Educator Trust Calibration as Sociotechnical Practice: A Field Study of Generative AI Use in Indian Higher Education

Summary

This 14-week field study of 42 faculty members at a mid-tier Indian technical university examines how educators calibrate trust in generative AI systems as a sociotechnical practice rather than an individual attitude. Using diaries, prompt logs, interviews, surveys, workshops and structured red-teaming, the authors identify three mechanisms of initial over-reliance and four educator trust postures, synthesized into the Educator-AI Trust Calibration (EATC) framework. The paper introduces the local knowledge verification gap, through which fluent but unreliable outputs become hard to contest in underrepresented regional contexts.