Thursday, July 14, 2005
Computer power and Asimov's robots
A recent study out of Cornell University has cast serious doubt on the idea that the brain works like a computer, and in fact questions whether computers will every be capable of true artificial intelligence at all. Computers are basically symbol processors, which carry out a sequence of logical operations on the symbols in lockstep. In common personal PCs everything is timed through a single CPU clock. There have been experiments with asynchronous CPUs (in which parts of the CPU run at different speeds by Sun, but these are still "state machines" processing discrete symbols in sequence.
In contrast, the Cornell study by Michael Spivey supports the notion that language comprehension (interesting because words are clearly symbols) does not happen in lockstep, but instead is a continuous process. To quote Spivey:
"For decades, the cognitive and neural sciences have treated mental processes as though they involved passing discrete packets of information in a strictly feed-forward fashion from one cognitive module to the next or in a string of individuated binary symbols -- like a digital computer," said Spivey. "More recently, however, a growing number of studies, such as ours, support dynamical-systems approaches to the mind. In this model, perception and cognition are mathematically described as a continuous trajectory through a high-dimensional mental space; the neural activation patterns flow back and forth to produce nonlinear, self-organized, emergent properties -- like a biological organism."
In the actual studies, students solving a variety of problems were shown to not be in a single computerlike "state" at any time - completely unlike a computer. Instead, students were in "multiple states" at all times. The relatively activity of each multiple state changed smoothly as a result of competition with other states.
Another quote:
"...Whereas the older models of language processing theorized that neural systems process words in a series of discrete stages, the alternative model suggests that sensory input is processed continuously so that even partial linguistic input can start "the dynamic competition between simultaneously active representations."
In other words, animals and humans simply don't process data the way a computer does. A computer processing words jumps to a particular state, tests the state, and jumps to a different state if it is incorrect. In contrast, brains apparently have all states present at once, and smoothly transition between on "state collection" and another.
If Spivey is correct, the implications are mind-blowing. No computer, no matter how fast it runs, could possibly simulate multiple states plus transitions. One might argue that if the computer is fast enough, it can 'time slice' so it appears that multiple states are present. But this is asking a car to be an airplane or a dog to walk on its hind legs - it ain't natural to the machine.
In short, the Cornell results tell us that the brain is NOT a computer!
This concept is hard to shake. For the last 50 years we have assumed that our minds are "computers made of meat" as MIT AI grandfather Marvin Minsky puts it. It is tempting to assume that somehow, we'll find a way to simulate brains on computers. The idea of computers as potentially intelligent is so engrained in our minds that we simply can't believe it - no HAL will ever exist, because a computer can NEVER be intelligent like a brain. Say it ain't so!
Before you sign off assuming that "they" will somehow figure out a workaround for this, consider the following:
1. Since 1950 computers have increased in speed 1 million times, but intelligent behavior has not ever been satisfactorily observed. Despite the hype, many, if not most robots don't do much more than the clockwork devices of a few hundred years ago. Sure, they can walk, but this is only a result of sensors. The lights are now on (due to sensors) but nobody is home.
If you don't believe this, ask yourself why your computer doesn't know a thing about you (including that you are sitting in front of it) and why "voice recognition systems" are no smarter than mouse/keyboard data entry.
2. Big Ai projects have largely come to naught. The most ambitious of these, Cyc (http://www.cyc.com) recently has been hooked up to "chat-bots" that operate on the Internet (see the Alice project). I'm sorry, but these programs are stupid beyond belief. In fact, I don't detect any more smarts in the chat-bots than I saw in ELIZA decades ago. Cyc itself is finding application in sorting through databases for phone companies and credit cards - labor-saving, but hardly what we think of as smart.
3. We often forget (in our fantasy that our "tech age" is different than any that came before) that the computer is just the latest in a long line of machines that were supposed to show how the brains work. If you're old enough, you may remember when textbooks compared the brain to the telephone network. SF writer Arthur C. Clarke even wrote a story where the phone system woke up and became intelligent. Before the phone system there was the steam engine, the loom, and even the vacuum pump. All are failed metaphors for the brain.
It is entirely possible that the brain is not a computer, any more than it is a phone network or vacuum pump. It is entirely possible that the brain is not a computer, and conversely, computers will never act like brains. In other words, "state machines" can never create a mind - or even come close.
Which brings me to Asimov. The Cornell study describes the mind as having multiple states which compete to become dominant in a constant fashion. This in fact is how Isaac Asimov original described the "positronic" brains of his robots. If you read the early robot stories from the 1940s and 1950s, Asimov said that computers were used to control the process of creating a robot brain - but that the robot brain was not a computer. Instead, the positronic brain juggled "potentials" which settled out into complex states. A complex math theory was used to calculate the change in potentials over time, strongly implying the positronic brain "computing" was actually similar to the "dynamic continuum" described by the Cornell study.
