Threatened by AI: Analyzing Users’ Responses to the Introduction of AI in a Crowd-Sourcing Platform

Mikhail Lysyakov () and Siva Viswanathan ()
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Mikhail Lysyakov: Simon School of Business, University of Rochester, Rochester, New York 14620
Siva Viswanathan: Robert H. Smith School of Business, University of Maryland, College Park, Maryland 20742

Information Systems Research, 2023, vol. 34, issue 3, 1191-1210

Abstract: As artificial intelligence (AI) solutions are being rapidly deployed, they increasingly compete with human labor. This study examines designers’ strategies in response to the threat from the introduction of an AI system for simple logo designs in a crowdsourcing design platform. We study designers who were active both before and after the introduction of the AI system to understand their responses to the threat from AI. Our study is informed by the theories of threat, specifically the protection motivation theory that posits that individuals will respond to threats based on their capabilities. We find that, although some designers who had primarily participated in contests for lower-tier, simple logo designs leave the platform, others continue to participate in these contests. Interestingly, designers who have higher capabilities, evidenced by their prior participation in more-complex higher-tier logo-design contests and contests in other nonlogo categories, move away from the primary locus of threat in the lower-tier and switch to the more-complex contests after the introduction of the AI system. More interestingly, we find that successful designers respond differently from unsuccessful designers on the platform. Although unsuccessful designers increase participation across multiple contests, they do not change the quality (emotional content and complexity) of their design submissions after the AI launch. In contrast, successful designers become more focused (i.e., they substantially increase the number of submissions within a contest) and more quality oriented (i.e., they increase emotional content and complexity of their design submissions) after the AI launch. These findings have important implications for the nascent research on the impacts of AI on users in a crowdsourcing platform and for the design of such platforms.

Keywords: artificial intelligence; crowdsourcing; users’ strategies; image analytics; PMT; threat of AI (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (1)

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