Exceptional Intelligence

This morning I was reading an article about Larry Page’s evolution at Google and it made me reflect on the kinds of smarts that Google and others are embedding in the devices that surround us.

Whether it is Microsoft’s Clippy’s failed attempts at being helpful or Siri‘s inability to simple variations to queries that it otherwise would understand, most attempts at computational intelligence tend to work reasonably well within narrow domains and perform very badly outside of them. If the boundaries between expertise and incompetence are clear, the tools can be a joy to use. When the boundary is fuzzy, we become frustrated with the technology’s limits and often stop using it altogether. If you can ask about the weather in ten ways but Siri can only understand three, and you can’t easily remember which is the “right” way to ask about the weather…well, why not just go and tap on the weather app and get the right results 100% of the time?

This rigidity of expectations – only being able to handle inputs that fit within a narrow range – points to the true limitation of current “intelligent” technology. In everyday life we associate intelligence not with getting common things right but with graceful, creative handling of the exceptional. The handling of the exceptional, however, is where most approaches to artificial intelligence break down. This limitation influences the core design of virtually every computational artifact that we build. Learning how to transcend it is, I think, the core problem of computer science.