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Achieving a ‘Good AI Society’: Comparing the Aims and Progress of the EU and the US

Abstract:
Copyright . Over the past few years, there has been a proliferation of artificial intelligence (AI) strategies, released by governments around the world, that seek to maximise the benefits of AI and minimise potential harms. This article provides a comparative analysis of the European Union (EU) and the United States’ (US) AI strategies and considers (i) the visions of a ‘Good AI Society’ that are forwarded in key policy documents and their opportunity costs, (ii) the extent to which the implementation of each vision is living up to stated aims and (iii) the consequences that these differing visions of a ‘Good AI Society’ have for transatlantic cooperation. The article concludes by comparing the ethical desirability of each vision and identifies areas where the EU, and especially the US, need to improve in order to achieve ethical outcomes and deepen cooperation
Publication status:
Published
Peer review status:
Peer reviewed

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Files:
Publisher copy:
10.1007/s11948-021-00340-7
Publication website:
http://bura.brunel.ac.uk/bitstream/2438/27397/1/FullText.pdf

Authors

More by this author
Institution:
University of Oxford
Division:
SSD
Department:
Oxford Internet Institute
Role:
Author
ORCID:
0000-0002-9610-7245
More by this author
Institution:
University of Oxford
Division:
SSD
Department:
Oxford Internet Institute
Role:
Author
ORCID:
0000-0002-8545-5068
More by this author
Institution:
University of Oxford
Division:
SSD
Department:
Oxford Internet Institute
Role:
Author
ORCID:
0000-0002-5891-6324
More by this author
Institution:
University of Oxford
Division:
SSD
Department:
Oxford Internet Institute
Role:
Author
ORCID:
0000-0002-6423-9147
More by this author
Institution:
University of Oxford
Division:
SSD
Department:
Oxford Internet Institute
Role:
Author


Publisher:
Springer
Journal:
Science and Engineering Ethics More from this journal
Volume:
27
Issue:
6
Pages:
68-68
Article number:
68
Publication date:
2021-11-12
DOI:
EISSN:
1471-5546
ISSN:
1353-3452


Language:
English
Keywords:
Pubs id:
1185659
Local pid:
pubs:1185659
Source identifiers:
W3214175988
Deposit date:
2026-03-25
ARK identifier:
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