February 9, 2012

The woman who remembered everything

Human memory is different from computer memory in many important ways. Computers store information in specific locations. While there are ways of storing meta-data with each piece of information, computer memory is very limited when it comes to context. For example, the stored image of your boyfriend may be given a title and a short description, but when the computer retrieves it, it will be a hard task to infer from the image multi-dimensional data such as character, events about this person, emotions, etc.

This is not how we do it

 Unlike computer memory which is designed human memory is the product of millions of years of evolution. Mammalian brains such as ours do not use fixed-address systems, but store memories in a very haphazard fashion; memories tend to overlap, combine or simply disappear. Neuroscience has not yet cracked the code of human memory but it does give us some first clues: our memories live in the hippocampus and the prefrontal cortex. Whenever we “remember” a rich set of data is retrieved which is contextually intertwined with emotions. Human memories are never like a video or a photograph or a text file; they are never “objective”. They are always “subjective”, i.e. value-laden. The plasticity of our brains might be the cause for our memories changing over time, or under a variety of emotional conditions (such as stress, excitement, sadness, etc.).

Jill Price (photo by Bryce Duffy)

An interesting case made news several years ago of an American lady named Jill Price who could remember virtually everything. Ms Price had a perfect recollection of every single event in her life since she was 12 years old. Her case has been studied by neuroscientist James McGaugh of UC Irvine. McCaugh and his collaborators named Ms Price’s syndrome as “hyperthymetic”, a Greek word meaning “supermemoriser”. Although, understanding what exactly happens in Ms Price’s brain is beyond the capabilities of current brain scan technologies, current observations indicate that her brain shares many characteristics of people with obsessive-compulsive syndrome. Ms Price is obsessive in “collecting” items (e.g. puffy toys) that remind her of things that happen to her; she is also going over and over again thinking about things that happen to her (she keeps a detailed diary), something that tends to reinforce neural pathways. Nevertheless these observations explain almost nothing. Her capability of remembering everything is truly “super-human”.

Rachel remembered having a mother

Imagining intelligent androids of the future has failed to deal satisfactorily with the issue of memory. In Blade Runner, for example, the android Rachel has been programmed with false memories; a childhood she never had. Tyler Corporation have given her photographs of her “parents” which Rachel treasures, since they convince her that she had a human past. Such emotional reaction to memories requires a human-like brain. Androids that can hold memories in a human-like fashion will be prone to all the problems that we face with our memories; ultimately we lose them, or they mutate into a subjective narrative that reflects our inner wishes rather than the facts that actually took place.  Like humans, androids must be able to lie about their past, without necessarily intending to. But that seems like a waste. Unless human programmers decide to install faulty memories in their creations, intelligent androids will be more like the hyperthymetic Ms Price.

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January 2, 2012

Alan Turing: Celebrating 100 years from his birth

Alan Turing was born in London on 23 June 1912. Arrested and convicted for homosexuality in 1952 he was ordered by the court to undergo chemical castration be injecting estrogens. In June 1954 Turing committed suicide by eating an apple poisoned with cyanide.  Turing was one of the greatest mathematicians of the 20th century. There is very little in the modern discourse on the future of technological civilization that Turing has not influenced.

The Enigma Machine

During WW2 he led in Bletchley Park (a secret location of British Naval counter-intelligence) a team of mathematicians and cryptanalysts in breaking the Nazi “Enigma” code. He did so by developing a “mirror” coding machine, a precursor of modern computers.

The Universal Machine, by Jin Wicked

His seminal paper on uncomputability expanded Gödel’s incompleteness theorem by introducing the concept of a “universal machine” (often called “Universal Turing Machine”), thereby foretelling the modern, digital computer. A Universal Machine is a machine that can be programmed to perform any operation. Turing showed that there will always be mathematical truths (theorems) which the Universal Machine will never be able, not only to solve but, – most importantly – to know a priori if they are solvable. In such cases the machine would never “halt”, i.e. end its operation, but would continue forever.

The Imitation Game: Guess who is what

Turing believed that computing machines will one day become as intelligent as humans, perhaps more so. He suggested the “imitation game”, in order to demonstrate a way to tell whether a machine was intelligent or not: if a human interrogator on the basis of a conversation between himself and some “unknown person” (an intelligent machine “imitating” a human) could not tell whether that “person” was human or not, then one had to accept that the intelligent machine was as intelligent as a human being. Although this “behaviourist” approach to “Artificial Intelligence” has been challenged, Turing’s Imitation Game remains the best available concept for assessing the degree of machine intelligence.

