Institution profile

Arcadia Impact

Research institutionnorthamerica · us
Research library11linked papers
Opportunities0open roles
Selected work

Representative Papers

Designing escalation criteria for international AI incident response: criteria, triggers, and thresholds

Apr 25, 2026

This study addresses the absence of actionable international standards for determining when AI incidents warrant escalation from national to cross-border coordinated responses. It proposes a systematic, multi-jurisdictional escalation framework that integrates eight assessment criteria, gated decision points, and threshold mechanisms to balance local policy flexibility with global coordination. Through regulatory analysis (e.g., SB 53, EU AI Act), cross-sectoral response framework comparisons, structured case testing, and flowchart modeling, the research identifies three design patterns in developer-led reporting systems that contribute to underreporting and highlights how ambiguous definitions and data gaps critically undermine detection efficacy. Validation across ten real-world and variant incidents demonstrates the framework’s practical utility while exposing significant deficiencies in current regimes regarding timeliness and operational feasibility.

0 citationsRead paper
Recent publications

Latest Papers

Designing escalation criteria for international AI incident response: criteria, triggers, and thresholds

Apr 25, 2026

This study addresses the absence of actionable international standards for determining when AI incidents warrant escalation from national to cross-border coordinated responses. It proposes a systematic, multi-jurisdictional escalation framework that integrates eight assessment criteria, gated decision points, and threshold mechanisms to balance local policy flexibility with global coordination. Through regulatory analysis (e.g., SB 53, EU AI Act), cross-sectoral response framework comparisons, structured case testing, and flowchart modeling, the research identifies three design patterns in developer-led reporting systems that contribute to underreporting and highlights how ambiguous definitions and data gaps critically undermine detection efficacy. Validation across ten real-world and variant incidents demonstrates the framework’s practical utility while exposing significant deficiencies in current regimes regarding timeliness and operational feasibility.

0 citationsRead paper