In this workshop, participants will learn how to:
(1) design and build processes for risk identification and mitigation in AI and data science;
(2) develop and deploy governance frameworks and standards to build organizational principles for responsible AI and data justice;
(3) deploy a practical set of tools for building responsible AI and data ethics culture within an organization;
(4) use design justice, data justice, and inclusive design practices to improve AI and data science in professional practice.
(5) conceptualize practical problems in philosophical-conceptual and ethical terms, and vice versa (e.g., the trolley problem);
(6) differentiate themselves from other job candidates skilled in algorithmic and data science by developing expertise in data ethics, data justice and AI governance practices;
(7) use various ethics and governance options available to recent graduates seeking a career in technology ethics;
(8) explain how data not only describes but increasingly produces social reality;
(9) provide a humanistic understanding of how STEM fields (including data science) both shape and impact contemporary social and political lifeworlds;
(10) articulate a greater sense of the meaning and purpose that can be cultivated in data-oriented work.


Justification / Rationale

While the products of STEM-oriented practices are becoming an increasingly dominant aspect of contemporary social life, university programs in STEM fields typically lack any ethics-based curriculum or training tailored to science, technology, engineering, or math. Where students are introduced to ethics-based curriculum, it is often delivered in a disciplinary context and thus divorced from their own interests and expertise. On the other hand, humanities and social science graduates seeking employment in STEM-oriented fields with increasing private-sector demand (e.g. data science) often express concern that in responding to the needs of the market, they are not leveraging their own expertise and insights.

This workshop will address these concerns by offering STEM PhDs a lexicon and set of skills that employers increasingly look for as a differentiating factor in top job candidates. It will offer humanities PhDs a way to bridge their training with the more practical data-oriented skills offered by Erdős programs and demanded by potential employers, while helping them to find meaning in a data-oriented profession.