Trustworthy Sustainability

AI systems whose environmental, social, and governance claims can be audited, compared, and trusted.

Trustworthy sustainability asks whether AI that is used to measure, rate, or reduce environmental impact can itself be trusted. The track covers sustainability rating methodology, energy and water accounting for AI systems, climate-risk analytics, and governance of automated ESG processes.

We seek methods that produce comparable scores, disclose data provenance, and surface disagreement among models or rating agencies. Papers may also study the environmental cost of training and deploying physical AI itself.

Submissions should make evaluation criteria explicit and discuss how results could be gamed, misreported, or transferred across jurisdictions.

All papers in this track must follow the PIJ Ethics Code.