Administrative Information
| Title | Trust Models and Trust quantification |
| Duration | 90 min |
| Module | C |
| Lesson Type | Lecture |
| Focus | Technical - Future AI |
| Topic | Emerging Evaluations for HCAI models |
Keywords
Trustworthiness,Trust,
Learning Goals
- Understand trust as an AI Virtue
- Understand the Assessment List for Trustworthy AI (ALTAI)
- Be able to conduct a self-assessment to the ALTAI list
Expected Preparation
Learning Events to be Completed Before
Obligatory for Students
- None
Optional for Students
- ALTAI list
References and background for students
- Floridi, L. (2021). Establishing the rules for building trustworthy AI. Ethics, Governance, and Policies in Artificial Intelligence, 41-45.
Recommended for Teachers
- (AI HLEG) High-Level Expert Group on Artificial Intelligence, Ethics guidelines for trustworthy AI, European Commission, Text, Apr. 2019. Accessed: Oct. 26, 2020.
- Zerilli, J., Bhatt, U., & Weller, A. (2022). How transparency modulates trust in artificial intelligence. Patterns.
Lesson materials
Instructions for Teachers
- Introduction (10 min)
- European Approach to AI Trust(10 min)
- Human Agency and Oversight (15 min)
- Technical Robustness and Safety (5 min)
- Privacy and Data Governance (5 min)
- Transparency (15 min)
- Diversity, Non-Discrimination and Fairness (10 min)
- Societal and Environmental Impact
- Accountability
Outline
Acknowledgements
None
The Human-Centered AI Masters programme was Co-Financed by the Connecting Europe Facility of the European Union Under Grant №CEF-TC-2020-1 Digital Skills 2020-EU-IA-0068.