Good systems: Ethical AI for CSCW

Kenneth R. Fleischmann, Sherri R. Greenberg, Danna Gurari, Abigale Stangl, Nitin Verma, Jaxsen R. Day, Rachel N. Simons, Tom Yeh

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Scopus citations


Artificial intelligence is revolutionizing work, including what it means for cooperative work to be supported by computers. The increased use of AI in CSCW can lead to many advantages, including increased productivity and efficiency, but it can also include several potential ethical trade-offs, such as invasions of privacy, loss of autonomy, and job displacement. This workshop will explore the ethical dimensions of AI in CSCW, building on Good Systems, a UT Grand Challenge. Specifically, the first half of the workshop will focus on the need to design AI to work for all users and to avoid bias through the use of universal design as well as the need for AI and CSCW researchers to interact with policy and legal experts to work together to ensure that AI will be developed in an ethical manner with sufficient consideration of its societal implications, and also that AI will be regulated and legislated in ways that will maximize its benefits to all people.

Original languageEnglish
Title of host publicationCSCW 2019 Companion - Conference Companion Publication of the 2019 Computer Supported Cooperative Work and Social Computing
PublisherAssociation for Computing Machinery
Number of pages7
ISBN (Electronic)9781450366922
StatePublished - 9 Nov 2019
Event22nd ACM Conference on Computer-Supported Cooperative Work and Social Computing, CSCW 2019 - Austin, United States
Duration: 9 Nov 201913 Nov 2019

Publication series

NameProceedings of the ACM Conference on Computer Supported Cooperative Work, CSCW


Conference22nd ACM Conference on Computer-Supported Cooperative Work and Social Computing, CSCW 2019
Country/TerritoryUnited States

Bibliographical note

Publisher Copyright:
© 2019 Copyright is held by the author/owner(s).


  • Artificial intelligence
  • Automation
  • Ethics
  • Human values
  • Machine learning
  • Policy
  • Universal design
  • Work


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