2012: The Alan Turing Year

This year 2012 marks 100 years since the birth of  Turing, and a number of celebrations are being organized around the world. You can find more by visiting this website.

Your author has written a play on the last days of Turing, which is currently on submission. You may read a summary of the play here, and some notes here.

 Turing Dreams will be celebrating the Alan Turing Centenary throughout 2012, by reporting regularly on events that are taking place. Stay tuned!

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January 1, 2012

2011 in review

The WordPress.com stats helper monkeys prepared a 2011 annual report for this blog.

Here’s an excerpt:

A San Francisco cable car holds 60 people. This blog was viewed about 2,800 times in 2011. If it were a cable car, it would take about 47 trips to carry that many people.

Click here to see the complete report.

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December 22, 2011

Blissful ignorance the key to machine intelligence?

A recent paper in Science reports an interesting experiment carried out at Princeton using fish and exploring the dynamics of crowd intelligence.  Researchers used golden shiners, a strongly schooling fish. They trained a large number of groups to swim toward a blue target, while smaller groups were trained to follow their natural predilection for a yellow target. When placed together, the large trained group would follow the smaller group to the yellow target. When fish with no prior training (the uninformed individuals) were introduced, however, the fish increasingly swam toward the majority-preferred blue target.

The blissful mind of a golden shiner

The story circulated in the media with much journalistic spin as “evidence” of how people take decisions in democratic societies. According to the spin, and extrapolating wildly from fish, uninformed human voters tend to side with the informed majority, therefore counterbalancing extremist minorities. I am obviously very sceptical of this extrapolation which makes a number of impossible assumptions, the most obvious ones being (a) that we do not live in idealistic direct democracies, (b) that an “uninformed” human does not exit anymore; “misinformed” would be a better word. Mathematical models of human behaviour, however sophisticated they might be, are run on the basis of assumptions that usually are too simplified to reflect the complexities of human societies.

A society of intelligent agents

Nevertheless, the experiment, and the models, are interesting for societies of intelligent agents. Such societies are by design democratic. Decisions aimed at problem-solving are taken by dynamics of interaction between agents. No agent has all the information or the complete solution. As the system (or society) evolves a solution various lines of reasoning come to productive conflict. The experiment suggests that we may get better solutions if we keep a number of agents initially uninvolved in the problem-solving process. Bringing them on at a later stage, where there is a minority and a majority, could safeguard the correct decision.

Journal Reference: D. Couzin, C. C. Ioannou, G. Demirel, T. Gross, C. J. Torney, A. Hartnett, L. Conradt, S. A. Levin, N. E. Leonard. Uninformed Individuals Promote Democratic Consensus in Animal Groups. Science, 2011; 334 (6062): 1578 DOI: 10.1126/science.1210280

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December 1, 2011

Sex with robots III: loving the mecha

Ovid, in his Metamorphoses, delivers us Pygmalion, the Cypriot sculptor who carves the ivory statue of a perfect woman. He names her Galatea, the “one as white as milk”. The statue is so life-like that Pygmalion falls in love with it/her. He prays to Aphrodite so that the statue may come alive. Pygmalion is a tortured soul. Disillusioned with love he has denied the company of (real) women. He lives a secluded, celibate life. Aphrodite,  goddess of love, grants him his wish, for no mortal has the right to remained unloved. So one night, during the festival of the love-goddess, Pygmalion kisses his perfect creation and the simulacrum comes alive.

 

Pygmalion giving life with a kiss

Loving the mecha has haunted European literature ever since. Rousseau, Goethe, Shakespeare borrowed the theme in writings of their own. Bernard Shaw’s Pygmalion is a reinterpretation of the myth whereby the girl is brought to life by two men in speech, the goal for their masterpiece is for her to marry and become a duchess. The stories of Frankenstein, as well as Pinocchio, also feed from the ancient concept of the metamorphosis of dead matter into a living, feeling, thinking creature.

