Diversity and Inclusion in Artificial Intelligence

TL;DR

This paper defines diversity and inclusion within AI, offering practical guidelines for embedding these principles into AI systems and ecosystems to promote fairness and representation.

Contribution

It provides a clear definition and conceptual framework for diversity and inclusion in AI, along with actionable guidelines for practitioners.

Findings

A comprehensive definition of diversity and inclusion in AI

Practical guidelines for AI technologists and data scientists

Framework to embed inclusion in AI ecosystems

Abstract

To date, there has been little concrete practical advice about how to ensure that diversity and inclusion considerations should be embedded within both specific Artificial Intelligence (AI) systems and the larger global AI ecosystem. In this chapter, we present a clear definition of diversity and inclusion in AI, one which positions this concept within an evolving and holistic ecosystem. We use this definition and conceptual framing to present a set of practical guidelines primarily aimed at AI technologists, data scientists and project leaders.