Administrative information

Title	Trust, Normativity and Model Drift
Duration	60
Module	C
Lesson Type	Lecture
Focus	Technical - Future AI
Topic	Open Problems and Challenges

Keywords

Trust, Model drift, Normativity,

Learning Goals

• Apply trust frameworks to several AI/ML example case studies
• Propose trust metrics to example case studies and link to EU Trust framework
• Discuss digital normativity in the context of example case studies
• Identify and Model Drift potential in example case studies and propose drift metrics and solutions to re-enforce model trust

Expected Preparation

Lesson materials

• Interactive session slides

The materials of this learning event are available under CC BY-NC-SA 4.0.

Instructions for Teachers

Instigate the students to engage in discussions. Lead and guide the discussion within the scope of the discussion points. Encourage students to focus on the evidence and interrupt if they are speaking over others. Keep a note of all the discussion points and share the discussion trail at the end of class. Provide conclusive remarks of the discussion with possible open questions and challenges.

Outline

More information

Click here for an overview of all lesson plans of the master human centred AI

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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