Trust & Security

Trust calibration, cybersecurity, privacy, and the human factors that determine whether people rely on secure systems.

47 posts Category
AI & Agentic Systems 117IS Theory 111IT Governance & Strategy 107Organizational Theory 99Comps & Reflections 94Platforms & Ecosystems 59IS Research Methods 57Trust & Security 47Sociotechnical Systems 36Technology Adoption 36

When 80% of unauthorized AI use is internal policy violations, AI security platforms are governance products, not security products.

AI trust repair is not about rebuilding a relationship. It is about recalibration. The IS trust literature has been explaining this for two decades.

2026-05-14 6 min read

CARE Is Not About Privacy

Most people think digital privacy is about data breaches. Leidner and Tona's CARE framework says it is really about whether your dignity can survive digitizatio...

Hardware-level encryption during processing changes the risk side of the privacy calculus. IS privacy models were built for a world that no longer exists.

Digital provenance (BOMs, attestation databases, watermarking) gives users verifiable information about system origin and integrity. It is the first trust calib...

Learning analytics platforms collect enormous amounts of student behavior data. Whether that data measures learning, or just measures clicking, is a much harder...

2026-05-14 7 min read

Fear Does Not Make People Secure

Security awareness training loves a good scare story. The research says fear without efficacy produces denial, not compliance.

Hundreds of millions of people have downloaded mental health apps. The clinical evidence is mixed, the privacy practices are questionable, and the regulation ba...

Open data initiatives promise neutral access to government information. What gets published, in what format, and how usable it is reflects political choices.

Trust, trustworthiness, reliance, and delegation operate at different levels with different antecedents. Treating them as interchangeable is not a measurement c...