The responsibility challenge for data

As data science and artificial intelligence become ubiquitous, they have an increasing impact on society. While many of these impacts are beneficial, others may not be. So understanding and managing these impacts is required of every responsible data scientist. Nevertheless, most human decision-makers use algorithms for efficiency purposes and not to make a better (i.e., fairer) decisions. Even the task of risk assessment in the criminal justice system enables efficiency instead of (and often at the expense of) fairness. So we need to frame the problem with fairness, and other societal impacts, as primary objectives.