Watson: Pathfinder for Global Business?

Abstract

When discussing artificial intelligence, Dr. Ray Kurzweil often projects a future where thinking machines have become so proficient at imitating the cognitive processes of humans, they do each of those functions better than humans, by every measure. Many believe, perhaps under the influence of recent screenplays and novels, that this rule-changing transformation could bring dire consequences for an increasingly vulnerable human race at the mercy of a superior but soulless machine intelligence. However, what this rather dramatic scenario ignores is that the highly dynamic force driving the development of this “machine intelligence” is the creative and adaptive spark of human intelligence, which has a much longer track record than that of machines and has shown the ability to reinvent itself whenever circumstances call for it. This observation in no way minimizes the significant gains that have been made in artificial intelligence (AI). It only raises the consideration that human intelligence is a moving target, as well, and that humans might be learning as much about how to think from teaching machines as they are teaching “our new masters.” As an illustration of this viewpoint, I offer Watson, IBM’s recent celebrity supercomputer, who bested humanity’s top contestants earlier this year in the rather narrow arena of Jeopardy, a decades-old U.S. television game show that tests broad-based knowledge of what has usually been called cultural trivia—aka “insignificant or inessential matters.” This game show format involves quick retrieval and expression of facts across a wide range of subjects. Accordingly, competitive advantage requires quick location of the information needed, assessment of that information, and presentation in a specified format (as a “What is...?” question). The underlying competence required is not subtle, and not particularly taxing to a suitably prepared human savant. In IBM’s case, success was achieved by using many thousands of algorithms running simultaneously to maximize the speed and breadth of the search process. Human Jeopardy competitors often find achieving success at the above task quite challenging, and long-term definitive winners have been few. As many already know, Watson’s victory in this 2011 contest was quite decisive—but getting the machine to that level of skill (95% accuracy, at response speeds of under four seconds) was no small task for IBM. Five years earlier, when the project was first launched, the computer’s accuracy rates hovered around 15%, and response times were close to two hours, versus four seconds for the top human competitors. While the victory of IBM’s Deep Blue computer over reigning chess grandmaster Garry Kasparov in 1997 was a significant accomplishment, Kasparov contended afterwards that he saw intuitive play in the machine’s game that suggested a guiding outside intelligence. That question was never definitively settled, but it is clear that the winning chess computer in 1997 had twice the computation speed of its predecessor machine, which lost to the same opponent just one year before. Watson: Pathfinder for Global Business?