ALGORISTS DREAM OF OBJECTIVITY Peter Galison Peter Galison is a science historian, Joseph Pellegrino University Professor and co- founder of the Black Hole Initiative at Harvard University, and the author of Einstein's Clocks and Poincaré’s Maps: Empires of Time. In his second-best book, the great medieval mathematician al-Khwarizmi described the new place-based Indian form of arithmetic. His name, soon sonically linked to “algorismus” (in late medieval Latin) came to designate procedures acting upon numbers—eventually wending its way through “algorithm,” (on the model of “logarithm”), into French and on into English. But I like the idea of a modern algorist, even if my spellcheck does not. I mean by it someone profoundly suspicious of the intervention of human judgment, someone who takes that judgment to violate the fundamental norms of what it is to be objective (and therefore scientific). Near the end of the 20th century, a paper by two University of Minnesota psychologists summarized a vast literature that had long roiled the waters of prediction. One side, they judged, had for all too long held resolutely—and ultimately unethically— to the “clinical method” of prediction, which prized all that was subjective: “informal,” “in-the-head,” and “impressionistic.” These clinicians were people (so said the psychologists) who thought they could study their subjects with meticulous care, gather in committees, and make judgment-based predictions about criminal recidivism, college success, medical outcomes, and the like. The other side, the psychologists continued, embodied everything the clinicians did not, embracing the objective: “formal,” “mechanical,” “algorithmic.” This the authors took to stand at the root of the whole triumph of post-Galilean science. Not only did science benefit from the actuarial; to a great extent, science was the mechanical-actuarial. Breezing through 136 studies of predictions, across domains from sentencing to psychiatry, the authors showe