (See how to live 100 years.)

Underlying the practical challenges are a host of philosophical ones. Suppose we did create a computer that talked and acted in a way that was indistinguishable from a human being — in other words, a computer that could pass the Turing test. (Very loosely speaking, such a computer would be able to pass as human in a blind test.) Would that mean that the computer was sentient, the way a human being is? Or would it just be an extremely sophisticated but essentially mechanical automaton without the mysterious spark of consciousness — a machine with no ghost in it? And how would we know?

Even if you grant that the Singularity is plausible, you're still staring at a thicket of unanswerable questions. If I can scan my consciousness into a computer, am I still me? What are the geopolitics and the socioeconomics of the Singularity? Who decides who gets to be immortal? Who draws the line between sentient and nonsentient? And as we approach immortality, omniscience and omnipotence, will our lives still have meaning? By beating death, will we have lost our essential humanity?

Kurzweil admits that there's a fundamental level of risk associated with the Singularity that's impossible to refine away, simply because we don't know what a highly advanced artificial intelligence, finding itself a newly created inhabitant of the planet Earth, would choose to do. It might not feel like competing with us for resources. One of the goals of the Singularity Institute is to make sure not just that artificial intelligence develops but also that the AI is friendly. You don't have to be a super-intelligent cyborg to understand that introducing a superior life-form into your own biosphere is a basic Darwinian error. (Comment on this story.)

If the Singularity is coming, these questions are going to get answers whether we like it or not, and Kurzweil thinks that trying to put off the Singularity by banning technologies is not only impossible but also unethical and probably dangerous. "It would require a totalitarian system to implement such a ban," he says. "It wouldn't work. It would just drive these technologies underground, where the responsible scientists who we're counting on to create the defenses would not have easy access to the tools."

Kurzweil is an almost inhumanly patient and thorough debater. He relishes it. He's tireless in hunting down his critics so that he can respond to them, point by point, carefully and in detail.

See TIME's photo-essay "A Global Look at Longevity."

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Take the question of whether computers can replicate the biochemical complexity of an organic brain. Kurzweil yields no ground there whatsoever. He does not see any fundamental difference between flesh and silicon that would prevent the latter from thinking. He defies biologists to come up with a neurological mechanism that could not be modeled or at least matched in power and flexibility by software running on a computer. He refuses to fall on his knees before the mystery of the human brain. "Generally speaking," he says, "the core of a disagreement I'll have with a critic is, they'll say, Oh, Kurzweil is underestimating the complexity of reverse-engineering of the human brain or the complexity of biology. But I don't believe I'm underestimating the challenge. I think they're underestimating the power of exponential growth."

This position doesn't make Kurzweil an outlier, at least among Singularitarians. Plenty of people make more-extreme predictions. Since 2005 the neuroscientist Henry Markram has been running an ambitious initiative at the Brain Mind Institute of the Ecole Polytechnique in Lausanne, Switzerland. It's called the Blue Brain project, and it's an attempt to create a neuron-by-neuron simulation of a mammalian brain, using IBM's Blue Gene super-computer. So far, Markram's team has managed to simulate one neocortical column from a rat's brain, which contains about 10,000 neurons. Markram has said that he hopes to have a complete virtual human brain up and running in 10 years. (Even Kurzweil sniffs at this. If it worked, he points out, you'd then have to educate the brain, and who knows how long that would take?) (See portraits of centenarians.)

By definition, the future beyond the Singularity is not knowable by our linear, chemical, animal brains, but Kurzweil is teeming with theories about it. He positively flogs himself to think bigger and bigger; you can see him kicking against the confines of his aging organic hardware. "When people look at the implications of ongoing exponential growth, it gets harder and harder to accept," he says. "So you get people who really accept, yes, things are progressing exponentially, but they fall off the horse at some point because the implications are too fantastic. I've tried to push myself to really look."

In Kurzweil's future, biotechnology and nanotechnology give us the power to manipulate our bodies and the world around us at will, at the molecular level. Progress hyperaccelerates, and every hour brings a century's worth of scientific breakthroughs. We ditch Darwin and take charge of our own evolution. The human genome becomes just so much code to be bug-tested and optimized and, if necessary, rewritten. Indefinite life extension becomes a reality; people die only if they choose to. Death loses its sting once and for all. Kurzweil hopes to bring his dead father back to life.

We can scan our consciousnesses into computers and enter a virtual existence or swap our bodies for immortal robots and light out for the edges of space as intergalactic godlings. Within a matter of centuries, human intelligence will have re-engineered and saturated all the matter in the universe. This is, Kurzweil believes, our destiny as a species. (See the costs of living a long life.)

Or it isn't. When the big questions get answered, a lot of the action will happen where no one can see it, deep inside the black silicon brains of the computers, which will either bloom bit by bit into conscious minds or just continue in ever more brilliant and powerful iterations of nonsentience.

But as for the minor questions, they're already being decided all around us and in plain sight. The more you read about the Singularity, the more you start to see it peeking out at you, coyly, from unexpected directions. Five years ago we didn't have 600 million humans carrying out their social lives over a single electronic network. Now we have Facebook. Five years ago you didn't see people double-checking what they were saying and where they were going, even as they were saying it and going there, using handheld network-enabled digital prosthetics. Now we have iPhones. Is it an unimaginable step to take the iPhones out of our hands and put them into our skulls?

Already 30,000 patients with Parkinson's disease have neural implants. Google is experimenting with computers that can drive cars. There are more than 2,000 robots fighting in Afghanistan alongside the human troops. This month a game show will once again figure in the history of artificial intelligence, but this time the computer will be the guest: an IBM super-computer nicknamed Watson will compete on Jeopardy! Watson runs on 90 servers and takes up an entire room, and in a practice match in January it finished ahead of two former champions, Ken Jennings and Brad Rutter. It got every question it answered right, but much more important, it didn't need help understanding the questions (or, strictly speaking, the answers), which were phrased in plain English. Watson isn't strong AI, but if strong AI happens, it will arrive gradually, bit by bit, and this will have been one of the bits. (Comment on this story.)

A hundred years from now, Kurzweil and de Grey and the others could be the 22nd century's answer to the Founding Fathers — except unlike the Founding Fathers, they'll still be alive to get credit — or their ideas could look as hilariously retro and dated as Disney's Tomorrowland. Nothing gets old as fast as the future.

