insight. There can be no royal road to becoming Goethe. In scientific atlas after scientific atlas, one sees explicit argument that “subjective” factors had to be part of the scientific work needed to create, classify, and interpret scientific images. What we see in so many of the algorists’ claims is a tremendous desire to find scientific objectivity precisely by abandoning judgment and relying on mechanical procedures—in the name of scientific objectivity. Many American states have legislated the use of sentencing and parole algorithms. Better a machine, it is argued, than the vagaries of a judge’s judgment. So here is a warning from the sciences. Hands-off algorithmic proceduralism did indeed have its heyday in the 19th century, and of course still plays a role in many of the most successful technical and scientific endeavors. But the idea that mechanical objectivity, construed as binding self-restraint, follows a simple, monotonic curve increasing from the bad impressionistic clinician to the good externalized actuary simply does not answer to the more interesting and nuanced history of the sciences. There 1s a more important lesson from the sciences. Mechanical objectivity is a scientific virtue among others, and the hard sciences learned that lesson often. We must do the same in the legal and social scientific domains. What happens, for example, when the secret, proprietary algorithm sends one person to prison for ten years and another for five years, for the same crime? Rebecca Wexler, visiting fellow at the Yale Law School Information Society Project, has explored that question, and the tremendous cost that trade-secret algorithms impose on the possibility of a fair legal defense.*4 Indeed, for a variety of reasons, law enforcement may not want to share the algorithms used to make DNA, chemical, or fingerprint identifications, which puts the defense in a much weakened position to make its case. In the courtroom, objectivity, trade secrets, and judicial tr