Text Shot: We find that users submit longer and more complex queries than in traditional search, and treat the system as a collaborative research partner, delegating tasks such as drafting content and identifying research gaps. Users treat generated responses as persistent artifacts, revisiting and navigating among outputs and cited evidence in non-linear ways. With experience, users issue more targeted queries and engage more deeply with supporting citations, although keyword-style queries persist even among experienced users. We release the anonymized dataset and analysis with a new query intent taxonomy to inform future designs of real-world AI research assistants and to support realistic evaluation.
New From Allen Institute For Artificial Intelligence (Ai2): Understanding Usage and Engagement in AI-Powered Scientific Research Tools: The Asta Interaction Dataset (preprint) - Library Journal infoDOCKET www.infodocket.com/2026/02/26/new… #AI #ResearchTools