Ethics and society review: Ethics reflection as a precondition to research funding

Michael S. Bernstein, Margaret Levi, David Magnus, Betsy A. Rajala, Debra Satz and Charla Waeiss
Additional contact information
Michael S. Bernstein: a Department of Computer Science, Stanford University, Stanford, CA 94305;
Margaret Levi: b Center for Advanced Study in the Behavioral Sciences, Stanford University, Stanford, CA, 94305;; c Department of Political Science, Stanford University, Stanford, CA 94305;
David Magnus: d Department of Pediatrics, Stanford University, Stanford, CA 94305;
Betsy A. Rajala: b Center for Advanced Study in the Behavioral Sciences, Stanford University, Stanford, CA, 94305;
Debra Satz: e Department of Philosophy, Stanford University, Stanford, CA 94305
Charla Waeiss: b Center for Advanced Study in the Behavioral Sciences, Stanford University, Stanford, CA, 94305;

Proceedings of the National Academy of Sciences, 2021, vol. 118, issue 52, -

Abstract: Research fields that hold transformative possibilities for improving the human condition also raise risks of negative ethical and societal outcomes. These ethical and societal risks fall outside the purview of most research reviews. We introduce an iterative review process that draws these fields into reflection and mitigation of ethical and societal risks by conditioning access to grant funding on completion of the process. A 1-y evaluation of our approach with an artificial intelligence funding program at our university suggests that this approach is well-received by researchers and positively influenced the design of their research. This process has also generated lists of common risks and mitigation strategies, to provide scaffolding for future processes.

Keywords: ethics; machine learning; computer science; societal consequences (search for similar items in EconPapers)
Date: 2021
References: Add references at CitEc
Citations:

Downloads: (external link)
http://dx.doi.org/10.1073/pnas.2117261118 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nas:journl:v:118:y:2021:p:e2117261118

Access Statistics for this article

More articles in Proceedings of the National Academy of Sciences from Proceedings of the National Academy of Sciences
Bibliographic data for series maintained by PNAS Product Team ().