Both people and their algorithms make mistakes. Algorithms make mistakes differently, however. They tend to make and repeat the same mistakes at scale! Individual’s mistakes tend to differ slightly from each other, and their effects are often limited. To scale their impact, individuals must combine their efforts and errors. If we’re unlucky, collaboration collapses into group think. If we’re lucky, however, different mistakes cancel each other out, and successes accumulate—a consequence of the fact that there are more ways to fail than succeed. This is the world we know, a world of “protective randomness.” Take a random walk through history, exploring why we fear a particular version of the “AI” unknown. Learn from Lincoln’s attempt to square the circle. Simulate the unknown using chance. Evaluate whether it can ever be logical to prefer random noisy processes over low-noise alternatives. Consider, e.g., the random assignment of judges. Then struggle with what this all means for legal educators in the here and now.

Opening Remarks:

Keynote: