  Scholars and industry practitioners have debated how to best develop
interventions for ethical artificial intelligence (AI). Such interventions
recommend that companies building and using AI tools change their technical
practices, but fail to wrangle with critical questions about the organizational
and institutional context in which AI is developed. In this paper, we
contribute descriptive research around the life of "AI" as a discursive concept
and organizational practice in an understudied sphere--emerging AI
startups--and with a focus on extra-organizational pressures faced by
entrepreneurs. Leveraging a theoretical lens for how organizations change, we
conducted semi-structured interviews with 23 entrepreneurs working at
early-stage AI startups. We find that actors within startups both conform to
and resist institutional pressures. Our analysis identifies a central tension
for AI entrepreneurs: they often valued scientific integrity and methodological
rigor; however, influential external stakeholders either lacked the technical
knowledge to appreciate entrepreneurs' emphasis on rigor or were more focused
on business priorities. As a result, entrepreneurs adopted hyped marketing
messages about AI that diverged from their scientific values, but attempted to
preserve their legitimacy internally. Institutional pressures and
organizational constraints also influenced entrepreneurs' modeling practices
and their response to actual or impending regulation. We conclude with a
discussion for how such pressures could be used as leverage for effective
interventions towards building ethical AI.
