Physics of the Future: How Science Will Shape Human Destiny and Our Daily Lives by the Year 2100

example, autistic savants can perform miraculous feats of memorization and calculation. But they have difficulty tying their shoelaces, getting a job, or functioning in society. The late Kim Peek, who was so remarkable that the movie
Rain Man
was based on his extraordinary life, memorized every word in 12,000 books and could perform calculations that only a computer could check. Yet he had an IQ of 73, had difficultyholding a conversation, and needed constant help to survive. Without his father’s assistance, he was largely helpless. In other words, the superfast computers of the future will be like autistic savants, able to memorize vast amounts of information, but not much more, unable to survive in the real world on their own.
    Even if computers begin to match the computing speed of the brain, they will still lack the necessary software and programming to make everything work. Matching the computing speed of the brain is just the humble beginning.
    Third, even if intelligent robots are possible, it is not clear if a robot can make a copy of itself that is smarter than the original. The mathematics behind self-replicating robots was first developed by the mathematician John von Neumann, who invented game theory and helped to develop the electronic computer. He pioneered the question of determining the minimum number of assumptions before a machine could create a copy of itself. However, he never addressed the question of whether a robot can make a copy of itself that is smarter than it. In fact, the very definition of “smart” is problematic, since there is no universally accepted definition of “smart.”
    Certainly, a robot might be able to create a copy of itself with more memory and processing ability by simply upgrading and adding more chips. But does this mean the copy is smarter, or just faster? For example, an adding machine is millions of times faster than a human, with much more memory and processing speed, but it is certainly not smarter. So intelligence is more than just memory and speed.
    Fourth, although hardware may progress exponentially, software may not. While hardware has grown by the ability to etch smaller and smaller transistors onto a wafer, software is totally different; it requires a human to sit down with a pencil and paper and write code. That is the bottleneck: the human.
    Software, like all human creative activity, progresses in fits and starts, with brilliant insights and long stretches of drudgery and stagnation. Unlike simply etching more transistors onto silicon, which has grown like clockwork, software depends on the unpredictable nature of human creativity and whim. Therefore all predictions of a steady, exponential growth in computer power have to be qualified. A chain is no stronger than itsweakest link, and the weakest link is software and programming done by humans.
    Engineering progress often grows exponentially, especially when it is a simple matter of achieving greater efficiency, such as etching more and more transistors onto a silicon wafer. But when it comes to basic research, which requires luck, skill, and unexpected strokes of genius, progress is more like “punctuated equilibrium,” with long stretches of time when not much happens, with sudden breakthroughs that change the entire terrain. If we look at the history of basic research, from Newton to Einstein to the present day, we see that punctuated equilibrium more accurately describes the way in which progress is made.
    Fifth, as we have seen in the research for reverse engineering the brain, the staggering cost and sheer size of the project will probably delay it into the middle of this century. And then making sense of all this data may take many more decades, pushing the final reverse engineering of the brain to late in this century.
    Sixth, there probably won’t be a “big bang,” when machines suddenly become conscious. As before, if we define consciousness as including the ability to make plans for the future by running simulations of the future, then there is a spectrum of consciousness. Machines will slowly climb up this scale, giving us plenty of time to prepare. This will happen toward the end of this century, I believe, so there is ample time to discuss various options available to us. Also, consciousness in machines will probably have its own peculiarities. So a form of “silicon consciousness” rather than pure human consciousness will develop first.
    But this raises another question.