By the way, this is why the famous "Three Laws" of Asimov's stories could not be erased from a robot's mind simply by editing a line of software. The "three laws" were set up as a series of "dynamic potentials" according to Asimov that reinforced each other - sort of like a series of magnets holding each other in a complex spatial pattern, or an old-style analog (Moog) synthesizer) creating a particular musical tone through the adjustments of numerous electrical circuits. Remove one magnet at the bottom (mapped to law 2) and the whole potential structure would collapse.
This also explains why Asimov never describes software being loaded into his robots - instead their "programming" is mechanical channeling of an exotic "sponge metal" by positrons enabling the potentials. True, Asimov is imaging a microfabrication process akin to integrated circuits - but the result is not a state machine juggling symbols.
In our computer-saturated world, we no longer understand this - Asimov did not imagine that his robots were computers!
I suspect two things. Asimov was able to develop this biologically-inspired model for robot brains because computers hadn't advanced in the 1940s as much as they have today. Second, Spivey probably knows about the "positronic" stories, and might even be using their insight in his own research!
In his later robot stories written in the 1980s (e.g. "Robots and Empire") Asimov still differentiates between positronic brains and computers. Earth colonists (who hate robots) use computer-driven cars (like the DARPA Grand Challenge) and spaceships - but do not use robots. You can detect contamination of the original "positronic" idea in these late works - Asimov has characters say robot brains are "similar" to computers. But I suspect that the rising importance of computers in society during th 1980s made Asimov feel he was wrong, and feel computers might be the "way to go". He was covering for an apparent mistake, when he may have been right in his original idea.
What does this mean for robotics? It may be that even a "sensor dense" robot will not approach human or animal cognition - it will never understand enough to be the household maid people still dream of. Certainly, the iRobot people feel that special-purpose robots for vacuuming and scrubbing floors are practical. The Japanese are pushing humanoid robots, but to date they aren't doing anything of significance beyond not running into stuff (due to their sensors).
It may be that our civilization does not understand how to create intelligence. Future historians will look at our "computers as Ai" as a quaint idea as Descartes describing the mind as a series of water pumps similar to the clockwork humanoids that existed in his day.
But this is cool - it means there is something "beyond" computers that we haven't discovered yet!
A recent study out of Cornell University has cast serious doubt on the idea that the brain works like a computer, and in fact questions whether computers will every be capable of true artificial intelligence at all. Computers are basically symbol processors, which carry out a sequence of logical operations on the symbols in lockstep. In common personal PCs everything is timed through a single CPU clock. There have been experiments with asynchronous CPUs (in which parts of the CPU run at different speeds by Sun, but these are still "state machines" processing discrete symbols in sequence.
In contrast, the Cornell study by Michael Spivey supports the notion that language comprehension (interesting because words are clearly symbols) does not happen in lockstep, but instead is a continuous process. To quote Spivey:
"For decades, the cognitive and neural sciences have treated mental processes as though they involved passing discrete packets of information in a strictly feed-forward fashion from one cognitive module to the next or in a string of individuated binary symbols -- like a digital computer," said Spivey. "More recently, however, a growing number of studies, such as ours, support dynamical-systems approaches to the mind. In this model, perception and cognition are mathematically described as a continuous trajectory through a high-dimensional mental space; the neural activation patterns flow back and forth to produce nonlinear, self-organized, emergent properties -- like a biological organism."
In the actual studies, students solving a variety of problems were shown to not be in a single computerlike "state" at any time - completely unlike a computer. Instead, students were in "multiple states" at all times. The relatively activity of each multiple state changed smoothly as a result of competition with other states.
Another quote:
"...Whereas the older models of language processing theorized that neural systems process words in a series of discrete stages, the alternative model suggests that sensory input is processed continuously so that even partial linguistic input can start "the dynamic competition between simultaneously active representations."
In other words, animals and humans simply don't process data the way a computer does. A computer processing words jumps to a particular state, tests the state, and jumps to a different state if it is incorrect. In contrast, brains apparently have all states present at once, and smoothly transition between on "state collection" and another.
If Spivey is correct, the implications are mind-blowing. No computer, no matter how fast it runs, could possibly simulate multiple states plus transitions. One might argue that if the computer is fast enough, it can 'time slice' so it appears that multiple states are present. But this is asking a car to be an airplane or a dog to walk on its hind legs - it ain't natural to the machine.
In short, the Cornell results tell us that the brain is NOT a computer!
