Reconfiguring Diversity and Inclusion for AI Ethics

TL;DR

This paper analyzes how major tech companies incorporate diversity and inclusion into AI ethics documentation, revealing a shift towards technical and managerial framing that distances from civil rights origins and broader DEI efforts.

Contribution

It provides an interpretive analysis of corporate AI ethics documents, highlighting how diversity and inclusion are reconfigured within engineering and managerial contexts.

Findings

Shift from civil rights to managerial framing of diversity

Focus on technical artifacts like datasets for inclusion

Responsibility for diversity and inclusion is shifted to customers

Abstract

Activists, journalists, and scholars have long raised critical questions about the relationship between diversity, representation, and structural exclusions in data-intensive tools and services. We build on work mapping the emergent landscape of corporate AI ethics to center one outcome of these conversations: the incorporation of diversity and inclusion in corporate AI ethics activities. Using interpretive document analysis and analytic tools from the values in design field, we examine how diversity and inclusion work is articulated in public-facing AI ethics documentation produced by three companies that create application and services layer AI infrastructure: Google, Microsoft, and Salesforce. We find that as these documents make diversity and inclusion more tractable to engineers and technical clients, they reveal a drift away from civil rights justifications that resonates with the managerialization of diversity by corporations in the mid-1980s. The focus on technical artifacts, such as diverse and inclusive datasets, and the replacement of equity with fairness make ethical work more actionable for everyday practitioners. Yet, they appear divorced from broader DEI initiatives and other subject matter experts that could provide needed context to nuanced decisions around how to operationalize these values. Finally, diversity and inclusion, as configured by engineering logic, positions firms not as ethics owners but as ethics allocators; while these companies claim expertise on AI ethics, the responsibility of defining who diversity and inclusion are meant to protect and where it is relevant is pushed downstream to their customers.