Linking Trust to Measurable Criteria
Participating researchers of the Seoul National University AI Reliability Center study AI standards and conduct international joint research.
Trustworthy AI Standards is SAPI’s research initiative on standards for reliable AI. The official introduction explains SAPI researchers’ participation in the Seoul National University AI Reliability Center and international joint research. It specifies collaboration with the Center for Technology, Innovation & Competition at Penn Carey Law and researchers from Singapore Management University.
When reading discussions about standards, it is helpful to examine how abstract values are connected to evaluation criteria and procedures. Since the technology’s performance, organizational operation methods, and usage environments differ, the scope of criteria application and verification conditions become important questions.
Background and collaboration of the research.
- Official title.
- Trustworthy AI Standards
- Date of introduction post.
- 2024.07.27
- Introduced partner organizations.
- Penn Carey Law Center for Technology, Innovation & Competition · Singapore Management University
Information on partner organizations and activities is based on the official project introduction on the date of the post above.
Questions for Reflection While Reading
- What evidence is required to judge that an AI system can be trusted?
- How are technical evaluation and organizational responsibility and management procedures connected?
- What considerations arise when applying common standards across different countries and industries?
Related Research Agendas
You can further explore related questions in subject-specific commentaries and foundational literature.
Research Materials for Further Reading
- Algorithmic Fairness Audit Research Case Study Report
This is a document compiled by law school student researchers on algorithmic fairness audit research cases, reviewed by supervising professors and lawyers.