But even if they're dead wrong about the future, they're right about the present. They're taking the long view and looking at the big picture. You may reject every specific article of the Singularitarian charter, but you should admire Kurzweil for taking the future seriously. Singularitarianism is grounded in the idea that change is real and that humanity is in charge of its own fate and that history might not be as simple as one damn thing after another. Kurzweil likes to point out that your average cell phone is about a millionth the size of, a millionth the price of and a thousand times more powerful than the computer he had at MIT 40 years ago. Flip that forward 40 years and what does the world look like? If you really want to figure that out, you have to think very, very far outside the box. Or maybe you have to think further inside it than anyone ever has before.**********************

 Mind vs. Machine

in the race to build computers that can think like humans, the proving ground is the Turing Test—an annual battle between the world’s most advanced artificial-intelligence programs and ordinary people. The objective? To find out whether a computer can act “more human” than a person. In his own quest to beat the machines, the author discovers that the march of technology isn’t just changing how we live, it’s raising new questions about what it means to be human.
By Brian Christian

Image credit: Bryan Christie

Brighton, England, September 2009. I wake up in a hotel room 5,000 miles from my home in Seattle. After breakfast, I step out into the salty air and walk the coastline of the country that invented my language, though I find I can’t understand a good portion of the signs I pass on my way—LET AGREED, one says, prominently, in large print, and it means nothing to me.

I pause, and stare dumbly at the sea for a moment, parsing and reparsing the sign. Normally these kinds of linguistic curiosities and cultural gaps intrigue me; today, though, they are mostly a cause for concern. In two hours, I will sit down at a computer and have a series of five-minute instant-message chats with several strangers. At the other end of these chats will be a psychologist, a linguist, a computer scientist, and the host of a popular British technology show. Together they form a judging panel, evaluating my ability to do one of the strangest things I’ve ever been asked to do.

I must convince them that I’m human.

Fortunately, I am human; unfortunately, it’s not clear how much that will help.

Also see:
From Luddites to Predators, Men vs. Machines Through Time
Humanity's fears and dilemmas resulting from technology since the Industrial Revolution.

Technology and Humanity in The Atlantic
Writings on the interface between technology and humanity by Mark Twain, Oliver Wendell Holmes, Nobel Laureate James D. Watson, James Fallows, and others.

The Turing Test

Each year for the past two decades, the artificial-intelligence community has convened for the field’s most anticipated and controversial event—a meeting to confer the Loebner Prize on the winner of a competition called the Turing Test. The test is named for the British mathematician Alan Turing, one of the founders of computer science, who in 1950 attempted to answer one of the field’s earliest questions: can machines think? That is, would it ever be possible to construct a computer so sophisticated that it could actually be said to be thinking, to be intelligent, to have a mind? And if indeed there were, someday, such a machine: how would we know?

Instead of debating this question on purely theoretical grounds, Turing proposed an experiment. Several judges each pose questions, via computer terminal, to several pairs of unseen correspondents, one a human “confederate,” the other a computer program, and attempt to discern which is which. The dialogue can range from small talk to trivia questions, from celebrity gossip to heavy-duty philosophy—the whole gamut of human conversation. Turing predicted that by the year 2000, computers would be able to fool 30 percent of human judges after five minutes of conversation, and that as a result, one would “be able to speak of machines thinking without expecting to be contradicted.”

Turing’s prediction has not come to pass; however, at the 2008 contest, the top-scoring computer program missed that mark by just a single vote. When I read the news, I realized instantly that the 2009 test in Brighton could be the decisive one. I’d never attended the event, but I felt I had to go—and not just as a spectator, but as part of the human defense. A steely voice had risen up inside me, seemingly out of nowhere: Not on my watch. I determined to become a confederate.

The thought of going head-to-head (head-to-motherboard?) against some of the world’s top AI programs filled me with a romantic notion that, as a confederate, I would be defending the human race, à la Garry Kasparov’s chess match against Deep Blue.

During the competition, each of four judges will type a conversation with one of us for five minutes, then the other, and then will have 10 minutes to reflect and decide which one is the human. Judges will also rank all the contestants—this is used in part as a tiebreaking measure. The computer program receiving the most votes and highest ranking from the judges (regardless of whether it passes the Turing Test by fooling 30 percent of them) is awarded the title of the Most Human Computer. It is this title that the research teams are all gunning for, the one with the cash prize (usually $3,000), the one with which most everyone involved in the contest is principally concerned. But there is also, intriguingly, another title, one given to the confederate who is most convincing: the Most Human Human award.

One of the first winners, in 1994, was the journalist and science-fiction writer Charles Platt. How’d he do it? By “being moody, irritable, and obnoxious,” as he explained in Wired magazine—which strikes me as not only hilarious and bleak, but, in some deeper sense, a call to arms: how, in fact, do we be the most human we can be—not only under the constraints of the test, but in life?

THE IMPORTANCE OF BEING YOURSELF

Since 1991, the Turing Test has been administered at the so-called Loebner Prize competition, an event sponsored by a colorful figure: the former baron of plastic roll-up portable disco dance floors, Hugh Loebner. When asked his motives for orchestrating this annual Turing Test, Loebner cites laziness, of all things: his utopian future, apparently, is one in which unemployment rates are nearly 100 percent and virtually all of human endeavor and industry is outsourced to intelligent machines.

To learn how to become a confederate, I sought out Loebner himself, who put me in touch with contest organizers, to whom I explained that I’m a nonfiction writer of science and philosophy, fascinated by the Most Human Human award. Soon I was on the confederate roster. I was briefed on the logistics of the competition, but not much else. “There’s not much more you need to know, really,” I was told. “You are human, so just be yourself.”

Just be yourself has become, in effect, the confederate motto, but it seems to me like a somewhat naive overconfidence in human instincts—or at worst, like fixing the fight. Many of the AI programs we confederates go up against are the result of decades of work. Then again, so are we. But the AI research teams have huge databases of test runs for their programs, and they’ve done statistical analysis on these archives: the programs know how to deftly guide the conversation away from their shortcomings and toward their strengths, know which conversational routes lead to deep exchange and which ones fizzle. The average off-the-street confederate’s instincts—or judge’s, for that matter—aren’t likely to be so good. This is a strange and deeply interesting point, amply proved by the perennial demand in our society for dating coaches and public-speaking classes. The transcripts from the 2008 contest show the humans to be such wet blankets that the judges become downright apologetic for failing to provoke better conversation: “I feel sorry for the humans behind the screen, I reckon they must be getting a bit bored talking about the weather,” one writes; another offers, meekly, “Sorry for being so banal.” Meanwhile a computer appears to be charming the pants off one judge, who in no time at all is gushing LOLs and smiley-face emoticons. We can do better.

