The Role of Humanity into the Future

Yet again, IBM is creating AI to best humans in a task that has been, perhaps, a symbol of uniquely human activity: Jeopardy! The system, Watson, is doing quite well against the humans. The number of applications for this technology is nearly endless.

I’d wonder how this success will play into the broader discourse on the human intellect, and our view of ourselves on the universe. When Deep Blue defeated Kasparov, and the computer became (unofficially) the world chess champion, I remember having mixed feelings. We like our icons, I suppose, and hate to get rid of them. It’s like growing up, and losing Santa Claus, perhaps. The history of science has been to deflate human arrogance, and yet successes like Deep Blue and Watson are not quite the same because it is our own ingenuity which created them.

On some level, Watson feels like a different accomplishment than Deep Blue. Chess is deterministic, well formulated, and complex. It’s complexity is the only thing that challenges an easy computer solution, which was accomplished finally by brute force: get enough fast hardware attacking a well-described problem and you win….always. Watson isn’t nearly as well defined as chess, or at least it doesn’t appear to be as well defined.

Watching Watson, there is a creepy sort of feeling, probably due to too many evil AI movies (2001, Terminator, Matrix, etc…). Kids growing up today will have this sort of technology as the norm. All-in-all, an interesting series of events to keep watching!


About brianblais

I am a professor of Science and Technology at Bryant University in Smithfield, RI, and a research professor in the Institute for Brain and Neural Systems, Brown University. My research is in computational neuroscience and statistics. I teach physics, meteorology, astonomy, theoretical neuroscience, systems dynamics, artificial intelligence and robotics. My book, "Theory of Cortical Plasticity" (World Scientific, 2004), details a theory of learning and memory in the cortex, and presents the consequences and predictions of the theory. I am an avid python enthusiast, and a Bayesian (a la E. T. Jaynes), and love music.
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