A five-point trust margin is not a mandate: what Drexel's Reddit study implies for AI product design

Drexel University researchers analyzed more than 230,000 posts from 39 AI-related subreddits between November 2022 and June 2025 and found trust in generative AI expressed in about 31% of them against distrust in 26% ^[1][2]. That is a five-point margin nearly four years after ChatGPT became a household name ^[15][17], which makes trust an unresolved product variable rather than a settled one.

The rest of the distribution matters more than the headline. In the same study, 41% of posts expressed neither trust nor distrust and 1% expressed both ^[2]. Only 57% of posts took a side at all, and the non-committal share is larger than either camp ^[16]. Across the study window trust generally held its modest lead, but the balance fluctuated and distrust briefly surpassed trust during some periods, and the steady flow of new models and applications did not push the pattern toward either pole ^[4].

The segment breakdown is the part that should change roadmaps. The team sorted posts into ten types of "trustor" using self-identifying information ^[9]. Trust outweighed distrust among business leaders, academics, software developers and tech industry professionals ^[10]. Distrust was more frequent among posts categorized as the general public, AI ethicists and advocacy groups, and media and journalists ^[11]. Generative AI users, the largest group, along with educators and knowledge workers, were relatively balanced ^[12]. In other words, the constituency that signs purchase orders skews positive while the constituency that actually operates the tools splits down the middle. Internal enthusiasm is therefore a poor proxy for how the output will land.

The study's definitions explain why this cannot be handled downstream by messaging. Lead author Aria Pessianzadeh defined trust as a belief that generative AI is reliable, competent or acts with integrity, producing positive expectations about its performance ^[7]. Distrust, he said, is more than the absence of trust: it is active skepticism about reliability, competence or ethical implications, which leads to negative expectations or more cautious behavior ^[8]. Active skepticism is not converted by a launch post. It is converted, if at all, by artifacts a user can inspect: visible sourcing on generated claims, honest uncertainty signaling instead of uniform confidence, a legible undo, and a real opt-out for people whose work or data is in scope. Those are backlog items with owners and latency budgets, not a comms workstream.

Two caveats on the evidence. The unit of analysis is posts, not people, drawn from AI-related subreddits discussing systems such as ChatGPT, LLaMA and Claude ^[1][13], so this is a picture of expressed sentiment in communities already engaged with the technology, not a population survey. And the result cuts against other recent reports suggesting that usage is rising while trust declines ^[5], so treat it as one baseline rather than the settled number. The paper, published in Transactions of the Association for Computational Linguistics, is described as the first large-scale longitudinal study of how these attitudes evolved over the last four years ^[3][14].

What to watch: whether the modest lead survives wider adoption, which Shadi Rezapour, who led the research, flagged as the open question and positioned as a baseline for responsible AI design, governance and literacy work ^[6]. Watch also for a re-crossing of the kind the study already recorded ^[4], and for whether the balanced posture of actual users ^[12] shows up in your own retention and escalation data before it shows up in a survey.