Distinguishing two features of accountability for AI technologies

Porter, Zoe, Zimmermann, Annette, Morgan, Phillip David James orcid.org/0000-0002-8797-4216 et al. (3 more authors) (2022) Distinguishing two features of accountability for AI technologies. Nature Machine Intelligence. pp. 734-736. ISSN: 2522-5839

Metadata

Item Type: Article
Authors/Creators:
Copyright, Publisher and Additional Information:

This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy. Further copying may not be permitted; contact the publisher for details
Dates:
  • Accepted: 19 August 2022
  • Published: 22 September 2022
Institution: The University of York
Academic Units: The University of York > Faculty of Sciences (York) > Computer Science (York)
The University of York > Faculty of Social Sciences (York) > The York Law School
Funding Information:
Funder
Grant number
EPSRC
EP/W011239/1
Depositing User: Pure (York)
Date Deposited: 28 Sep 2022 17:20
Last Modified: 20 Sep 2025 01:52
Published Version: https://doi.org/10.1038/s42256-022-00533-0
Status: Published
Refereed: Yes
Identification Number: 10.1038/s42256-022-00533-0
Open Archives Initiative ID (OAI ID):

Download

Accepted Version

Filename: Distinguishing_two_features_of_accountability_for_AI_technologies_Nature_Machine_Intelligence_.pdf

Description: Distinguishing two features of accountability for AI technologies (Nature Machine Intelligence)

CLICK TO DOWNLOAD [thumbnail of Distinguishing two features of accountability for AI technologies (Nature Machine Intelligence)]

Export

Statistics


CORE (COnnecting REpositories)