Strategies for Increasing Corporate Responsible AI Prioritization

TL;DR

This paper explores the motivations and strategies for increasing corporate prioritization of responsible AI through interviews, providing a structured overview of current landscape and potential directions for practitioners.

Contribution

It offers a structured analysis of motivators and strategies for corporate RAI prioritization based on practitioner interviews, highlighting key actors and promising approaches.

Findings

Identifies diverse motivators for RAI prioritization

Classifies available strategies and responsible actors

Suggests promising directions for future efforts

Abstract

Responsible artificial intelligence (RAI) is increasingly recognized as a critical concern. However, the level of corporate RAI prioritization has not kept pace. In this work, we conduct 16 semi-structured interviews with practitioners to investigate what has historically motivated companies to increase the prioritization of RAI. What emerges is a complex story of conflicting and varied factors, but we bring structure to the narrative by highlighting the different strategies available to employ, and point to the actors with access to each. While there are no guaranteed steps for increasing RAI prioritization, we paint the current landscape of motivators so that practitioners can learn from each other, and put forth our own selection of promising directions forward.