Thus, my intention from the start was to thoroughly disobey the advice to just show up and be myself—I would spend months preparing to give it everything I had.

Ordinarily this notion wouldn’t be odd at all, of course—we train and prepare for tennis competitions, spelling bees, standardized tests, and the like. But given that the Turing Test is meant to evaluate how human I am, the implication seems to be that being human (and being oneself) is about more than simply showing up.

THE SENTENCE

To understand why our human sense of self is so bound up with the history of computers, it’s important to realize that computers used to behuman. In the early 20th century, before a “computer” was one of the digital processing devices that permeate our 21st-century lives, it was something else: a job description.

From the mid-18th century onward, computers, many of them women, were on the payrolls of corporations, engineering firms, and universities, performing calculations and numerical analysis, sometimes with the use of a rudimentary calculator. These original, human computers were behind the calculations for everything from the first accurate prediction, in 1757, for the return of Halley’s Comet—early proof of Newton’s theory of gravity—to the Manhattan Project at Los Alamos, where the physicist Richard Feynman oversaw a group of human computers.

It’s amazing to look back at some of the earliest papers on computer science and see the authors attempting to explain what exactly these new contraptions were. Turing’s paper, for instance, describes the unheard-of “digital computer” by making analogies to a human computer:

    The idea behind digital computers may be explained by saying that these machines are intended to carry out any operations which could be done by a human computer.

Of course, in the decades that followed, we know that the quotation marks migrated, and now it is “digital computer” that is not only the default term, but the literal one. In the mid-20th century, a piece of cutting-edge mathematical gadgetry was said to be “like a computer.” In the 21st century, it is the human math whiz who is “like a computer.” It’s an odd twist: we’re like the thing that used to be like us. We imitate our old imitators, in one of the strange reversals in the long saga of human uniqueness.

Philosophers, psychologists, and scientists have been puzzling over the essential definition of human uniqueness since the beginning of recorded history. The Harvard psychologist Daniel Gilbert says that every psychologist must, at some point in his or her career, write a version of what he calls “The Sentence.” Specifically, The Sentence reads like this:

    The human being is the only animal that ______.

The story of humans’ sense of self is, you might say, the story of failed, debunked versions of The Sentence. Except now it’s not just the animals that we’re worried about.

We once thought humans were unique for using language, but this seems less certain each year; we once thought humans were unique for using tools, but this claim also erodes with ongoing animal-behavior research; we once thought humans were unique for being able to do mathematics, and now we can barely imagine being able to do what our calculators can.

We might ask ourselves: Is it appropriate to allow our definition of our own uniqueness to be, in some sense, reactive to the advancing front of technology? And why is it that we are so compelled to feel unique in the first place?

“Sometimes it seems,” says Douglas Hofstadter, a Pulitzer Prize–winning cognitive scientist, “as though each new step towards AI, rather than producing something which everyone agrees is real intelligence, merely reveals what real intelligence is not.” While at first this seems a consoling position—one that keeps our unique claim to thought intact—it does bear the uncomfortable appearance of a gradual retreat, like a medieval army withdrawing from the castle to the keep. But the retreat can’t continue indefinitely. Consider: if everything that we thought hinged on thinking turns out to not involve it, then … what is thinking? It would seem to reduce to either an epiphenomenon—a kind of “exhaust” thrown off by the brain—or, worse, an illusion.

Where is the keep of our selfhood?

The story of the 21st century will be, in part, the story of the drawing and redrawing of these battle lines, the story of Homo sapiens trying to stake a claim on shifting ground, flanked by beast and machine, pinned between meat and math.

Is this retreat a good thing or a bad thing? For instance, does the fact that computers are so good at mathematics in some sense take away an arena of human activity, or does it free us from having to do a nonhuman activity, liberating us into a more human life? The latter view seems to be more appealing, but less so when we begin to imagine a point in the future when the number of “human activities” left for us to be “liberated” into has grown uncomfortably small. What then?

Alan Turing proposed his test as a way to measure technology’s progress, but it just as easily lets us measure our own. The Oxford philosopher John Lucas says, for instance, that if we fail to prevent the machines from passing the Turing Test, it will be “not because machines are so intelligent, but because humans, many of them at least, are so wooden.”

Beyond its use as a technological benchmark, the Turing Test is, at bottom, about the act of communication. I see its deepest questions as practical ones: How do we connect meaningfully with each other, as meaningfully as possible, within the limits of language and time? How does empathy work? What is the process by which someone enters into our life and comes to mean something to us? These, to me, are the test’s most central questions—the most central questions of being human.

Part of what’s fascinating about studying the programs that have done well at the Turing Test is seeing how conversation can work in the total absence of emotional intimacy. A look at the transcripts of Turing Tests past is, frankly, a sobering tour of the various ways in which we demur, dodge the question, lighten the mood, change the subject, distract, burn time: what shouldn’t pass for real conversation at the Turing Test probably shouldn’t be allowed to pass for real conversation in everyday life either.

HOW TO TALK LIKE A HUMAN

When the Turing Test was first proposed in 1950, it was a hypothetical: technology was nowhere near the point at which a practical test was possible. But, as we know, it got there; the first conversational computer program to attract significant notice and attention was Eliza, written in 1964 and 1965 by Joseph Weizenbaum at MIT. Modeled after a Rogerian therapist, Eliza worked on a very simple principle: extract key words from the users’ own language, and pose their statements back to them. (“I am unhappy.” “Do you think coming here will help you not to be unhappy?”) If in doubt, it might fall back on some completely generic phrases, like “Please go on.” This technique of fitting the users’ statements into predefined patterns and responding with a prescribed phrasing of its own—called “template matching”—was Eliza’s only capacity.

A look at an Eliza transcript reveals how adeptly such an impoverished set of rules can, in the right context, pass at a glance for understanding:

User: Men are all alike.

Eliza: In what way?

User: They’re always bugging us about something or other.

Eliza: Can you think of a specific example?

User: Well, my boyfriend made me come here.

Eliza: Your boyfriend made you come here.

User: He says I’m depressed much of the time.

Eliza: I am sorry to hear you are depressed.

User: It’s true. I am unhappy.

Eliza: Do you think coming here will help you not to be unhappy?

