Conclusion: More Genius at Your Fingertips?
We can only see a short distance ahead, but we can see plenty there
that needs to be done.
—ALAN TURING, Computing Machinery and Intelligence, 1950
I was fortunate, in 1991, to attend a public lecture by the great theoretical physicist Stephen Hawking. During the lecture, which was boldly titled “The Future of the Universe,” Hawking confidently predicted that the universe would keep expanding for at least the next 10 billion years. He wryly added, “I don’t expect to be around to be proved wrong.” Unfortunately for me, predictions about computer science do not come with the same 10-billion-year insurance policy that is available to cosmologists. Any predictions I make may well be disproved during my own lifetime.
But that shouldn’t stop us thinking about the future of the great ideas of computer science. Will the great algorithms we’ve explored remain “great” forever? Will some become obsolete? Will new great algorithms emerge? To address these questions, we need to think less like a cosmologist and more like a historian. This brings to mind another experience I had many years ago, watching some televised lectures by the acclaimed, if controversial, Oxford historian A. J. P. Taylor. At the end of the lecture series, Taylor directly addressed the question of whether there would ever be a third world war. He thought the answer was yes, because humans would probably “behave in the future as they have done in the past.”
So let’s follow A. J. P. Taylor’s lead and bow to the broad sweep of history. The great algorithms described in this book arose from incidents and inventions sprinkled throughout the 20th century. It seems reasonable to assume a similar pace for the 21st century, with a major new set of algorithms coming to the fore every two or three decades. In some cases, these algorithms could be stunningly original, completely new techniques dreamed up by scientists. Public key