The University of Southampton
University of Southampton Institutional Repository

Putting AI ethics to work: are the tools fit for purpose for SMEs?

Putting AI ethics to work: are the tools fit for purpose for SMEs?
Putting AI ethics to work: are the tools fit for purpose for SMEs?
Bias, unfairness and lack of transparency and accountability in Artificial Intelligence (AI) systems have raised concerns about the ethical impact, and unintended consequences of new technologies for society across every sector where data-driven innovation is taking place. This thesis first reviews the landscape of proposed ethical frameworks with a focus on those which go beyond high-level statements of principles and offer practical tools. It then provides an assessment of these practical ethics tools through the lens of known best practices for impact assessment and audit of technology. It reviews other historical uses of risk assessments and audits to create a typology that allows us to compare current AI ethics tools to best practice found in previous methodologies from technology, environment, privacy, finance, and engineering. It analyses current AI ethics tools and their support for diverse stakeholders and components of the AI development and deployment lifecycle. Building on this analysis, a series of interviews were conducted with CEO’s/founders of smaller tech companies to understand how these tools might be used (or not) in the production of real products and services. This uncovers a narrower conception of ethical concerns and stakeholders in the sector than presented in AI ethics tools and principles. The sector also understands itself as already taking the necessary steps to address ethical issues without the need for specific ethical tools or governance. From this, gaps are identified in current AI ethics tools and their practical application that should be considered going forward.
University of Southampton
Ayling, Jacqueline, Anne
11c61a24-f8dc-4539-b8c4-c9edcd090111
Ayling, Jacqueline, Anne
11c61a24-f8dc-4539-b8c4-c9edcd090111

Ayling, Jacqueline, Anne (2021) Putting AI ethics to work: are the tools fit for purpose for SMEs? University of Southampton, Doctoral Thesis, 139pp.

Record type: Thesis (Doctoral)

Abstract

Bias, unfairness and lack of transparency and accountability in Artificial Intelligence (AI) systems have raised concerns about the ethical impact, and unintended consequences of new technologies for society across every sector where data-driven innovation is taking place. This thesis first reviews the landscape of proposed ethical frameworks with a focus on those which go beyond high-level statements of principles and offer practical tools. It then provides an assessment of these practical ethics tools through the lens of known best practices for impact assessment and audit of technology. It reviews other historical uses of risk assessments and audits to create a typology that allows us to compare current AI ethics tools to best practice found in previous methodologies from technology, environment, privacy, finance, and engineering. It analyses current AI ethics tools and their support for diverse stakeholders and components of the AI development and deployment lifecycle. Building on this analysis, a series of interviews were conducted with CEO’s/founders of smaller tech companies to understand how these tools might be used (or not) in the production of real products and services. This uncovers a narrower conception of ethical concerns and stakeholders in the sector than presented in AI ethics tools and principles. The sector also understands itself as already taking the necessary steps to address ethical issues without the need for specific ethical tools or governance. From this, gaps are identified in current AI ethics tools and their practical application that should be considered going forward.

Text
J Ayling 29004926 Corrected Thesis 6 April 2022 (1) - Version of Record
Available under License University of Southampton Thesis Licence.
Download (2MB)
Text
Permission to deposit thesis - APC
Restricted to Repository staff only
Available under License University of Southampton Thesis Licence.

More information

Submitted date: December 2021

Identifiers

Local EPrints ID: 457628
URI: http://eprints.soton.ac.uk/id/eprint/457628
PURE UUID: 4bd17213-7544-41e4-87d5-a5f3a9bc4b16

Catalogue record

Date deposited: 14 Jun 2022 16:45
Last modified: 16 Mar 2024 17:56

Export record

Contributors

Author: Jacqueline, Anne Ayling

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×