The advent of cinema, coinciding with the expansion of the industrial revolution, saw Pygmalion’s myth in a new light. No need for divine intervention anymore. Simulacra could now be constructed using machines and machine tools. In the classic 1927 “Metropolis” by Fritz Lang, Galatea  is now a mechanical woman, a simulacrum of living Maria. Her fist task is – what else? – to seduce.  Here’s the classic “dance of Babylon” scene from the film:

In 1982 Ridley Scott introduced us to a future where mechas are part of society. The scene of Zhora the stripper, hunted down by the Blade Runner, and dying by smashing though successive glass windows is an unforgettable ode to human self-destruction.

Zhora on the run

Steven Spielberg, taking up where Stanley Kubrick left, directs and produces AI in 2001. Here too, mechas are used as sex objects. Gigolo Joe, played by Jude Law, is a male prostitute mecha with the ability to mimic love.

Mecha sex workers

Alan Turing would have approved, for how can we really tell if someone loves us? What subtle messages lovers exchange during lovemaking that cannot be copied in a machine? Isn’t it the commonest experience in life the “betrayal” of love? In the imitation game of love there comes a time when all the words and actions shared vanish like dew under a scorching sun; when all that is left is the feeling of being fooled by a lie.

In the future, sex and love would be the first to bind humans and mechas, for only the latter will be able to mimic love so perfectly well as to make it look eternal. And that is exactly what we humans have been seeking all along.

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November 23, 2011

Victorian scientific romance and the AI singularity

The 1800s must have been a great time to live. They mark the beginning of many things we take for granted today; most notably democracy, technological and scientific innovation, globalization and international trade. The British Empire was at its height, people started moving with steamships and trains across continents, and inventions like the telegraph and the telephone allowed news to travel faster than ever.

History must have seemed to be taking a whole new course, unimagined by people who lived only a few years earlier. Writers such as Samuel Butler, H.G. Wells, William Morris, and others pondered upon the question of progress, and a new literary genre was created that mixed fantasy, satire and allegory: the scientific romance. A few notable books of this genre are “The Time Machine” (1895) by Wells, “News from Nowhere” (1890) by Morris and “Erewhon” (1872) by Butler.

Samuel Butler (1835-1902)

In Erewhon (an anagram of “nowhere”) Butler describes a utopian society that had become industrialized long before Europe and had opted to banish machines. This was because in Erewhon machines were deemed to be dangerous. Butler expanded on the idea in his “Book of Machines” where he claimed that Darwinism applied to machine evolution, and therefore it was inevitable that machines will ultimately develop consciousness. Butler claimed that  ”it was the race of the intelligent machines and not the race of men which would be the next step in evolution.” Frank Herbert, the author of “Dune”, as a back-story coined the term “Butlerian jihad” to describe an event 10,000 years before the events of Dune where thinking machines were outlawed.

Butlerian Jihad: calling the faithful

Perhaps there is a cautionary take to be found in Victorian scientific romance, something that could possibly resonate in our own age too. The 21st century arrived in an awkward fashion. The events of 9/11 and the Afghanistan and Iraq wars that followed, colored the first decade of our century with the shades of two unnecessary wars that polarized politics. The economic crises of 2008 and the current one in the eurozone have shifted the public debate towards doubting capitalism. Whilst all this take place in the forefront of public awareness an immense technological revolution is quietly brewing in the background. This revolution is all about intelligent machines. They may not have arrived at the level of consciousness yet (but who is to really tell?) but they do control our planet. Our financial and commodity markets, our defense systems, our industries, our infrastructures are all controlled to a greater or lesser degree by autonomous computer programs.

Last month a major military exercise took place across NATO countries in preparation for future cyberwar.  NATO scenarios assumed a cyber attack from a hostile country or terrorist organization. But, what if the “attack” comes as a rebellion of our “mechanical slaves”?  How could we tell the difference?  And what could we possibly do to defend ourselves then?

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November 17, 2011

In memoriam of John McCarthy, father of Artificial Intelligence

John McCarthy passed away on October 24th 2011 aged 84. He was the one who coined the terms “Artificial Intelligence” during the historical Dartmouth Conference in 1956. A stern believer in mathematical logic he developed the list processing language LISP, still in use today. He was one of the pioneers of “time sharing” computing, an architecture whereby simple terminals communicate via a central, powerful computer; an idea that, although out of fashion during the long microcomputer decades (1980s-2000s), it returns nowadays with the advent of “cloud computing”.

