Paper Number
2066
Paper Type
Short
Abstract
Given the transformative potential of generative artificial intelligence (GenAI) for completing creative tasks on crowdsourcing platforms, we aim to examine whether the disclosure of GenAI usage in gigs affects sellers’ popularity on supply-driven crowdsourcing platforms, an area where empirical understanding remains limited. In this context, a 'gig' refers to a specific task or service sellers offer on these platforms. We focus on four types of creative gigs: text, audio, image, and video. Moreover, most previous research has focused on the impact of textual cues on sellers’ popularity on these crowdsourcing platforms, and there is a lack of understanding of the connection between textual cues and visual cues. To address these gaps, we plan to conduct a quasi-experiment and a lab experiment to explore how textual and visual cues in gigs influence the popularity of sellers on crowdsourcing platforms across different gig types.
Recommended Citation
Zhu, Zimeng and Hsu, Carol, "Does the Disclosure of GenAI Usage in Gigs Affect Sellers’ Popularity on Supply-driven Crowdsourcing Platforms? The Role of Textual and Visual Cues" (2024). ICIS 2024 Proceedings. 10.
https://aisel.aisnet.org/icis2024/sharing_econ/sharing_econ/10
Does the Disclosure of GenAI Usage in Gigs Affect Sellers’ Popularity on Supply-driven Crowdsourcing Platforms? The Role of Textual and Visual Cues
Given the transformative potential of generative artificial intelligence (GenAI) for completing creative tasks on crowdsourcing platforms, we aim to examine whether the disclosure of GenAI usage in gigs affects sellers’ popularity on supply-driven crowdsourcing platforms, an area where empirical understanding remains limited. In this context, a 'gig' refers to a specific task or service sellers offer on these platforms. We focus on four types of creative gigs: text, audio, image, and video. Moreover, most previous research has focused on the impact of textual cues on sellers’ popularity on these crowdsourcing platforms, and there is a lack of understanding of the connection between textual cues and visual cues. To address these gaps, we plan to conduct a quasi-experiment and a lab experiment to explore how textual and visual cues in gigs influence the popularity of sellers on crowdsourcing platforms across different gig types.
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