More recently, some programs competing in computer challenges have come close to fooling one-third of interrogators, as required in a restricted form of Turing Test, in which a program must be indistinguishable from a human in its ability to hold a text-based conversation. During the recent contest organised at the Royal Society in London, more than 30 per cent of judges were deceived by the Eugene Goostman chatbot. As discussed last week in Science, few scientists believe that Goostman displayed the sort of “intelligence” that British computer pioneer Alan Turing had in mind. In its original incarnation, Turing’s test was intended to be a way of determining whether a computer was displaying signs of a new breed of machine intelligence, known as artificial intelligence, or AI. (The computer HAL 9000, depicted in Stanley Kubrick and Arthur C. Clarke’s 1968 film 2001: A Space Odyssey, was one of the first fictional machines to pass the test.) One reason why AI has proved to be so controversial and elusive is that the concept of intelligence is hard to define. Even a working definition is difficult to construct. All the same, let’s say intelligence, in the broadest sense of the word, refers to the ability to perceive and to understand meaning. “Intelligence is about external performance,” says Australian National University philosopher David Chalmers. “In a sense, it’s about sophisticated behaviour.”

Based on this definition, might computers be anywhere near achieving an artificial version of such intelligence? “Probably not,” replies Sydney University computational linguist James Curran, who directs the National Computer Science School. The Turing Test, he reminds, was a thought experiment – performed just by thinking about it – which Turing proposed to avoid the question of what it means to be intelligent. “His idea was basically to say that, if enough people think you’re intelligent, you are intelligent,” Dr Curran notes. Another way to judge whether or not a chatbot is intelligent is to follow a conversation, such as one that took place between Goostman and Scott Aaronson from the Massachusetts Institute of Technology in the US. “Goostman avoided answering most of the questions – so he might make a good politician but not a human,” Dr Curran quips. Dr Curran is not alone: most experts doubt that a program will pass a so-called full Turing Test for some time yet. And if it did – would that mean the machine had demonstrated “intelligence” of some sort? Such questions have been the source of philosophical debate since the 1950s.

Many researchers now feel the test is of little value as a measure of intelligence. “That’s because human beings are too ready to attribute intelligence to things that don’t have it: dolls, puppets, constellations of stars, and so on,” reflects Murdoch University roboticist Graham Mann. “Human psychology is a sucker for things that appear to talk and this means that the test, as normally understood, is much too weak,” Dr Mann explains. Take over? The issue of artificial intelligence begs the question of whether silicon might someday supplant carbon-based life forms. At least one respected international journal, Cognitive Processing, has agonised over this. American philosopher Daniel Dennett sums up the feelings of some scientists when suggesting that humans are immensely complex and able computational machines. Brute force computing power, he reckons, might eventually mimic the human mind.

Other computer experts, however, dismiss the idea of AI as silicon pie in the sky. Intelligence, they argue, is special – and involves more than very fast, very extensive digital information processing. What else might it involve? Dr Mann, for one, believes that something missing from our current conception of intelligence – and which greatly disadvantages efforts to create intelligent behaviour in machines – is that we regard the brain as a box of processes that takes inputs in the form of sensors, or senses, and produces outputs in the form of actuators, or muscles. “This comes from the way we traditionally conceive of computers; you input information, do calculations on it and get some output,” Dr Mann points out. Natural intelligence, too, depends on sensory inputs and outputs, he adds. “But it has something else: another dimension of processing that manages the personal agenda of a living system.” This other system, he explains, ministers to physiological needs including hunger, thirst, self-protection and reproduction. “It is deeply connected with emotions, which are nature’s solution to controlling behaviour without complete information or rational processing that evolved much later in humans,” Dr Mann says.

At a rational level, the “other system” manages a person’s many, sometimes conflicting, goals. “A person’s needs and ambitions matter to them and are intimately mixed up with their cognition – in a way that’s almost never present in today’s AI designs,” he explains. “When we start to design intelligent systems to include motives and the emotional signalling that accompanies them – and to use these as a reference standard against which perceived events and objects can be sorted, evaluated and organised – we’ll have made a major step towards achieving true machine intelligence.” Evolution “Intelligence can be identified with specific cognitive functions,” says Monash University computer scientist Kevin Korb. “This is suggested by the fact that it’s a product of evolution – and evolution through natural selection selects for functional characteristics.” Another alternative, Associate Professor Korb explains, is that scientists use hugely improved nano-recordings of the brain and put them through some huge data mining and modelling processes to build a brain emulator.

