AI Fairness in Practice

123 Pages Posted: 18 Mar 2024

See all articles by David Leslie

David Leslie

The Alan Turing Institute

Cami Rincon

The Alan Turing Institute

Morgan Briggs

The Alan Turing Institute

Antonella Perini

The Alan Turing Institute

Smera Jayadeva

The Alan Turing Institute

Ann Borda

The Alan Turing Institute

SJ Bennett

The Alan Turing Institute

Christopher Burr

The Alan Turing Institute; University of Oxford - Oxford Internet Institute

Mhairi Aitken

The Alan Turing Institute

Michael Katell

The Alan Turing Institute Public Policy Programme

Claudia Fischer

The Alan Turing Institute

Janis Wong

The Alan Turing Institute

Ismael Kherroubi Garcia

Kairoi

Date Written: November 2, 2023

Abstract

Reaching consensus on a commonly accepted definition of AI Fairness has long been a central challenge in AI ethics and governance. There is a broad spectrum of views across society on what the concept of fairness means and how it should best be put to practice. In this workbook, we tackle this challenge by exploring how a context-based and society-centred approach to understanding AI Fairness can help project teams better identify, mitigate, and manage the many ways that unfair bias and discrimination can crop up across the AI project workflow.

We begin by exploring how, despite the plurality of understandings about the meaning of fairness, priorities of equality and non-discrimination have come to constitute the broadly accepted core of its application as a practical principle. We focus on how these priorities manifest in the form of equal protection from direct and indirect discrimination and from discriminatory harassment. These elements form ethical and legal criteria based upon which instances of unfair bias and discrimination can be identified and mitigated across the AI project workflow.

We then take a deeper dive into how the different contexts of the AI project lifecycle give rise to different fairness concerns. This allows us to identify several types of AI Fairness (Data Fairness, Application Fairness, Model Design and Development Fairness, Metric-Based Fairness, System Implementation Fairness, and Ecosystem Fairness) that form the basis of a multi-lens approach to bias identification, mitigation, and management. Building on this, we discuss how to put the principle of AI Fairness into practice across the AI project workflow through Bias Self-Assessment and Bias Risk Management as well as through the documentation of metric-based fairness criteria in a Fairness Position Statement.

Keywords: artificial intelligence, Model Design and Development, Data Fairness, AI Ethics, AI workflow, Bias Risk Management, Ecosystem Fairness, Application Fairness, AI Governance, AI Policy, AI systems, AI regulation, AI Fairness,

Suggested Citation

Leslie, David and Rincon, Cami and Briggs, Morgan and Perini, Antonella and Jayadeva, Smera and Borda, Ann and Bennett, SJ and Burr, Christopher and Burr, Christopher and Aitken, Mhairi and Katell, Michael and Fischer, Claudia and Wong, Janis and Kherroubi Garcia, Ismael, AI Fairness in Practice (November 2, 2023). Available at SSRN: https://ssrn.com/abstract=4731838 or http://dx.doi.org/10.2139/ssrn.4731838

David Leslie (Contact Author)

The Alan Turing Institute ( email )

British Library, 96 Euston Road
96 Euston Road
London, NW12DB
United Kingdom

HOME PAGE: http://https://www.turing.ac.uk/people/researchers/david-leslie

Cami Rincon

The Alan Turing Institute ( email )

British Library
96 Euston Road
London, NW1 2DB
United Kingdom

Morgan Briggs

The Alan Turing Institute ( email )

British Library
96 Euston Road
London, NW1 2DB
United Kingdom

Antonella Perini

The Alan Turing Institute ( email )

British Library, 96 Euston Road
96 Euston Road
London, NW12DB
United Kingdom

Smera Jayadeva

The Alan Turing Institute ( email )

British Library, 96 Euston Road
96 Euston Road
London, NW12DB
United Kingdom

Ann Borda

The Alan Turing Institute ( email )

British Library, 96 Euston Road
96 Euston Road
London, NW12DB
United Kingdom

SJ Bennett

The Alan Turing Institute ( email )

British Library, 96 Euston Road
96 Euston Road
London, NW12DB
United Kingdom

Christopher Burr

University of Oxford - Oxford Internet Institute ( email )

1 St. Giles
University of Oxford
Oxford OX1 3PG Oxfordshire, Oxfordshire OX1 3JS
United Kingdom

The Alan Turing Institute ( email )

British Library
96 Euston Road
London, NW1 2DB
United Kingdom

HOME PAGE: http://https://chrisdburr.com

Mhairi Aitken

The Alan Turing Institute ( email )

British Library
96 Euston Road
London, NW1 2DB
United Kingdom

Michael Katell

The Alan Turing Institute Public Policy Programme ( email )

British Library
96 Euston Road
London, NW1 2DB
United Kingdom

Claudia Fischer

The Alan Turing Institute ( email )

Janis Wong

The Alan Turing Institute ( email )

British Library, 96 Euston Road
96 Euston Road
London, NW12DB
United Kingdom

Ismael Kherroubi Garcia

Kairoi ( email )

71-75 Shelton Street
Covent Garden
London, WC2H 9JQ
United Kingdom

HOME PAGE: http://kairoi.uk

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