Trust in Generative AI for Health Information Consumption and the Effect of Learned Dependency: Randomized Controlled Experimental Study
Arif Ahmed, Gondy Leroy, Agrim Sachdeva, Philip Harber, Stephen Rains, Seokjun Youn, Prosanta Barai, Ivan Steenstra · 2026
Read Trust in Generative AI for Health Information Consumption and the Effect of Learned Dependency: Randomized Controlled Experimental Study by Arif Ahmed, Gondy Leroy, Agrim Sachdeva, Philip Harber, Stephen Rains, Seokjun Youn, Prosanta Barai, Ivan Steenstra (2026) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-13580606.txt.
Description
Arif Ahmed and a team of co-authors test trust in AI health answers, in a paper dated twenty twenty-six. Two randomized experiments asked whether habit-like reliance on AI skews how people judge its output. Highlight cues in the text were tested as a counterweight.
The first run used 338 college students; the second, 563 online workers. Each split people by answer accuracy and by whether key text was highlighted. Trust was scored on a multi-item scale. The design separates blind trust from earned trust and checks whether simple cues can curb overreliance on wrong answers.
Catalog record
| CREATOR | Arif Ahmed, Gondy Leroy, Agrim Sachdeva, Philip Harber, Stephen Rains, Seokjun Youn, Prosanta Barai, Ivan Steenstra |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 51 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |