The World in 2030
The World in 2030 The World in 2030
The World in 2030 81 because intelligent machines will help with their own science and engineering. And the knowledge gap that has been shrinking over the centuries will start to grow. Not in the sense that scientific knowledge will shrink, but in the sense that people will have less understanding of their world because of their intimate relationship with a mind beyond their comprehension. We will understand the machine’s mind about as much as our pets understand ours. We will fill this knowledge gap with religion, giving the intelligent machine the role of god. 157 In his 2007 book ‘Beyond AI: Creating the Conscience of the Machine’, Dr J. Storrs Hall, 158 Research Fellow of the Institute for Molecular Manufacturing in Palo Alto, California, describes the abilities of an artificial intelligence of what he calls an ‘epihuman’ (just above human level) of intelligence: My model for what an epihuman AI would be like is to take the ten smartest people you know, remove their egos, and duplicate them a hundred times, so that you have a thousand really bright people willing to apply themselves all to the same project. Alternatively, simply imagine a very bright person given a thousand times as long to do any given task. We can straightforwardly predict, from Moore’s law, that ten years after the advent of a learning but not radically self-improving human-level AI, the same software running on machinery of the same cost would do
82 The World in 2030 the same human-level tasks a thousand times as fast as we. It could, for example: – read an average book in one second with full comprehension; – take a college course and do all the homework and research in ten minutes; – write a book, again with ample research, in two or three hours; – produce the equivalent of a human’s lifetime intellectual output, complete with all the learning, growth, and experience involved, in a couple of weeks. 159 Perhaps the last word on super-intelligent machines should go to Irving John Good 160 (one of the British World War II cryptographers who worked alongside Alan Turing), author of the 1965 paper, ‘Speculations Concerning the First Ultraintelligent Machine’: Thus the first ultraintelligent machine is the last invention that man need ever make. 161 Nanotechnology The term ‘nanotechnology’ 162 is simple to define (the control of matter on a scale smaller than 1 micrometer, normally between 1-100 nanometers) but the types of science and technology being developed at this sub-microscopic level vary greatly.
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<strong>The</strong> <strong>World</strong> <strong>in</strong> <strong>2030</strong> 81<br />
because <strong>in</strong>telligent mach<strong>in</strong>es will help with their own<br />
science and eng<strong>in</strong>eer<strong>in</strong>g.<br />
And the knowledge gap that has been shr<strong>in</strong>k<strong>in</strong>g over<br />
the centuries will start to grow. Not <strong>in</strong> the sense that<br />
scientific knowledge will shr<strong>in</strong>k, but <strong>in</strong> the sense that<br />
people will have less understand<strong>in</strong>g of their world<br />
because of their <strong>in</strong>timate relationship with a m<strong>in</strong>d<br />
beyond their comprehension. We will understand<br />
the mach<strong>in</strong>e’s m<strong>in</strong>d about as much as our pets<br />
understand ours. We will fill this knowledge gap<br />
with religion, giv<strong>in</strong>g the <strong>in</strong>telligent mach<strong>in</strong>e the role<br />
of god. 157<br />
In his 2007 book ‘Beyond AI: Creat<strong>in</strong>g the Conscience<br />
of the Mach<strong>in</strong>e’, Dr J. Storrs Hall, 158 Research Fellow of<br />
the Institute for Molecular Manufactur<strong>in</strong>g <strong>in</strong> Palo Alto,<br />
California, describes the abilities of an artificial <strong>in</strong>telligence<br />
of what he calls an ‘epihuman’ (just above human level) of<br />
<strong>in</strong>telligence:<br />
My model for what an epihuman AI would be like<br />
is to take the ten smartest people you know, remove<br />
their egos, and duplicate them a hundred times, so<br />
that you have a thousand really bright people will<strong>in</strong>g<br />
to apply themselves all to the same project. Alternatively,<br />
simply imag<strong>in</strong>e a very bright person given a<br />
thousand times as long to do any given task. We can<br />
straightforwardly predict, from Moore’s law, that ten<br />
years after the advent of a learn<strong>in</strong>g but not radically<br />
self-improv<strong>in</strong>g human-level AI, the same software<br />
runn<strong>in</strong>g on mach<strong>in</strong>ery of the same cost would do