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Motivating transparent communications about bias in healthcare technology development

Abstract:

As healthcare artificial intelligence (AI) systems advance, their capacity for bias (e.g., as a function of patient protected characteristics) increases as well, and these limitations are often left undisclosed by developers. Here, the question arises - does supportive motivational messaging designed to increase buy-in inspire healthcare AI developers to transparently communicate about bias in their technology? Computer science students (Study 1: N=271; Study 2: N=209) were randomly assigned to receive a brief communication framed in either an autonomy-supportive (choice promoting) or controlling (judging and pressuring) way, emphasizing either personal benefits (gaining profit) of transparency or legal implications of non-transparency. Results showed that while communication type was not associated with behavioral intention to engage in an educational course on transparent communication about bias, both internal (self-directed) and external motivation were associated with greater intention to take a course to build transparency-congruent technology skills, as well as with greater ethical voice - intention to speak up in the service of positive transparency-consistent cultural change, and lower antagonism – i.e., a lower critical perspective regarding the need for transparency. Findings suggest that universities and workplaces should provide students and developers with a broadly supportive motivational climate, rather than a singular brief training.

Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1525/collabra.136456

Authors

More by this author
Institution:
University of Oxford
Division:
SSD
Department:
Oxford Internet Institute
Role:
Author
More by this author
Institution:
University of Oxford
Division:
SSD
Department:
Oxford Internet Institute
Role:
Author
ORCID:
0000-0003-3800-0113
More by this author
Institution:
University of Oxford
Division:
SSD
Department:
Oxford Internet Institute
Role:
Author
ORCID:
0000-0002-4709-6404
More by this author
Institution:
University of Oxford
Division:
SSD
Department:
Oxford Internet Institute
Role:
Author


More from this funder
Funder identifier:
https://ror.org/052csg198
Grant:
G-2021-16779


Publisher:
University of California Press
Journal:
Collabra: Psychology More from this journal
Volume:
11
Issue:
1
Article number:
136456
Publication date:
2025-05-06
Acceptance date:
2025-02-28
DOI:
EISSN:
2474-7394


Language:
English
Keywords:
Pubs id:
2101718
Local pid:
pubs:2101718
Deposit date:
2025-04-01
ARK identifier:

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