The Managerial Effects of Algorithmic Fairness Activism

TL;DR

This study examines how different ethical arguments in AI fairness activism influence business decision-makers' adoption of AI, revealing that emphasizing bias inevitability discourages AI use and increases negative expectations, regardless of AI's fairness benefits.

Contribution

It provides experimental evidence on how ethical framing in AI fairness debates impacts managerial decisions and perceptions, highlighting the power of argument framing in AI ethics.

Findings

Bias inevitability arguments reduce AI adoption and increase negative expectations.

Status quo emphasis has opposite effects, encouraging AI use.

Scientific veneer influences managerial behavior without favoring positive activism.

Abstract

How do ethical arguments affect AI adoption in business? We randomly expose business decision-makers to arguments used in AI fairness activism. Arguments emphasizing the inescapability of algorithmic bias lead managers to abandon AI for manual review by humans and report greater expectations about lawsuits and negative PR. These effects persist even when AI lowers gender and racial disparities and when engineering investments to address AI fairness are feasible. Emphasis on status quo comparisons yields opposite effects. We also measure the effects of "scientific veneer" in AI ethics arguments. Scientific veneer changes managerial behavior but does not asymmetrically benefit favorable (versus critical) AI activism.