Cars, AI and … Derrida?
Super-interesting essay on intelligent cars, AI, insurance (!), Google’s preference for humans over machines and lots of other things from Steve G. Steinberg, whose blog seems to take the “quality over quantity” concept to a new level. There are about five posts there in the last three years, and most of them are great. Make sure to read “group think“, a 2008 piece about reality mining and quantitative social science, or “human terrain mapping” as the post itself calls it. Anyway … back to the recent AI piece. Some choice quotes:
But, fortuitously, the hype over the electrical car is providing covering fire for a true revolution: the computational car. […] Already, more than a dozen 2010 car-year models offer intelligent safety features such as lane departure warning and adaptive cruise control. Crucially, they do not just flash a light or sound a buzzer when a problem is detected: they autonomously apply the brakes or adjust the steering. The driver is no longer the fail-safe that ensures the machine is running correctly. The driver is a problem to work around. The driver, you might say, is a bug.
And in reference to the concept of LbR (“learning by reading”):
Earlier, I described how an LbR system “knows everything — every single fact, the entirety of human knowledge — but can only reason with the intelligence of a cockroach.” You might argue this is hardly revolutionary: you have friends, even colleagues, who fit this description. The difference, of course, is LbR systems won’t just act like they know everything… they really will.
The most striking claim in the article, though, is buried in one of the last footnotes:
Anyone who lived through the Science Wars of the 1990s, when physicists and English professors engaged in pitched battle over the nature of objectivity, the meaning of (post)modernism, and the drawing of academic borders, will be amused to learn it is no longer unusual for computer scientists to cite works by Barthes, Derrida, and Foucault. Once dismissed as impenetrable, pernicious nonsense, their books are now simply instructional. (A strong rebuttal, to my mind, of the current conventional wisdom that lit crit must become more “scientific” to survive.)