Abstract

With the increasing adoption of automated algorithms in every part of our lives, greater attention has been dedicated to studying the societal effects of these algorithms. The first portion of the talk will highlight concepts covered in the machine learning fairness literature. The rest of the talk will explore how Big Tech can actively distort the ongoing “Ethics of AI” academic landscape to suit its needs. By comparing the well-studied actions of another industry, that of Big Tobacco, to the current actions of Big Tech we see similar strategies employed by both industries to sway and influence academic and public discourse. We argue that it is vital, particularly for universities and other institutions of higher learning, to discuss the appropriateness and the tradeoffs of accepting funding from Big Tech, and what limitations or conditions should be put in place.