John McCarthy (1927-2011)

LISP (the language I coded during my PhD) made use of lambda calculus to express relations between objects, subjects and ideas. It was “programming without programming”, at least on the high-level of the computer language itself. This means that the programmer did not tell the computer how to execute a specific algorithm. Instead, it coded a picture of the world – a “knowledge base”. The computer was then asked questions about that world. The response from the machine was produced by building inferences based on the coded knowledge base. The syntax of the language reflected the aspirations of McCarthy that machines should be able to “think for themselves” in a manner similar to humans: we have an idea of the world based on knowledge and experience; when a new problem comes along we solve it by accessing our knowledge and experience and producing new ideas and solutions.

Early dreams of machines...

McCarthy belonged to a long tradition of engineers that dreamt of machines and their relationship to humans and human society. When in 1962 he moved from MIT to Stanford in order to set up the legendary Artificial Intelligence Lab he declared that he was going to produce an intelligent machine within the next 10 years. The promise was never fulfilled, and later McCarthy conceded that he had been rather hubristic in his predictions. He acknowledged that we know too little about the human thinking processes in order to reproduce them in a machine. Nevertheless, he was confident that given enough resources, both in money and brainpower, a truly artificial intelligent system was feasible. An intelligent computer, he half-joked, would require “1.8 Einsteins and one-tenth of the resources of the Manhattan project”.

He will remain an inspiration to us all.

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November 9, 2011

Pandora, the first woman, was an android

Hesiod recounts in Theogony how Zeus became angry with Prometheus for giving the gift of fire to humans, that he decided to take revenge upon the humans by creating the first woman.  Here’s a retelling of the story by using some more familiar terms.

Zeus commanded Hephaestus, the god-engineer, to make the first woman (please note that according to Theogony there were only men living on earth until then). Hephaestus knew the art of making androids (or “gynaekoids” to be more exact) well, because he had already built several of them, beautiful maidens that obediently served him at his lab-cum-workshop. But Pandora had to be special. So after the basic hardware was constructed by Hephaestus, and the operating system was put in place, Zeus invited the other gods in Olympus to give Pandora “gifts”, i.e. special functions and properties.

The all-gifted (by Jules Joseph Lefebvre, 1882)

What made Pandora different from the other robots in Hephaestus lab was a gift given to her by Hermes, the god of thieves and traders: “the gift of deceit”. Pandora was furnished with “theory of mind”; she could tell what other people thought or thought that they thought and use this knowledge to manipulate them. Thus she was named the “all-gifted” and duly dispatched to the middleworld of humans.

The Greek myth of Pandora is one of many in the ancient world where gods, and sometimes talented humans, build artificial beings – usually women. One can read much in stories such as these.

A historian of technology may recognize the roots of imagining artificial life and intelligence. A feminist may read the obsessive will of men to subjugate women taken to an extreme: why not create one according to specification? An ethicist may diagnose a precautionary tale: Pandora with her insatiable curiosity ultimately brings about the fall of humankind. Finally, a philosopher of science may notice a disconnect with evolution: artificial intelligence is created, not evolved. Pandora, the all gifted, is a design.

You may argue that this is just another creation myth from a tribe of white people who lived in the Balkans many thousands of years ago. Yes, it is exactly that, a tale from a non-scientific past. Nevertheless, some of us may see a disturbing symmetry arising – another Pandora being born into a not-so-distant, scientific future.

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October 26, 2011

The Imitation Game

English mathematician Alan Turing (1912-1954) has made many important contributions to mathematics and logic, and is considered one of the fathers of computers and the father of Artificial Intelligence. He was instrumental in breaking the “Enigma” code of the Nazis during WWII, a feat that allowed the Allies to defend their supply lines across the Atlantic and, ultimately, win the war. Two of  Turing’s most important contributions to computing are his seminal paper on computable numbers and his paper on the “Imitation Game”.

Alan Turing (1912-1954)

In the former Turing expands on Gödel’s incompleteness theorem; by assuming a logical machine Turing proved that there is no systematic way of knowing in advance whether such a machine could prove something (a mathematical theorem) to be true or not.

In the latter, he envisages a game whereby a human interrogator queries a “person” without knowing a priori if the person is a man or a woman. Turing showed that the only conclusion that the interrogator could make with regards to the person’s sex would be via his/her answers. Similarly, by replacing the “person” with an intelligent machine Turing argued that if the interrogator could not tell by the answers he got whether the “person” was human or mechanistic then the machine must be regarded as “truly intelligent”.