“In that case, we’d have an artificial human brain – but it would have as much understanding of its brain as we do of ours, in other words, rather little. So, it would be in no special position to improve itself, and no Technological Singularity would be imminent, even though the machine would be intelligent.” Super-software When IBM supercomputer “Deep Blue” defeated Gary Kasparov in 1997, the then reigning world chess champion declared “quantity had become quality”. What he meant was that, even though differences between Deep Blue and earlier chess computers were related to the computer’s speed, a new kind of artificial intelligence had somehow emerged. “It is likely that part of what we recognise as natural intelligence in animals, including humans, is based on the speed of mental computing operations,” says Kristinn Thorisson, director of the Icelandic Institute for Intelligent Machines at Reykjavik University.

As computers get faster and more powerful, Associate Professor Thorisson says, they will start resembling machines that “think”. New designs and computer architectures would require the development of super-software systems. In addition to neural networks, which take their inspiration from biology in trying to mimic the way the brain works, and genetic algorithms, which mimic the process of evolution in the natural world, the software might include as-yet-uninvented methods. Computer scientists at Reykjavik University, for instance, are refining programs and languages that share common ground with self-evolving biological systems. “Natural intelligence, as observed in humans and animals, is the result of multiple systems and subsystems, implementing a complex pattern of information flow and controlled interaction,” Professor Thorisson says. How can complex interactions produce a thinking mind? “This question is basically an architectural one: how the system operates as a whole,” he explains. “Without a deep understanding of architecture, we will never understand intuition, attention, insight, or understand understanding itself.”

Caution If and when it does arrive, a general form of artificial intelligence may be dangerous, either in itself or in the hands of certain people, warns Oxford University computer scientist Stuart Armstrong. “It may be able to work a thousand times faster than humans, and to copy itself millions of times and thus operate as a huge group, all within minutes,” Professor Armstrong explains. “It might even improve its own intelligence or develop new technologies that give it great wealth and power. In this situation, we have to ensure that the AI is safe – since great power and good motivations are very distinct things.” Prize Every year, the Loebner Prize in artificial intelligence is awarded to a lucky chatbot considered by a panel of four judges to be the most human-like. The contest involves administering a version of the Turing Test.

Is this year’s Loebner Prize, due to be announced in November, likely to go to Goostman’s creators, Russian-born Vladimir Veselov and Ukrainian-born Eugene Demchenko? “The Loebner Prize has a different set of competition rules, and the interaction time between judges and the contestants – which could be a human or a chatbot – has varied each year over the past few years,” says RMIT computer scientist Xiaodong Li. In the 2010 competition, for instance, the interaction time was 25 minutes. “Such a lengthy conversation may affect Goostman’s performance,” Associate Professor Li points out. Professor Armstrong’s guess is that Goostman will not win the much-coveted prize. “This latest success has been well publicised, so the whole ‘persona’ trick – with the chatbot being a young kid with limited English language skills – may be useless,” he says. “Without that, Goostman has little chance.” Dr Mann, on the other hand, is more upbeat. Goostman may win the Loebner, he suggests: “But only if it competes according to the rules – which have a tendency to change from year to year. I met Hugh Loebner once, and he certainly won’t be giving away his big prize too easily!”

Topics Whether Goostman, or another chatbot, wins the prize depends on the topics the judges discuss, says Dr Curran. “There are a lot of pre-programmed – rather than learnt – areas of conversation and avoidance strategies in these chatbots. If the judges ask questions that suit this pre-programming, then any system could be more convincing.” By way of comparison, Dr Curran’s department at Sydney University has a system that sends out an automatic welcome email when a student enrols. “Some students reply, saying hello or thank you,” he explains. “In some sense, those people have been fooled into believing our system is human – but it is clearly not intelligent at all.” Apple’s intelligent iPhone assistant, Siri, has several amusing responses programmed by its developers. For instance, to the question “Siri, will you marry me?” it has said “You should know you’re not the only one who’s asked”. “Does this mean Siri itself is funny – or that its developers are funny?” Dr Curran asks. Links

Read Dr Mann’s research papers at: http://aai.murdoch.edu.au/publications/index.php?action=showcategory&by=author&pub=Graham%20A.%20Mann Try your hand at the $100,000 Loebner Prize at: www.loebner.net/Prizef/loebner-prize.html Read the conversation between Goostman and Scott Aaronson at: www.scottaaronson.com/blog/?p=1858 VCAA link Science VCE study page: www.vcaa.vic.edu.au/Pages/vce/studies/envscience/envscindex.aspx

Please send bright ideas for new topics to pspinks@fairfaxmedia.com.au