CHAPTER 7

From Measurement Failure to Privacy Infrastructure

COVID-19 was also a "measurement failure". The contact histories, mobility data, testing information and biosignals needed for effective infection control were not captured with sufficient resolution. This was not mainly because the technology did not exist, but because society lacked the privacy infrastructure needed for people to take part in high-resolution measurement with confidence.

From Measurement Failure to Privacy Infrastructure: Reframing Contact Tracing Governance for the Next Pandemic
Y. Fujii — Journal of Medical Internet Research, Vol.28, e99645, 2026.
https://doi.org/10.2196/99645

Role: Privacy-preserving governance of infectious-disease measurement

A Viewpoint analysing the dilemma of contact-tracing apps and proposing to apply VRAIO (Verifiable Record of AI Output) to infectious-disease measurement. Published 5 October 2026.

The contact-tracing dilemma

Design	Result
Privacy-centred design	People take part, but epidemiological utility is lost
Data-rich design	Useful, but public trust and participation are lost

Infectious-disease measurement concerns human behaviour, relationships and bodily states, so greater precision also means deeper intrusion into privacy. Better technology alone cannot resolve this.

A change of view: privacy protection as a precondition

Privacy protection is treated not as a constraint on high-resolution measurement, but as the enabling condition that makes such measurement socially possible.

VRAIO: governing what leaves the system

Rather than focusing only on what an AI system is allowed to know, VRAIO makes it possible to verify, record and audit what information may be released, to whom, and for what purpose.

Output rules are set democratically
Each output carries a metadata declaration (purpose, target, scope)
An independent verifier checks it
A tamper-proof record is kept
Misuse is deterred (audit and sanctions)

Where two lines of research meet

This paper is the meeting point of two lines of research: individual exposure control (PAPR for Everyone) and AI/privacy governance (VRAIO). Measurement of PAPR wear and breathing, too, can become part of next-generation infectious-disease measurement only on top of trusted privacy infrastructure.

Related VRAIO research

Y. Fujii, "Verifiable record of AI output for privacy protection: public space watched by AI-connected cameras as a target example", AI & Society, Vol.40, pp.3697–3706, 2025. https://doi.org/10.1007/s00146-024-02122-8
Y. Fujii, "Governing AI Output in Autonomous Driving: Scalable Privacy Infrastructure for Societal Acceptance", Future Transportation, Vol.5, No.3, 116, 2025.
Application to streetlight camera networks: FMPS + VRAIO: public-safety infrastructure built on streetlights

← Previous: 6. Toward Formal Evaluation | Next: 8. Govern, Measure, Protect →