Computing Machinery and Intelligence: the imitation game

     In this artitical, Doctor Turning explored the question "Can machines think?" through a game called "imitation game". The game is played by three people, a man(A), a woman(B) ,and an interrogator(C).C is separated from A and B, its task is to tell who is A(the man) and who is B through asking questions and analyze the answers. A is supposed to trick C to make the wrong judgement(e.g, "I‘m wearing ear studs")and B is supposed to help C make the right judgement and avoid A's traps("Don't listen to him! he's lying!").But of course, since C does not who is A and who is B, so C can't really tell who's trying to trick it and who's helping it.(Turning provided more details and experimental conditions, I didn't list them all here).

   The purpose of this game is to see when facing such a condition(which means pure logic won't help very much here), how would a robot "think" and analyze the situation in order to get the right answer? Turning did not give any specific result on this imitation game, instead , he's just trying to materialize the way of "thinking" of a robot into a controllable experiment situation so people can have more ground to base when think over this kind of question.

   He also mentioned another situation, that is a robot who participates in the game  is supposed to trick its interrogator into believing  it's a human; while a human who also participates in this game, tries to trick the interrogator into believing that he/she is a robot.The result, however, is not very favourable to human. For example, when an interrogating question like"please multiply 34957 to 23457" is given, a robot can still pretend to be a human by pausing for a while, pretending that it is calculating on a piece of paper, or simply by answering:"I don't have a pencil and paper with me, I can't do this calculation" while a human would immediately get revealed since a robot is supposed to give out an answer in a split second,but a human just can't.

   Turning agrees that a robot might not do very well on test like"what do you think of Shakespeare?". They may give out some very limited and rigid answers. But Turning believes that "the criticism that a machine cannot have much diversity of behavior is just a way of saying that it cannot have much storage capacity.Until fairly recently a storage capacity of even a thousand digits was very rare." He agrees that the way a robot functions is certainly not the same as the nervous system; but "by observing the results fo its own behavior it can modify its own programs so as to achieve some purpose more effectively." So the ideas that one day people might not be able to differentiate a robot from a human in the imitation game or in other fields "are possibilities of the near future, rather than Utopian dreams."

(note: Turning has written a complete and detailed essay on this topic, the points I mentioned here is only part of his research.) 

Main source:

Turning, Alan Mathison. Ed.Luger, George F. Computation and Intelligence: Collected Readings. 

   Menlo Park/Cambridge/London/AAAI Press/ The MIT Press, 1995.

 

More on AI: Can we reach the technological singularity

Related Articles:

http://science.howstuffworks.com/robot-computer-conscious.htm

http://electronics.howstuffworks.com/gadgets/high-tech-gadgets/technological-singularity1.htm

http://ase.tufts.edu/cogstud/papers/concrobt.htm

       The term/notion "singularity"(in technological field) is coined by Vernor Vinge, a former professor of mathematics at the San Diego State University. His basic idea is that the technology is developing at such a dazzling speed,towards an irreversible destiny and one day we might merge together with our AI companies and evolve into a new species---or even worse,our AI companies might evolve into robots with self-awareness and decide that human beings are redundant or unwanted...Such a scenario has been accepted by many people and reflected in many novels and movies,and based on the theory that the data density of an integrated circuit could double every 18 months,this hypothesis is quite "reliable". 

       However,some engineers and scientists have questioned this hypothesis through the limit of circuitry itself. Till today, we can already build microprocessors with transistors that only 45-nanometers wide("a human hair can have a diameter of up to 180,000 nanometers"),but to continue with this trend and to make more and more delicate and complex circuitry(which means to make computer smaller, faster, more powerful, and finally achieve the capacity of human brain),we would soon get into the field of quantum physics, and then face the problem of quantum tunneling(which means "electrons can pass through extremely thin material as if the material weren't there " and we would lose control of them).From this point of view, the potential would have already" ran out" before a computer can achieve such complex capacity as "self-awareness".But they also admit, there are more than one way to build circuits and chips, and the potential technologies like optics and nanotechnology are also developing very fast.We are still uncertain about what could happen in the far future.

     

    

Rise of the Robots--The Future of Artificial Intelligence :How far is it?

Artical URL: http://www.scientificamerican.com/article.cfm?id=rise-of-the-robots

(I love this article! Very easy and clear and fit perfectly with my topic.Too bad  we are not going to discuss this on Discussion Board.)

       I've read many articles that explore the future and power of robot from  moral and ethic perspectives, but this one uses concrete data and scientific evidence to evaluate its future and potential; and allows people to have a very clear concept about how it is possible for the chip of a robot to achieve the power of a human brain('Can Hardware Simulate Wetware?'): 

   Level one: 10 MIPS(one million instructions per second) insectlike robot: would be able to track landmarks but can get confused very easily.

   Level two:100,000MIPS mouselike robot: Could be trainable; can improve their work by collecting and analyzing previous data.

   Level three: 5,000,000 MIPS monkeylike robot: can "learn a skill by imitation and afford a kind of consciousness"; can answer simple questions like "why there are candles on the table?"

   Level four: 100million MIPS humanlike robot: "will be able to abstract and generalize"

         However, there are still two problems here. First, the method he used to calculate the capacity of human brain and convert it into measurable unit like MIPS is questionable("The entire human brain is about 75,000 times heavier than the 0.02 gram of processing circuitry in the retina, which implies that it would take, in round numbers,100 million MIPS to emulate the 1,500-gram human brain."). This method works technologically, but in fact our brain's power is way much complexer than this and it can  vary greatly from person to person. For example, how do you decide which person has larger MIPS? Picasso or Kandinsky? Newton or Shakespear? J.K Rowling or Dan Brown? Human brain's diversity, creativity and uniqueness are simply immeasurable(I'm not saying this method is wrong, I'm just saying it's not precise and inclusive enough).
        The second problem is the optimistic attitude towards highly-intelligent humanlike robot: "In that case, mass-produced, fully educated robot scientists working diligently,cheaply,rapidly and increasingly effectively will ensure that most of what science knows in 2050 will have been discovered by our artificial progeny!"

However, there's a paradoxical situation here: if the robots are not as clever and 'conscious' as human being, then there's no obvious breakthrough in this field and most of the jobs still need to be done by ourself; if the robots are indeed as clever and 'conscious' as human being, are they still willing to serve us and obey us, instead of trying to enjoy their own 'life'?