Certified into the record
The exact text we saved
This is the version exactly as it was saved, character for character. The SHA-256 hash below is a 64-character code worked out from that text. Run the same text through SHA-256 and you get the same code; change a single letter and the code comes out completely different. Each version also stores the previous version’s hash, which chains them together so no version can be swapped out quietly.
TRUVACE RECORD VERSION record: TRV-2026-2566 version: 1 kind: certified reason: Certified into the record timestamp: 2026-11-12T07:55:18.821221Z status: published lens: p_space sector: labor headline: How workplace AI feedback shapes AI dependency: A randomized controlled trial on the moderating role of workplace social support among Japanese office workers dek: AI dependency—habitual, automatic AI use accompanied by diminished autonomy—is a growing concern in the workplace, yet the conditions under which it develops remain poorly understood. Two competing pathways have been proposed. Users with limited social support from colleagues may compensate for this deficit by depending on AI (the compensatory pathway ), or users with abundant support may be better positioned to leverage AI interaction, thereby fostering dependency (the enhancement pathway ). To test these pathw… gain_title: (none) problem_title: In a randomized trial of 294 Japanese office workers, positive chatbot feedback increased AI dependency one week later regardless of workplace support, and negative feedback did so among workers with abundant social support. trace_subject: (none) gain_reading: (none) gain_evidence: (none) problem_reading: In a randomized trial of 294 Japanese office workers, positive chatbot feedback increased AI dependency one week later regardless of workplace support, and negative feedback did so among workers with abundant social support. problem_evidence: Positive feedback increased AI dependency regardless of workplace social support levels | negative feedback did not increase AI dependency overall but did so selectively among participants with abundant social support quick_read: A five-day randomized controlled trial with 294 Japanese office workers tested how an AI chatbot's feedback shapes AI dependency, defined as habitual, automatic AI use with diminished autonomy. Participants held daily work-reflection sessions with the chatbot, which gave positive feedback on strengths, negative feedback on areas for improvement, or no work-related feedback in the control condition. Dependency was measured one week after the final session. Positive feedback raised it regardless of how much social support workers had from colleagues. Negative feedback did not raise it overall, but did among workers with abundant workplace support. The pattern matches the enhancement pathway, in which well-supported workers are better placed to build dependency on AI, rather than the compensatory pathway, in which isolated workers lean on AI to fill a gap. The authors conclude that dependency depends on the interaction between AI feedback and existing workplace relationships, not on AI characteristics alone. limitation: The outcome was short-term and self-reported, the analysis was exploratory and not preregistered, the key interaction was modest in size, and the crowdsourced Japanese sample limits generalizability. tag: Evidence-backed problem key_points: The trial enrolled 294 Japanese office workers who completed work-reflection sessions with an AI chatbot over 5 days. | Three conditions were compared: positive feedback emphasizing strengths, negative feedback highlighting areas for improvement, and no work-related feedback. | AI dependency was measured one week after the final session. | Positive feedback increased dependency regardless of workplace social support levels. | Negative feedback increased dependency only among participants with abundant social support, consistent with the enhancement pathway. | Two competing explanations were tested: a compensatory pathway for workers lacking support and an enhancement pathway for well-supported workers. rundown: Researchers define AI dependency as habitual, automatic AI use accompanied by diminished autonomy, and describe it as a growing workplace concern whose causes are poorly understood. They tested two proposed routes: workers with little colleague support compensating by relying on AI, or workers with plenty of support being better positioned to build dependency. In the trial, workers had daily work-reflection sessions with a chatbot for five days. The chatbot gave positive feedback, negative feedback or none, and dependency was assessed a week after the last session. Positive feedback worked as a general route to dependency across support levels. Negative feedback had an effect only for workers with abundant social support, which fits the enhancement pathway and not the compensatory one. sources: - peer_reviewed | Computers in Human Behavior: Artificial Humans | https://doi.org/10.1016/j.chbah.2026.100365 | 2026-08-01 prev: 0000000000000000000000000000000000000000000000000000000000000000
- SHA-256 hash
- 36e84e44fec16d86e4a9a0acdc458ac7647cab36ae5c22bdb5e959c73bf381cf
- Previous version’s hash
- 0000000000000000000000000000000000000000000000000000000000000000
How to check it yourself, without trusting this page
Download any version from /api/record/TRV-2026-2566 and hash its canonical field yourself, for example with shasum -a 256. You should get its content_hash. Each version’s text also ends with prev:and the hash of the version before it (version 1 points to 64 zeros). If anyone had changed a single character of any version after it was saved, those hashes wouldn’t line up.
ace