User: I need some help, that much seems certain.

Eliza: What would it mean to you if you got some help?

User: Perhaps I could learn to get along with my mother.

Eliza: Tell me more about your family.

The results were stunning: many of the people who first talked with Eliza were convinced that they were having a genuine human exchange. In some cases, even Weizenbaum’s own insistence to the contrary was of no use. People asked to be left alone to talk “in private,” sometimes for hours, and returned with reports of having had a meaningful therapeutic experience. Meanwhile, academics leapt to conclude that Eliza represented “a general solution to the problem of computer understanding of natural language.”

One of the strangest twists to the Eliza story, however, was the reaction of the medical community, which decided Weizenbaum had hit upon something both brilliant and useful. The Journal of Nervous and Mental Disease, for example, said of Eliza in 1966:

    Several hundred patients an hour could be handled by a computer system designed for this purpose. The human therapist, involved in the design and operation of this system, would not be replaced, but would become a much more efficient man.

The famed scientist Carl Sagan, in 1975, concurred:

    I can imagine the development of a network of computer psychotherapeutic terminals, something like arrays of large telephone booths, in which, for a few dollars a session, we would be able to talk with an attentive, tested, and largely non-directive psychotherapist.

As for Weizenbaum, appalled and horrified, he did something almost unheard-of: an about-face on his entire career. He pulled the plug on the Eliza project, encouraged his own critics, and became one of science’s most outspoken opponents of AI research. But the genie was out of the bottle, and there was no going back. The basic “template matching” skeleton and approach of Eliza has been reworked and implemented in some form or another in almost every chat program since, including the contenders at the 2009 Loebner Prize competition. The enthusiasm—as well as the unease—about these programs has only grown.

THE JERK AS GENIUS

The first Loebner Prize competition was held on November 8, 1991, at the Boston Computer Museum. In its first few years, the contest required each program and human confederate to choose a topic, as a means of limiting the conversation. One of the confederates in 1991 was the Shakespeare expert Cynthia Clay, who was, famously, deemed a computer by three different judges after a conversation about the playwright. The consensus seemed to be: “No one knows that much about Shakespeare.” (For this reason, Clay took her misclassifications as a compliment.)

The programmer Joseph Weintraub chose “Whimsical Conversation” for his PC Therapist III and went on to earn the very first Most Human Computer award. As the program practiced it, “whimsical conversation” was not a topic at all, but a manner—a crucial distinction. Weintraub was able to play off a looseness in the contest rules, the natural behavior patterns of chatbots, and people’s stereotypes about computers and humans, all at once. Strategically, this was brilliant.

By dutifully and scrupulously providing information in response to the questions asked, Clay demonstrated her knowledge and understanding—but sometimes in a factual, encyclopedic way commonly associated with computer systems. Here is a sample of Clay’s conversation:

Judge: What is your opinion on Shakespeare’s plays?

Confederate: That’s pretty general; would you be more specific? Otherwise, I’ll just say I like them.

The computer at the “Whimsical Conversation” terminal stood in stark contrast:

Judge: It has been a long day! Now I think I’m ready for some fun. The weather isn’t very pleasant today. Do you have any jokes that could lift the clouds?

Computer: Everybody talks about the weather but nobody seems to do much about it. Why do you need to tell me now you think you’re ready for some fun? Groannnnnn … … … … …

Judge: What is the definition of whimsical conversation?

Computer: Didn’t you say well anyway I would imagine whimsical conversation is like a series of knight’s moves in chess—skrt of zig-zag rather than following any nparticular line.? [Weintraub’s program, like many that followed it, faked typos. Any unintentional typing errors in the transcripts that follow have been corrected.] Why do you ask? Was that a clever comment, or what? Are such questions much on your mind?

Judge: I like the image of knights moving haphazardly across the chess board, does that mean there is no thought to whimsical conversation?

Computer: I could swear you just said how do you define whimsical?? How do yku define whimsical? Were you always so sick sick sick? Why do you need to tell me you like the image of knights moving haphazardly across the chess board?

“I really thought [PC Therapist] was human, because it … was weird and funny, in a normal sort of way,” said one of the judges, a Harvard graduate student. Weintraub’s program, shifting topics wildly and spouting non sequiturs and canned one-liners, came off as zany, a jokester, a much more “human” personality type. At least I used to think so—before I learned how easy this was to mimic.

As Richard Wallace, three-time winner of the Most Human Computer award (’00, ’01, and ’04), explains:

    Experience with [Wallace’s chatbot] ALICE indicates that most casual conversation is “state-less,” that is, each reply depends only on the current query, without any knowledge of the history of the conversation required to formulate the reply.

Many human conversations function in this way, and it behooves AI researchers to determine which types of conversation are stateless—with each remark depending only on the last—and try to create these very sorts of interactions. It’s our job as confederates, as humans, to resist them.

One of the classic stateless conversation types is the kind of zany free-associative riffing that Weintraub’s program, PC Therapist III, employed. Another, it turns out, is verbal abuse.

In May 1989, Mark Humphrys, a 21-year-old University College Dublin undergraduate, put online an Eliza-style program he’d written, called “MGonz,” and left the building for the day. A user (screen name “Someone”) at Drake University in Iowa tentatively sent the message “finger” to Humphrys’s account—an early-Internet command that acted as a request for basic information about a user. To Someone’s surprise, a response came back immediately: “cut this cryptic shit speak in full sentences.” This began an argument between Someone and MGonz that lasted almost an hour and a half. (The best part was undoubtedly when Someone said, “you sound like a goddamn robot that repeats everything.”)

Returning to the lab the next morning, Humphrys was stunned to find the log, and felt a strange, ambivalent emotion. His program might have just shown how to pass the Turing Test, he thought—but the evidence was so profane that he was afraid to publish it.

Humphrys’s twist on the Eliza paradigm was to abandon the therapist persona for that of an abusive jerk; when it lacked any clear cue for what to say, MGonz fell back not on therapy clichés like “How does that make you feel?” but on things like “You are obviously an asshole,” or “Ah type something interesting or shut up.” It’s a stroke of genius because, as becomes painfully clear from reading the MGonz transcripts, argument is stateless—that is, unanchored from all context, a kind of Markov chain of riposte, meta-riposte, meta-meta-riposte. Each remark after the first is only about the previous remark. If a program can induce us to sink to this level, of course it can pass the Turing Test.

