Abstract
In response to the growing recognition of the social, legal, and ethical impacts of new AI-based technologies, major AI and ML conferences and journals now encourage or require submitted papers to include ethics impact statements and undergo ethics reviews. This move has sparked heated debate concerning the role of ethics in AI and data science research, at times devolving into counter-productive name-calling and threats of "cancellation." We argue that greater focus on the moral education of data scientists may help bridge the ideological divide separating the data science community. We diagnose this deep ideological conflict as one between atomists and holists. Among other things, atomists espouse the idea that facts are and should be kept separate from values, while holists believe facts and values are and should be inextricable from one another. With the goals of encouraging civil discourse across disciplines and reducing disciplinary polarization, we draw on a variety of historical sources ranging from philosophy and law, to social theory and humanistic psychology, to describe each ideology's beliefs and assumptions. Finally, we call on atomists and holists within the data science community to exhibit greater empathy during ethical disagreements and propose four targeted strategies to ensure data science research benefits society.
Abstract (translated)
URL
https://arxiv.org/abs/2208.09174
