Robots are hard, too

Friday’s Wall Street Journal included a book review of Almost Human: Making Robots Think,a new book by Lee Gutkind that’s a portrait of the work at Carnegie Mellon’s Robotics Institute.

That work, it seems, has its frustrations, and — as the reviewer, George Anders, tells it — the difficulties sound eerily like those recounted in Dreaming in Code’s description of the things that make software hard:

Mr. Gutkind’s second big insight involves Carnegie-Mellon’s approach to project management. It’s awful. Goals aren’t defined. Interim deadlines aren’t met. Crucial subsystems turn out to be incompatible. People rely on all-nighters to get everything finished. Such bad habits invite catastrophic blunders by exhausted people whose last-minute “fixes” snarl everything else.

In the most maddening breakdown of all, the scientists devising research projects seldom communicate well with the engineers trying to build them. Even the word “target” becomes a sore spot. To scientists, it means their working hypothesis. To engineers, it means the robot’s physical destination. Unaware of this gap, supposed colleagues get mired in confusing conversations.

Gutkind’s book is now on my “must read” list. One final irony to me, coming out of Dreaming in Code, is that Carnegie Mellon is not only home to Gutkind’s roboticists; it also harbors the Software Engineering Institute, which is ground zero for the CMM, CMMI, TSP and other acronymic attempts to add a framework of engineering rigor around the maddeningly difficult enterprise of producing new software. I might be jumping the gun (not having read Gutkind’s book yet), but it sounds like those roboticists and the SEI people should have lunch some time.