Beyond the Hype: Mapping Uncertainty and Gratification in AI Assistant Use
For HCI researchers and designers, this paper provides a qualitative framework for understanding user expectations and satisfaction with AI assistants.
Through interviews with nine early adopters of AI assistants, the study identifies three forms of user uncertainty and finds that satisfying use comes from curated tool sets rather than autonomous agents.
A new generation of AI personal assistants reached consumers in 2023-2024 amid sweeping claims about anticipatory, agentic intelligence. Wearables such as the Rabbit R1 and Humane AI Pin, and subscription services such as Ohai and Docus, promised to learn users' routines and complete tasks across digital platforms. Drawing on semi-structured interviews with nine early adopters, this article asks how users make sense of these systems when the imaginary of an autonomous "second self" meets the recalcitrance of actual devices. Extending uncertainty reduction theory, we specify three forms of uncertainty in initial encounters: functional (what can it do?), relational (how do I get it to do it?), and metaphysical (what is it to me, and what should it remember?). We find that hype continues the pre-domestication of voice assistants; that the most satisfying uses are user-curated constellations of narrow tools rather than standalone "second selves."