Once again, the question of what types of human behavior computers can imitate shines light on how we conduct our own, human lives. Verbal abuse is simply less complex than other forms of conversation. In fact, since reading the papers on MGonz, and transcripts of its conversations, I find myself much more able to constructively manage heated conversations. Aware of the stateless, knee-jerk character of the terse remark I want to blurt out, I recognize that that remark has far more to do with a reflex reaction to the very last sentence of the conversation than with either the issue at hand or the person I’m talking to. All of a sudden, the absurdity and ridiculousness of this kind of escalation become quantitatively clear, and, contemptuously unwilling to act like a bot, I steer myself toward a more “stateful” response: better living through science.

BEWARE OF BANALITY

Entering the Brighton Centre, I found my way to the Loebner Prize contest room. I saw rows of seats, where a handful of audience members had already gathered, and up front, what could only be the bot programmers worked hurriedly, plugging in tangles of wires and making the last flurries of keystrokes. Before I could get too good a look at them, this year’s test organizer, Philip Jackson, greeted me and led me behind a velvet curtain to the confederate area. Out of view of the audience and the judges, the four of us confederates sat around a rectangular table, each at a laptop set up for the test: Doug, a Canadian linguistics researcher; Dave, an American engineer working for Sandia National Laboratories; Olga, a speech-research graduate student from South Africa; and me. As we introduced ourselves, we could hear the judges and audience members slowly filing in, but couldn’t see them around the curtain. A man zoomed by in a green floral shirt, talking a mile a minute and devouring finger sandwiches. Though I had never met him before, I knew instantly he could be only one person: Hugh Loebner. Everything was in place, he told us, between bites, and the first round of the test would start momentarily. We four confederates grew quiet, staring at the blinking cursors on our laptops. My hands were poised over the keyboard, like a nervous gunfighter’s over his holsters.

The cursor, blinking. I, unblinking. Then all at once, letters and words began to materialize:

Hi how are you doing?

The Turing Test had begun.

I had learned from reading past Loebner Prize transcripts that judges come in two types: the small-talkers and the interrogators. The latter go straight in with word problems, spatial-reasoning questions, deliberate misspellings. They lay down a verbal obstacle course, and you have to run it. This type of conversation is extraordinarily hard for programmers to prepare against, because anything goes—and this is why Turing had language and conversation in mind as his test, because they are really a test of everything. The downside to the give-’em-the-third-degree approach is that it doesn’t leave much room to express yourself, personality-wise.

The small-talk approach has the advantage of making it easier to get a sense of who a person is—if you are indeed talking to a person. And this style of conversation comes more naturally to layperson judges. For one reason or another, small talk has been explicitly and implicitly encouraged among Loebner Prize judges. It’s come to be known as the “strangers on a plane” paradigm. The downside is that these conversations are, in some sense, uniform—familiar in a way that allows a programmer to anticipate a number of the questions.

I started typing back.

Confederate: hey there!

Confederate: i’m good, excited to actually be typing

Confederate: how are you?

I could imagine the whole lackluster conversation spread out before me: Good. Where are you from? / Seattle. How about yourself? / London.

Four minutes and 43 seconds left. My fingers tapped and fluttered anxiously.

I could just feel the clock grinding away while we lingered over the pleasantries. I felt this desperate urge to go off script, cut the crap, cut to the chase—because I knew that the computers could do the small-talk thing, which played directly into their preparation. As the generic civilities stretched forebodingly out before me, I realized that this very kind of conversational boilerplate was the enemy, every bit as much as the bots. How, I was thinking as I typed another unassuming pleasantry, do I get an obviously human connection to happen?

Taking Turns

Part of what I needed to figure out was how to exploit the Loebner Prize’s unusual “live typing” medium. The protocol being used was unlike e-mails, text messages, and standard instant-messaging systems in a very crucial way: it transmitted our typing keystroke by keystroke. The judge and I were watching each other type, typos and backspacing and all. I remember some Internet chat programs back in the ’90s trying out this character-at-a-time approach, but people for the most part rejected it. It was too invasive, was the feeling: what people like about writing is the time and space to compose and edit a message before sharing it with the other person. The advantage of the character-at-a-time transmission, though, is that it approaches much more closely the condition of speech, with its fluidity of turn-taking and its choppy grammar: what’s lost in eloquence is made up for in agility.

It also, then, lets us see typing’s “negative space”: hesitation. In a chat conversation where text is transmitted with every carriage return, only egregiously long pauses are taken to be part of the interaction. With more fluid and immediate feedback, silence acquires meaning. Failing to quickly answer a question in a face-to-face conversation, for instance, is tantamount in many cases to answering it. I recall asking a friend of mine how things were going with the woman he’d started seeing; the um and the tiny pause in which he searched for the right words made it clear they were having problems.

So what did the Loebner Prize’s unusual (and recently implemented) protocols enable and disable, compared with the standard, walkie-talkie, turn-taking style? Long missives weren’t going to work, as they had in previous years, when programs were able to steamroll the judges by eating up the clock and delivering ridiculously prolix answers. If two parties are taking strict turns under time pressure, they are putting themselves at the mercy of the length of the other’s turns. Here, for instance, is one program’s conversation transcript from 1996:

Computer: How about telling me a joke?

Judge: No.

Computer: Here’s my favorite joke … A dog limps into a bar with a bloody bandage on his foot. He’s wearing a 10-gallon hat, six-shooters in his holsters and chaps. He growled, “I’m a-lookin’ for the man that shot my paw.”

“The joke’s not funny …” the judge writes, giving the program an opening to tell another one—which it does (“A knotty, worn-out old string walks into a bar …”). Meanwhile, three full minutes have elapsed. If a computer (or confederate) started rambling on too long under the new, live-typing protocols, the judge could and would just cut it off.

And so another piece of my confederate strategy fell into place. I would treat the Turing Test’s strange and unfamiliar textual medium more like spoken English, and less like the written language. I would attempt to disrupt the turn-taking “wait and parse” pattern that computers understand, and create a single, flowing duet of verbal behavior, emphasizing timing. If computers understand little about verbal “harmony,” they understand even less about rhythm.

If nothing was happening on my screen, whether or not it was my turn, I’d elaborate a little on my answer, or add a parenthetical, or throw a question back at the judge—just as we offer and/or fill audible silence when we talk out loud. If the judge took too long considering the next question, I’d keep talking. I would be the one (unlike the bots) with something to prove. If I knew what the judge was about to write, I’d spare him the keystrokes and jump in.

