4 citations · 5 across the 8 of their papers we have counts for
5 papers · 1 filter
The Belief Update Gate: Separating Inertia from Learning in Human-AI Interaction
Shreyan Biswas, Alexander Erlei, Ujwal Gadiraju
Repeated human-AI interaction is often analyzed through pooled belief-updating slopes: users observe AI successes and failures, revise reported beliefs in the feedback-consistent d…
LLM-Agent Interactions on Markets with Information Asymmetries
Alexander Erlei, Lukas Meub
As AI agents increasingly act on behalf of human stakeholders in economic settings, understanding their behavior in complex market environments becomes critical. This article exami…
The Data-Dollars Tradeoff: Privacy Harms vs. Economic Risk in Personalized AI Adoption
Alexander Erlei, Tahir Abbas, Kilian Bizer +1
Privacy concerns significantly impact AI adoption, yet little is known about how information environments shape user responses to data leak threats. We conducted a 2 x 3 between-su…
Belief Updating and Delegation in Multi-Task Human-AI Interaction: Evidence from Controlled Simulations
Shreyan Biswas, Alexander Erlei, Ujwal Gadiraju
Large language models (LLMs) increasingly support heterogeneous tasks within a single interface, requiring users to form, update, and act upon beliefs about one system across domai…
When Life Gives You AI, Will You Turn It Into A Market for Lemons? Understanding How Information Asymmetries About AI System Capabilities Affect Market Outcomes and Adoption
Alexander Erlei, Federico Cau, Radoslav Georgiev +3
AI consumer markets are characterized by severe buyer-supplier market asymmetries. Complex AI systems can appear highly accurate while making costly errors or embedding hidden defe…