AI Ethics and Governance in Practice: AI Sustainability in Practice Part One: Foundations for Sustainable AI Projects

The second workbook in the AI Ethics and Governance in Practice Programme, describing concepts and tools needed to put AI Sustainability into practice.

Abstract

In 2021, the UK's National AI Strategy recommended that UK Government’s official Public Sector Guidance on AI Ethics and Safety be transformed into a series of practice-based workbooks. The result is the AI Ethics and Governance in Practice Programme. This series of eight workbooks provides end-to-end guidance on how to apply principles of AI ethics and safety to the design, development, deployment, and maintenance of AI systems. It provides public sector organisations with a Process Based Governance (PBG) Framework designed to assist AI project teams in ensuring that the AI technologies they build, procure, or use are ethical, safe, and responsible. 

This workbook is the first in a pair that provides the concepts and tools needed to put AI Sustainability into practice.  

Sustainable AI projects are continuously responsive to the transformative effects as well as short-, medium-, and long-term impacts on individuals and society that the design, development, and deployment of AI technologies may have. Projects which centre AI Sustainability ensure that  values-led, collaborative, and anticipatory reflection both guide the assessment of potential social and ethical impacts, and steer responsible innovation practices.  

This workbook introduces the SUM Values (Support, Underwrite, Motivate), a set of ethical values intended to help AI project teams to assess the potential societal impacts and ethical permissibility of their projects. It then presents a Stakeholder Engagement Process (SEP), which provides tools to facilitate proportionate engagement of and input from stakeholders with an emphasis on equitable and meaningful participation and positionality awareness.

You can download a summary of the workbook below, alongside the full workbook. 

Citation information

Leslie, D., Rincón, C., Briggs, M., Perini, A., Jayadeva, S., Borda, A., Bennett, SJ. Burr, C., Aitken, M., Katell, M., Fischer, Wong, J., and Kherroubi Garcia, I. (2023). AI Sustainability in Practice. Part One: Foundations for Sustainable AI Projects. The Alan Turing Institute. 

Turing affiliated authors

SJ Bennett

Research Associate, Data Justice and Global Ethical Futures

Dr Christopher Burr

Innovation and Impact Hub Lead (TRIC-DT), Senior Researcher in Trustworthy Systems (Tools, Practices and Systems)