There’s a trade-off, of course, between the number of opportunities for serve and volley, and the sophistication of the responses themselves. The former thrives with brevity, the latter with length. It seemed to me, though, that so much of the nuance (or difficulty) in conversation comes from understanding (or misunderstanding) a question and offering an appropriate (or inappropriate) response—thus, it made sense to maximize the number of interchanges.

Some judges, I discovered, would be startled or confused at this jumping of the gun, and I saw them pause, hesitate, yield, even start backspacing what they had half-written. Other judges cottoned on immediately, and leapt right in after me.

In the first round of the 2009 contest, judge Shalom Lappin—a computational linguist at King’s College London—spoke with a computer program called Cleverbot, and then with me. My strategy of verbosity was clearly in evidence: I made 1,089 keystrokes in five minutes (3.6 keystrokes a second) to Cleverbot’s 356 (1.2/sec), and Lappin made 548 keystrokes (1.8/sec) in my conversation, compared with 397 (1.3/sec) with Cleverbot. Not only did I say three times as much as my silicon adversary, but I engaged the judge more, to the tune of 38 percent more typing from Lappin.

Reviewing the logs later, though, I looked for a way to quantify the fluidity of the human-to-human interactions against the rigidity of the human-to-machine ones. It occurred to me that you could count the changes—let’s call them “swaps”—of the party who typed the latest keystroke. I did manage to type three times as much as Cleverbot, but the real story, as it turns out, is in the swaps. Lappin’s conversation with Cleverbot had 33; his conversation with me had 492, almost 15 times as many.

The Confederate’s gambit

You don’t converse with Google, or with most computer systems; you depose them. There’s a crucial difference. Interestingly, many Loebner Prize judges approach the Turing Test as a kind of cross-examination; strangely, a number of confederates also seem to approach it with that dynamic in mind. One of the human-to-human conversations in 2008 never manages to get out of that stiff question-and-response mode:

Judge: Do you have a long drive?

Confederate: fairly long

Judge: so do I :( ah well, do you think you could have used public transport?

Confederate: i could have

Judge: and why not?

Confederate: i chose not to

Judge: that’s fair. Do you think we have too many cars on the road or not enough today?

Confederate: it’s not for me to say

Yawn! But the computer in this pair is playful with the judge from the get-go:

Judge: HI

Computer: Amen to that.

Judge: quite the evangelist

Computer: Our Father, who art in cyberspace, give us today our daily bandwidth.

Judge: evangelist / nerd lol. So how are things with you today?

And with that, the program has practically sealed up the judge’s confidence in its humanity with its second sentence. Note that the confederate’s stiff answers prompt more grilling and forced conversation—what’s your opinion on such-and-such political topic? But with the computer, the judge, misled by the opening wisecracks into assuming it’s the real person, remains utterly casual: how are things? This makes the contest easier for the computer and harder for the confederate.

It surprised me to see some confederates being coy with their judges. Asked what kind of engineer he is, Dave, to my left, answered, “A good one. :)” And Doug, to my right, responded to a question about what brought him to Brighton with “if I tell you, you’ll know immediately that I’m human ;-)” For my money, wit is very successful, but coyness is a double-edged sword. You show a sense of humor, but you jam the cogs of the conversation. Probably the most dangerous thing a confederate can do in a Turing Test is stall. It’s suspect—as the guilty party would tend to be the one running out the clock—and it squanders your most precious resource: time.

The humans in a Turing Test are strangers, limited to a medium that is slow and has no vocal tonality, and without much time. A five-second Turing Test would be an easy win for the machines: the judges, barely able to even say “hello,” simply wouldn’t be able to get enough data from their respondents to make any kind of judgment. A five-hour test would be an easy win for the humans. The Loebner Prize organizers have tried different time limits since the contest’s inception, but in recent years they’ve mostly adhered to Turing’s original prescription of five minutes: around the point when conversation starts to get interesting.

A big part of what I needed to do as a confederate was simply to make as much engagement happen in those minutes as I physically and mentally could. Rather than adopt the terseness of a deponent, I offered the prolixity of a writer. In other words, I talked a lot. I stopped typing only when to keep going would have seemed blatantly impolite or blatantly suspicious. The rest of the time, my fingers were moving. I went out of my way to embody that maxim of “A bore is a man who, being asked ‘How are you?’ starts telling you how he is.”

Judge: Hi, how’s things?

Confederate: hey there

Confederate: things are good

Confederate: a lot of waiting, but …

Confederate: good to be back now and going along

Confederate: how are you?

When we’d finished, and my judge was engaged in conversation with one of my computer counterparts, I strolled around the table, seeing what my comrades were up to. Looking over at my fellow confederate Dave’s screen, I noticed his conversation began like he was on the receiving end of an interrogation, and he was answering in a kind of minimal staccato:

Judge: Are you from Brighton?

Confederate: No, from the US

Judge: What are you doing in Brighton?

Confederate: On business

Judge: How did you get involved with the competition?

Confederate: I answered an e-mail.

Like a good deponent, he let the questioner do all the work. When I saw how stiff Dave was being, I confess I felt a certain confidence—I, in my role as the world’s worst deponent, was perhaps in fairly good shape as far as the Most Human Human award was concerned.

This confidence lasted approximately 60 seconds, or enough time for me to continue around the table and see what another fellow confederate, Doug, and his judge had been saying.

Judge: Hey Bro, I’m from TO.

Confederate: cool

Confederate: leafs suck

Confederate: ;-)

Judge: I am just back from a sabbatical in the CS Dept. at U of T.

Confederate: nice!

Judge: I remember when they were a great team.

Judge: That carbon date me, eh?

Confederate: well, the habs were a great team once, too …

Confederate: *sigh*

Judge: YEH, THEY SUCK TOO.

Confederate: (I’m from Montreal, if you didn’t guess)

Doug and his judge had just discovered that they were both Canadian. They let rip with abbreviations and nicknames and slang and local references. And then they started to talk about hockey.

I was in trouble.

Six months after the 2009 contest, a video appeared on YouTube of a man having a shockingly cogent conversation with a bot about Shakespeare’s Hamlet. Some suspected it might herald a new age for chatbots, and for AI. Others, including myself, were unimpressed. Sophisticated behavior doesn’t necessarily indicate a mind. It might indicate just a memory. As Dalí so famously put it, “The first man to compare the cheeks of a young woman to a rose was obviously a poet; the first to repeat it was possibly an idiot.”

