AI Risk,Risk Management,Resilience Management,Explainable AI,Interpretable AI,Security,Resilience,Transparency,Accountability,
Learning Goals
Recognize, analyze and discuss the necessity and the role of security testing in AI.
Employ documents, such as the AI Act, to classify use cases into risk categories.
Discuss in-depth and with common European vocabulary on AI risk and how can AI be designed safely and benevolently, in ways that will not expose humans to unacceptable risks of harm, even when risky behaviour may advance a system goal.
Classify the obligations of providers and users in relation to AI risk management.
Discuss the requirements for high-risk AI systems as per the AI Act.
Elaborate and recognize specific risks and risk taxonomies, relevant throughout the different stages of the AI lifecycle.
Expected Preparation
Learning Events to be Completed Before
None.
Obligatory for Students
High-Level Expert Group on Artificial Intelligence (AI HLEG). (Apr. 8, 2019). European Commission. “Ethics Guidelines for Trustworthy AI.
HCAIM Lecture on Risk and Risk Mitigation
Optional for Students
HCAIM Webinar on the European Approach Towards Reliable, Safe, and Trustworthy AI (Available on YouTube)
HCAIM Webinar on the Role of Security and Privacy in Machine Learning (Available on YouTube)
References and background for students:
High-Level Expert Group on Artificial Intelligence (AI HLEG). (Apr. 8, 2019). European Commission. “Ethics Guidelines for Trustworthy AI.
HCAIM Lecture on Risk and Risk Mitigation
Recommended for Teachers
European Commission: Proposal for a Regulation of the European Parliament and of the Council Laying Down Harmonized Rules on Artificial Intelligence (Artificial Intelligence Act), 2021
European Union Agency for Cybersecurity, Malatras, A., Dede, G.,AI cybersecurity challenges: threat landscape for artificial intelligence, European Network and Information Security Agency, 2020
High-Level Expert Group on Artificial Intelligence (AI HLEG). (Apr. 8, 2019). European Commission. “Ethics Guidelines for Trustworthy AI.”
Malicious Uses and Abuses of Artificial Intelligence 2020, Europol Publication
The materials of this learning event are available under CC BY-NC-SA 4.0.
Instructions for Teachers
This interactive session aims to build a common vocabulary for students to discuss risk and risk management related to AI, specifically through the EU risk-based approach towards AI. The materials provided, as well as the overall outline and schedule of the interactive session are indicative and presented in order to better guide a discussion with the students. As long as the learning goals are met, instructors are encouraged to follow the natural flow of the discussion.
Outline and Schedule of the Interactive Session:
Duration
Topic
Description
15 mins
Introduction
Defining risk. EU's approach towards AI risk management. Risk management strategies throughout the AI lifecycle.
30 mins
Classifying risk
AI assets and threat taxonomy and risk management frameworks to describe technical design characteristics for AI.
30 mins
Mitigating risk
Approaching risk mitigation using use cases and common vocabulary, and reference models to leverage the discussion.
15mins
Closing Remarks
Discussion with Students. Questions and Answers.
Two HCAIM Webinars are particularly relevant to this interactive session. Those could be shown prior to the discussion or parts of them could be played to facilitate topics and manage silence.
Please visit the home page of the consortium HCAIM
Acknowledgements
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.
The materials of this learning event are available under CC BY-NC-SA 4.0
The HCAIM consortium consists of three excellence centres, three SMEs and four Universities
