Kerr, Aphra and Barry, Marguerite and Kelleher, John D.
(2020)
Expectations of Artificial Intelligence and the Performativity of Ethics: Implications for Communication Governance.
Big Data & Society, 7 (1).
ISSN 2053-9517
Abstract
his article draws on the sociology of expectations to examine the construction of expectations of ‘ethical AI’ and considers the implications of these expectations for communication governance. We first analyse a range of public documents to identify the key actors, mechanisms and issues which structure societal expectations around AI and an emerging discourse on ethics. We then explore expectations of AI and ethics through a survey of members of the public. Finally, we discuss the implications of our findings for the role of AI in communication governance. We find that, despite societal expectations that we can design ethical AI, and public expectations that developers and governments should share responsibility for the outcomes of AI use, there is a significant divergence between these expectations and the ways in which AI technologies are currently used and governed in large scale communication systems. We conclude that discourses of ‘ethical AI’ are generically performative, but to become more effective we need to acknowledge the limitations of contemporary AI and the requirement for extensive human labour to meet the challenges of communication governance. An effective ethics of AI requires domain appropriate AI tools, updated professional practices, dignified places of work and robust regulatory and accountability frameworks.
Item Type: |
Article
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Additional Information: |
ADAPT/SFI |
Keywords: |
ethics; expectations; STS; artificial intelligence; performativity; communication governance; |
Academic Unit: |
Faculty of Social Sciences > Sociology |
Item ID: |
12880 |
Identification Number: |
https://doi.org/10.1177/2053951720915939 |
Depositing User: |
Prof. Aphra Kerr
|
Date Deposited: |
11 May 2020 11:02 |
Journal or Publication Title: |
Big Data & Society |
Publisher: |
Sage Publications |
Refereed: |
Yes |
Funders: |
ADAPT/SFI |
URI: |
|
Use Licence: |
This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available
here |
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