For instance, Richard Wallace, the three-time Most Human Computer winner, recounts an “AI urban legend” in which

    a famous natural language researcher was embarrassed … when it became apparent to his audience of Texas bankers that the robot was consistently responding to the next question he was about to ask … [His] demonstration of natural language understanding … was in reality nothing but a simple script.

The moral of the story: no demonstration is ever sufficient. Only interaction will do. In the 1997 contest, one judge gets taken for a ride by Catherine, waxing political and really engaging in the topical conversation “she” has been programmed to lead about the Clintons and Whitewater. In fact, everything is going swimmingly until the very end, when the judge signs off:

Judge: it looks like i’ve got to go, Catherine. its been nice talking with you

Judge: do you need water or something before the 5 minute rounds?

At which point the program erupts into gibberish.

Computer: OK, yes on balance … Time to get off this one I think and onto something more down to earth!

Judge: like what?

Computer: Almost certainly! let’s move on

Computer: I suppose it depends on where you’re coming from, but as the song goes in My Fair Lady, “Why can’t a woman be more like a man?”

Defeat from the jaws of victory.

We so often think of intelligence, of AI, in terms of sophistication, or complexity of behavior. But in so many cases, it’s impossible to say much with certainty about the program itself, because any number of different pieces of software—of wildly varying levels of “intelligence”—could have produced that behavior.

No, I think sophistication, complexity of behavior, is not it at all. For instance, you can’t judge the intelligence of an orator by the eloquence of his prepared remarks; you must wait until the Q&A and see how he fields questions. The computation theorist Hava Siegelmann once described intelligence as “a kind of sensitivity to things.” These Turing Test programs that hold forth may produce interesting output, but they’re rigid and inflexible. They are, in other words, insensitive—occasionally fascinating talkers that cannot listen.

As computing technology in the 21st century moves increasingly toward mobile devices, we’ve seen the 1990s’ explosive growth in processor speed taper off, and product development become less about raw computing horsepower than about the overall design of the product and its fluidity, reactivity, and ease of use. This fascinating shift in computing emphasis may be the cause, effect, or correlative of a healthier view of human intelligence—an understanding, not so much that it is complex and powerful, per se, as that it is reactive, responsive, sensitive, nimble. Our computers, flawed mirrors that they are, have helped us see that about ourselves.

the Most Human Human

The Most Human Computer award in 2009 goes to David Levy and his program, Do-Much-More. Levy, who also won in ’97, with Catherine, is an intriguing guy: he was one of the big early figures in the digital-chess scene of the ’70s and ’80s, and was one of the organizers of the Marion Tinsley–Chinook checkers matches that preceded the Kasparov–Deep Blue showdowns in the ’90s. He’s also the author of the recent nonfiction book Love and Sex With Robots, to give you an idea of the sorts of things that are on his mind when he’s not competing for the Loebner Prize.

Levy stands up, to applause, accepts the award from Philip Jackson and Hugh Loebner, and makes a short speech about the importance of AI for a bright future, and the importance of the Loebner Prize for AI. I know what’s next on the agenda, and my stomach knots. I’m certain that Doug’s gotten it; he and the judge were talking Canada 30 seconds into their conversation.

Ridiculous Canadians and their ice hockey, I’m thinking. Then I’m thinking how ridiculous it is that I’m even allowing myself to get this worked up about some silly award. Then I’m thinking how ridiculous it is to fly 5,000 miles just to have a few minutes’ worth of IM conversations. Then I’m thinking how maybe it’ll be great to be the runner-up; I can compete again in 2010, in Los Angeles, with the home-field cultural advantage, and finally prove—

“And the results here show also the identification of the humans,” Jackson announces, “and from the ranking list we can see that ‘Confederate 1,’ which is Brian Christian, was the most human.”

And he hands me the certificate for the Most Human Human award.

I didn’t know how to feel, exactly. It seemed strange to treat the award as meaningless or trivial, but did winning really represent something about me as a person? More than anything, I felt that together, my fellow confederates and I had avenged the mistakes of 2008 in dramatic fashion. That year, the 12 judges decided five times that computer programs were more human than confederates. In three of those instances, the judge was fooled by a program named Elbot, which was the handiwork of a company called Artificial Solutions, one of many new businesses leveraging chatbot technology. One more deception, and Elbot would have tricked 33 percent of that year’s dozen judges—surpassing Turing’s 30 percent mark, and making history. After Elbot’s victory at the Loebner Prize and the publicity that followed, the company seemingly decided to prioritize the Elbot software’s more commercial applications; at any rate, it had not entered the ’09 contest as the returning champion.

In some ways a closer fight would have been more dramatic. Between us, we confederates hadn’t permitted a single vote to go the machines’ way. Whereas 2008 was a nail-biter, 2009 was a rout. We think of science as an unhaltable, indefatigable advance. But in the context of the Turing Test, humans—dynamic as ever—don’t allow for that kind of narrative. We don’t provide the kind of benchmark that sits still.

As for the prospects of AI, some people imagine the future of computing as a kind of heaven. Rallying behind an idea called “The Singularity,” people like Ray Kurzweil (in The Singularity Is Near) and his cohort of believers envision a moment when we make smarter- than-us machines, which make machines smarter than themselves, and so on, and the whole thing accelerates exponentially toward a massive ultra-intelligence that we can barely fathom. Such a time will become, in their view, a kind of a techno-Rapture, in which humans can upload their consciousness onto the Internet and get assumed—if not bodily, than at least mentally—into an eternal, imperishable afterlife in the world of electricity.

Others imagine the future of computing as a kind of hell. Machines black out the sun, level our cities, seal us in hyperbaric chambers, and siphon our body heat forever.

I’m no futurist, but I suppose if anything, I prefer to think of the long-term future of AI as a kind of purgatory: a place where the flawed but good-hearted go to be purified—and tested—and come out better on the other side.

Who would have imagined that the computer’s earliest achievements would be in the domain of logical analysis, a capacity once held to be what made us most different from everything else on the planet? That it could fly a plane and guide a missile before it could ride a bike? That it could create plausible preludes in the style of Bach before it could make plausible small talk? That it could translate before it could paraphrase? That it could spin half-discernible essays on postmodern theory before it could be shown a chair and say, as most toddlers can, “chair”?

