Does disclosing AI use damage how trustworthy you seem?
When people learn you used AI to create work, do they trust you less? Schilke and Reimann tested this across 13 experiments with over 5,000 participants to understand whether transparency about AI reliance backfires.
Schilke and Reimann argue that telling people you used AI makes them trust you less. In a University of Arizona news piece written in the authors' own voice, the researchers report "13 experiments involving more than 5,000 participants" and "a consistent pattern: Revealing that you relied on AI undermines how trustworthy you seem." The participants included "students, legal analysts, hiring managers and investors," and even tech-savvy evaluators were less trusting of people who said they used AI. A positive view of technology "reduced the effect slightly, it didn't erase it." The authors call this a paradox, because honesty and transparency usually raise trust, and they name the effect a "transparency penalty."
The excerpt gives one reason for the penalty: "people still expect human effort in writing, thinking and innovating. When AI steps into that role and you highlight it, your work looks less legitimate." The account places the cost in the legitimacy of the work, not in a judgment that the discloser is dishonest. It is offered as "one reason," and the excerpt reports no test of it. It also gives no effect sizes, no measure of trust and no description of the experimental designs, so the size of the penalty across the 13 experiments cannot be read from the passage.
Against the nearest notes, the sharpest contrast is Does revealing AI identity help or hurt user trust?. That note finds a short-term bias against AI partners that reverses through repeated interaction with outcome feedback, in a hybrid society where people choose partners. The Schilke and Reimann excerpt is about how people judge a human who discloses AI reliance, and it describes no reversal; the authors write that "It's unclear whether this transparency penalty will fade over time." The two bodies of evidence therefore differ on whether the disclosure cost is temporary, and only the first reports a test of that question. Does telling people an AI wrote something actually stop them from believing it? points the same way in a persuasion setting: audiences who knew about AI involvement grew more critical, but the effect did not collapse. Both suggest that disclosure changes how audiences judge the work without fixing what the outcome will be.
What the excerpt does not establish is how far the penalty reaches. It reports no evidence that the effect holds outside the tested samples, and no test of the policy options the authors list. Their suggestion that a workplace culture where AI use is "seen as normal, accepted and legitimate" could "soften the trust penalty" is a proposal, not a result. The defensible reading is narrower than the headline: in these experiments, disclosing AI reliance cost the discloser trust, technology enthusiasm did not erase that cost, and whether it fades is open. A professional weighing disclosure should count the short-term cost as real in the settings studied, without treating it as proof that disclosure is the wrong choice.
Inquiring lines that read this note 9
This note is a source for these research framings, grouped by the broader line of inquiry each explores. Scan the bold lines of inquiry; follow any specific question forward.
How do AI hiring systems affect authenticity, fairness, and candidate preferences? Why do confident AI outputs mislead human trust calibration?- Does trust loss from AI exposure recover over time in workplaces?
- Does the trust penalty from AI disclosure fade with repeated exposure?
- Why does disclosure of AI involvement sometimes raise trust instead of lowering it?
- Does disclosing AI use in professional services damage client trust and credibility?
- Do people fear AI more when they use it directly and see its failures?
Related concepts in this collection 4
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Does hidden AI use cost more trust when exposed?
When AI use is discovered after being kept secret, does trust decline more steeply than if disclosed upfront? The question matters because it suggests concealment may carry hidden risks beyond the initial disclosure penalty.
sibling note: the concealment finding from the same excerpt, which makes the disclosure penalty a dilemma rather than a simple case for silence
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Does revealing AI identity help or hurt user trust?
Explores whether transparency about AI partners in interactions creates bias or enables better judgment. Matters because disclosure policies affect both user experience and fair evaluation of AI systems.
contrast: that study reports a disclosure cost that reverses with outcome feedback, while this excerpt reports no reversal
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Does telling people an AI wrote something actually stop them from believing it?
When audiences learn that AI created content, do they become skeptical enough to resist its persuasive pull? This explores whether disclosure works as a genuine defense against AI-driven persuasion or merely shifts how people process it.
parallel: knowing about AI involvement raises scrutiny in a persuasion setting without collapsing the effect
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Do people fear judgment when they use AI at work?
This research explores whether workers expect others to view them as less competent or diligent when using AI tools, and whether that fear affects their willingness to disclose tool use to managers and colleagues.
Evidence for and qualifies: AI disclosure lowers human and LLM raters' ratings too, but only by under 0.15 on a 7-point scale
Related papers in this collection 8
Papers most semantically related to this note, ranked by cosine similarity in the embedding space.
- Being honest about using AI at work makes people trust you less, research finds
- Humans learn to prefer trustworthy AI over human partners
- LLM or Human? Perceptions of Trust and Information Quality in Research Summaries
- Penalizing Transparency? How AI Disclosure and Author Demographics Shape Human and AI Judgments About Writing
- Toward Meaningful Transparency for AI Chatbots: Disclosing Persuasive Intent Reduces Persuasion
- What Influences Readers' and Writers' Perceived Necessity of AI Disclosure?
- Understanding Reader Perception Shifts upon Disclosure of AI Authorship
- Assistant or Actor? Student Trust, Control, and Delegation Regret When Using a General-Purpose AI Agent
Original note title
Schilke and Reimann find that revealing reliance on AI undermines how trustworthy people seem across 13 experiments — a transparency penalty