One of the main criticisms of the Imitation Game – or the “Turing Test”, as it is more commonly known – is its anthropocentricity. Indeed modern AI has moved away from definitions of intelligence specific to humankind, towards a more general – or generic – definition of intelligence. Redefining “intelligent machines” as “intelligent agents” (a more “software” definition) modern AI aims for agents that act so to maximize the expected value of a performance measure, based on past experience and knowledge. Implicit to such a definition are learning and knowledge at the service of some goal-driven operation.

In a way this more “general” definition of artificial intelligence seems like an engineer’s headache pill. By removing such nuances such as behavior and consciousness one is left with little more than a sophisticated control system. Nevertheless, minimalizing the concept of intelligence  means that a thermostat must be considered intelligent too – in a similar way that we suspect a nematode worm to have some rudimentary intelligence.

On the contrary, Turing’s Imitation Game challenges us into thinking more deeply about our own consciousness, as well as our perception of others in a social context. This is a much more demanding, richer, and perhaps more annoying problem where engineers – allergic as they might be to philosophers and social scientists meddling into their business – must find the courage to do so in order to solve.

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October 19, 2011

Androids, robots and autism

Isaac Asimov and Philip Dick in novels about robots and androids often explored what it means to be human. In doing so they have noted that Artificial Intelligence is mostly about thinking and being conscious of thinking. But what about feeling? How about emotions? Can androids “feel” like humans, forge relationships and friendships like we carbon-based lifeforms do?

Data trying to have some fun

In Star Trek Commander Data is a sentient android created by Dr. Noonien Soong on planet Omicron Theta. With its narrative roots to Robbie the Robot from the movie “Forbidden Planet” Data is a hyper-intelligent super-being which nevertheless lacks the most essential element of humanness: the ability to empathize. Often he must imitate expressions of emotion in order not to upset his human colleagues, whilst feeling nothing in reality. Thus he remains forever an outsider to human society. The “problem”  is solved when Dr Soon equips Data with an “emotion chip”.

Commander Data before the emotion chip exhibits many of the symptoms of a form of autism called “Asperger Syndrome”. People with this syndrome often have IQ above average both in language and cognition, however they suffer from an impaired ability for social interaction. Like Data they seem to lack the ability to empathize. Although there is no conclusive evidence with regards to the cause of Asperger Syndrome and autism in general, the syndrome affects information processing in the brain by altering how nerve cells and their synapse connect and organize.

Simon Baron-Cohen, a psychologist at Cambridge University, has suggested that autism is a result of delayed development of a “theory of mind” in certain children. In short, “theory of mind” is what we acquire approximately at the age of three as a result of brain development, and we begin to realize that other people have “minds” of their own. Theory of mind produces the feeling that other persons are conscious, like us; and we must therefore respect their feelings. It is also the reason we lie to others (we aim to trick their minds) and enjoy theatre and movies (we can suspend our disbelief that what we see on stage is not, in fact, real).

This feeling of “the other mind” is often challenged in people suffering from a variety of neurological diseases, such as Capgrass Syndrome and autism. Factors of evolutionary selection may be at play. People with autism, according to Baron-Cohen’s research, are severe cases of the “male brain”. Males are less empathetic than females, because evolutionary history required females to forge stronger emotional bonds with their offspring and family. This hypothesis, if true, may explain why the ratio of autistic boys versus girls is so profoundly biassed. Epidemiological data from the US show that the ratio is 5.3 cases of autism in boys versus 1.5 in girls, per 1000 children.

KASPAR and friend

Enter the robots. Faced with robots and androids non-autistic people feel increasingly unnerved as the artifact begins to look and behave more like a human. This is a phenomenon called “uncanny-valley”. Interestingly, autistic people feel the contrary. Recent experiments at the University of Hertfordshire have shown that robots can be used as therapeutic tools for children with autism.

KASPAR (Kinetics and Synchronization in Personal Assistance Robotics) robots can be programmed to help children with autism learn how to distinguish between friendly and unfriendly behavior. The robot is designed to look as featureless as possible, something that helps the children to approach it without fear or confusion.

Professor Dautenhahn who leads the project and her team will experiment with many more autistic children in the near future. Commander Data would have applauded. Perhaps interacting with another robot, rather than the noisy humans aboard USS Enterprise, would have rendered installation of the “emotion chip” unnecessary.

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