As computers have mastered rarefied domains once thought to be uniquely human, they simultaneously have failed to master the ground-floor basics of the human experience—spatial orientation, object recognition, natural language, adaptive goal-setting—and in so doing, have shown us how impressive, computationally and otherwise, such minute-to-minute fundamentals truly are.

We forget how impressive we are. Computers are reminding us.

One of my best friends was a barista in high school. Over the course of a day, she would make countless subtle adjustments to the espresso being made, to account for everything from the freshness of the beans to the temperature of the machine to the barometric pressure’s effect on the steam volume, meanwhile manipulating the machine with an octopus’s dexterity and bantering with all manner of customers on whatever topics came up. Then she went to college and landed her first “real” job: rigidly procedural data entry. She thought longingly back to her barista days—when her job actually made demands of her intelligence.

Perhaps the fetishization of analytical thinking, and the concomitant denigration of the creatural—that is, animal—and bodily aspects of life are two things we’d do well to leave behind. Perhaps at last, in the beginnings of an age of AI, we are starting to center ourselves again, after generations of living slightly to one side—the logical, left-hemisphere side. Add to this that humans’ contempt for “soulless” animals, our unwillingness to think of ourselves as descended from our fellow “beasts,” is now challenged on all fronts: growing secularism and empiricism, growing appreciation for the cognitive and behavioral abilities of organisms other than ourselves, and, not coincidentally, the entrance onto the scene of an entity with considerably less soul than we sense in a common chimpanzee or bonobo—in this way AI may even turn out to be a boon for animal rights.

Indeed, it’s entirely possible that we’ve seen the high-water mark of our left-hemisphere bias. I think the return of a more balanced view of the brain and mind—and of human identity—is a good thing, one that brings with it a changing perspective on the sophistication of various tasks.

It’s my belief that only experiencing and understanding truly disembodied cognition—only seeing the coldness and deadness and disconnectedness of something that really does deal in pure abstraction, divorced from sensory reality—can snap us out of it. Only this can bring us, quite literally, back to our senses.

In a 2006 article about the Turing Test, the Loebner Prize co-founder Robert Epstein writes, “One thing is certain: whereas the confederates in the competition will never get any smarter, the computers will.” I agree with the latter, and couldn’t disagree more strongly with the former.

When the world-champion chess player Garry Kasparov defeated Deep Blue, rather convincingly, in their first encounter in 1996, he and IBM readily agreed to return the next year for a rematch. When Deep Blue beat Kasparov (rather less convincingly) in ’97, Kasparov proposed another rematch for ’98, but IBM would have none of it. The company dismantled Deep Blue, which never played chess again.

The apparent implication is that—because technological evolution seems to occur so much faster than biological evolution (measured in years rather than millennia)—once the Homo sapiens species is overtaken, it won’t be able to catch up. Simply put: the Turing Test, once passed, is passed forever. I don’t buy it.

Rather, IBM’s odd anxiousness to get out of Dodge after the ’97 match suggests a kind of insecurity on its part that I think proves my point. The fact is, the human race got to where it is by being the most adaptive, flexible, innovative, and quick-learning species on the planet. We’re not going to take defeat lying down.

No, I think that, while the first year that computers pass the Turing Test will certainly be a historic one, it will not mark the end of the story. Indeed, the next year’s Turing Test will truly be the one to watch—the one where we humans, knocked to the canvas, must pull ourselves up; the one where we learn how to be better friends, artists, teachers, parents, lovers; the one where we come back. More human than ever.

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KURZWEIL INVENTIONS

Actually, the number of important inventions developed by Raymond Kurzweil (and later also by his team) is quite unbelievable:
- "first computer program. Designed to process statistical data, the program was used by researchers at IBM"

- "a sophisticated pattern-recognition software program that analyzed musical pieces of great classical music composers and then synthesized its own songs in similar styles"

- " he performed a piano piece that was composed by a computer he also had built."

- "a computer program to match high school students with colleges"

- "the first omni-font optical character recognition system--a computer program capable of recognizing text written in any normal font"

- "a reading machine for the blind, which would allow blind people to understand written text by having a computer read it to them out loud. However, this device required the invention of two enabling technologies--the CCD flatbed scanner and the text-to-speech synthesizer. Under his direction, development of these new technologies was completed"

- "a new generation of music synthesizers capable of accurately duplicating the sounds of real instruments"

- "computer speech recognition systems for commercial use. The first product, which debuted in 1987, was the world's first large-vocabulary speech recognition program, allowing human users to dictate to their computers via microphone and then have the device transcribe their speech into written text. Later, the company combined the speech recognition technology with medical expert systems to create the Kurzweil VoiceMed (today called Clinical Reporter) line of products, which allow doctors to write medical reports by speaking to their computers instead of writing."

- "new pattern-recognition-based computer technologies to help people with disabilities such as blindness, dyslexia and ADD in school. Products include the Kurzweil 1000 text-to-speech converter software program, which enables a computer to read electronic and scanned text aloud to blind or visually-impaired users, and the Kurzweil 3000 program, which is a multifaceted electronic learning system that helps with reading, writing, and study skills."

- "an interactive computer education program for doctors and a computer-simulated patient."

- "Kurzweil started KurzweilCyberArt.com--a website featuring computer programs meant to assist the creative art process. The site offers free downloads of a program called AARON--a visual art synthesizer developed by Harold Cohen--and of "Kurzweil's Cybernetic Poet", which automatically creates poetry."

- "KurzweilAI.net, a website devoted towards showcasing news of scientific developments, publicizing the ideas of high-tech thinkers and critics alike, and promoting futurist-related discussion among the general population through the Mind-X forum."

- " improve the performance of FatKat's A.I. investment software program, enhancing its ability to recognize patterns in "currency fluctuations and stock-ownership trends.""

- "the "Kurzweil-National Federation of the Blind Reader" (K-NFB Reader)--a pocket-sized device consisting of a digital camera and computer unit. Like the Kurzweil Reading Machine of almost 30 years before, the K-NFB Reader is designed to aid blind people by reading written text out loud, only the newer machine is portable and collects texts through captured digital camera images while the older machine is very large and obtains all text through flatbed scanning."
Source and further information:
http://en.wikipedia.org/wiki/Ray_Kurzweil

Read more: What were the most important inventions created by Ray Kurzweil, and how were they most important? | Answerbag http://www.answerbag.com/q_view/979015#ixzz1DsjJ9mKp
 
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Brophy Sunday 13 February 2011 - 10:37 am | | Brophy Blog

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