Philosophy within Data Science Ethics Courses

TL;DR

This paper proposes a framework to integrate philosophical ethics with practical data science ethics education, encouraging deeper engagement with moral considerations in data science practices.

Contribution

It introduces a structured approach linking philosophical ethics literature to current data science ethics curricula, based on analysis of existing course materials.

Findings

Identified key ethics topics from sixteen data science courses.

Proposed a framework connecting philosophy and data science practices.

Encouraged integration of philosophical ethics into data science education.

Abstract

There is wide agreement that ethical considerations are a valuable aspect of a data science curriculum, and to that end, many data science programs offer courses in data science ethics. There are not always, however, explicit connections between data science ethics and the centuries-old work on ethics within the discipline of philosophy. Here, we present a framework for bringing together key data science practices with ethics topics. The ethics topics were collated from sixteen data science ethics courses with public-facing syllabi and reading lists. We encourage individuals who are teaching data science ethics to engage with the philosophical literature and its connection to current data science practices, which are rife with potentially morally charged decision points.