Human–AI Collaboration in Agricultural E-commerce Live Streaming: A Task Allocation Framework
DOI:
https://doi.org/10.54097/k5rw8x04Keywords:
Agricultural livestream e-commerce; generative AI; AI streamers; human–AI collaboration; task allocation.Abstract
Agricultural e-commerce live streaming requires sellers to provide timely and accurate product information while using live demonstrations and interaction to address questions about quality, origin, and after-sales responsibility. Generative AI can help organize information, draft scripts, and answer routine questions, but it cannot independently resolve every issue that calls for on-site verification or an accountable response. Taking specific tasks before, during, and after a livestream as the unit of analysis, this conceptual paper develops a two-dimensional framework based on task codifiability and demands for trust and accountability. Their intersection distinguishes four types of work: tasks that AI can perform independently, tasks for which AI provides support, tasks requiring joint human–AI execution, and tasks led by a human streamer. In practice, these tasks are organized into three operating arrangements: AI-led, collaborative, and human-led live streaming. The framework offers a basis for analyzing how work may be divided between AI and human streamers in agricultural commerce. Its practical value remains to be tested in actual livestream settings.
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