Disdain for regulation is pervasive throughout the tech industry. In the case of automated decision making, this attitude is mistaken. Early engagement with governments and regulators could both smooth the path of adoption for systems built on machine learning, minimize the consequences of inevitable failures, increase public trust in these systems, and possibly avert the imposition of debilitating rules. Exponential growth in the sophistication and applications of machine learning is in the process of automating wholly or partially many tasks previously performed only by humans. This technology of automated decision making (ADM) promises many benefits, including reducing tedious labor as well as improving the appropriateness and acceptability of decisions and actions.