2 research outputs found
ChoiceMates: Supporting Unfamiliar Online Decision-Making with Multi-Agent Conversational Interactions
Unfamiliar decisions -- decisions where people lack adequate domain knowledge
or expertise -- specifically increase the complexity and uncertainty of the
process of searching for, understanding, and making decisions with online
information. Through our formative study (n=14), we observed users' challenges
in accessing diverse perspectives, identifying relevant information, and
deciding the right moment to make the final decision. We present ChoiceMates, a
system that enables conversations with a dynamic set of LLM-powered agents for
a holistic domain understanding and efficient discovery and management of
information to make decisions. Agents, as opinionated personas, flexibly join
the conversation, not only providing responses but also conversing among
themselves to elicit each agent's preferences. Our between-subjects study
(n=36) comparing ChoiceMates to conventional web search and single-agent showed
that ChoiceMates was more helpful in discovering, diving deeper, and managing
information compared to Web with higher confidence. We also describe how
participants utilized multi-agent conversations in their decision-making
process