This concept is hard to shake. For the last 50 years we have assumed that our minds are "computers made of meat" as MIT AI grandfather Marvin Minsky puts it. It is tempting to assume that somehow, we'll find a way to simulate brains on computers. The idea of computers as potentially intelligent is so engrained in our minds that we simply can't believe it - no HAL will ever exist, because a computer can NEVER be intelligent like a brain. Say it ain't so!
Before you sign off assuming that "they" will somehow figure out a workaround for this, consider the following:
1. Since 1950 computers have increased in speed 1 million times, but intelligent behavior has not ever been satisfactorily observed. Despite the hype, many, if not most robots don't do much more than the clockwork devices of a few hundred years ago. Sure, they can walk, but this is only a result of sensors. The lights are now on (due to sensors) but nobody is home.
If you don't believe this, ask yourself why your computer doesn't know a thing about you (including that you are sitting in front of it) and why "voice recognition systems" are no smarter than mouse/keyboard data entry.
2. Big Ai projects have largely come to naught. The most ambitious of these, Cyc (http://www.cyc.com) recently has been hooked up to "chat-bots" that operate on the Internet (see the Alice project). I'm sorry, but these programs are stupid beyond belief. In fact, I don't detect any more smarts in the chat-bots than I saw in ELIZA decades ago. Cyc itself is finding application in sorting through databases for phone companies and credit cards - labor-saving, but hardly what we think of as smart.
3. We often forget (in our fantasy that our "tech age" is different than any that came before) that the computer is just the latest in a long line of machines that were supposed to show how the brains work. If you're old enough, you may remember when textbooks compared the brain to the telephone network. SF writer Arthur C. Clarke even wrote a story where the phone system woke up and became intelligent. Before the phone system there was the steam engine, the loom, and even the vacuum pump. All are failed metaphors for the brain.
It is entirely possible that the brain is not a computer, any more than it is a phone network or vacuum pump. It is entirely possible that the brain is not a computer, and conversely, computers will never act like brains. In other words, "state machines" can never create a mind - or even come close.
Which brings me to Asimov. The Cornell study describes the mind as having multiple states which compete to become dominant in a constant fashion. This in fact is how Isaac Asimov original described the "positronic" brains of his robots. If you read the early robot stories from the 1940s and 1950s, Asimov said that computers were used to control the process of creating a robot brain - but that the robot brain was not a computer. Instead, the positronic brain juggled "potentials" which settled out into complex states. A complex math theory was used to calculate the change in potentials over time, strongly implying the positronic brain "computing" was actually similar to the "dynamic continuum" described by the Cornell study.
By the way, this is why the famous "Three Laws" of Asimov's stories could not be erased from a robot's mind simply by editing a line of software. The "three laws" were set up as a series of "dynamic potentials" according to Asimov that reinforced each other - sort of like a series of magnets holding each other in a complex spatial pattern, or an old-style analog (Moog) synthesizer) creating a particular musical tone through the adjustments of numerous electrical circuits. Remove one magnet at the bottom (mapped to law 2) and the whole potential structure would collapse.
This also explains why Asimov never describes software being loaded into his robots - instead their "programming" is mechanical channeling of an exotic "sponge metal" by positrons enabling the potentials. True, Asimov is imaging a microfabrication process akin to integrated circuits - but the result is not a state machine juggling symbols.
In our computer-saturated world, we no longer understand this - Asimov did not imagine that his robots were computers!
I suspect two things. Asimov was able to develop this biologically-inspired model for robot brains because computers hadn't advanced in the 1940s as much as they have today. Second, Spivey probably knows about the "positronic" stories, and might even be using their insight in his own research!
In his later robot stories written in the 1980s (e.g. "Robots and Empire") Asimov still differentiates between positronic brains and computers. Earth colonists (who hate robots) use computer-driven cars (like the DARPA Grand Challenge) and spaceships - but do not use robots. You can detect contamination of the original "positronic" idea in these late works - Asimov has characters say robot brains are "similar" to computers. But I suspect that the rising importance of computers in society during th 1980s made Asimov feel he was wrong, and feel computers might be the "way to go". He was covering for an apparent mistake, when he may have been right in his original idea.
What does this mean for robotics? It may be that even a "sensor dense" robot will not approach human or animal cognition - it will never understand enough to be the household maid people still dream of. Certainly, the iRobot people feel that special-purpose robots for vacuuming and scrubbing floors are practical. The Japanese are pushing humanoid robots, but to date they aren't doing anything of significance beyond not running into stuff (due to their sensors).
It may be that our civilization does not understand how to create intelligence. Future historians will look at our "computers as Ai" as a quaint idea as Descartes describing the mind as a series of water pumps similar to the clockwork humanoids that existed in his day.
But this is cool - it means there is something "beyond" computers that we haven't discovered yet!
