Motivating transparent communications about bias in healthcare technology development
Tovmasyan, A.
It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing. To link to this item DOI: 10.1525/collabra.136456 Abstract/SummaryAs 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.
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