GigSense
An LLM-Infused Tool for Workers’ Collective Intelligence
DOI:
https://doi.org/10.47756/aihc.y9i1.159Keywords:
Human- centered computing, Human computer interaction (HCI), Interactive systems and tools, LLM, Empirical studies in collaborative and social computingAbstract
Collective intelligence among gig workers yields considerable ad- vantages, including improved information exchange, deeper social bonds, and stronger advocacy for better labor conditions. Especially as it enables workers to collaboratively pinpoint shared challenges and devise optimal strategies for addressing these issues. However, enabling collective intelligence remains challenging, as existing tools often overestimate gig workers’ available time and uniformity in analytical reasoning. To overcome this, we introduce GigSense, a tool that leverages large language models alongside theories of collective intelligence and sensemaking. GigSense enables gig workers to rapidly understand and address shared challenges effectively, irrespective of their diverse backgrounds. GigSense not only empowers gig workers but also opens new possibilities for supporting workers more broadly, demonstrating the potential of large language model interfaces to enhance collective intelligence efforts in the evolving workplace.
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