Administrative information

Title	Trust, Normativity and Model Drift
Duration	45-60
Module	C
Lesson Type	Lecture
Focus	Technical - Future AI
Topic	Open Problems and Challenges

Keywords

XAI,Ante-hoc,Post-hoc,SHAP,LIME,

Learning Goals

• Understand the Taxonomy of XAI techniques
• Understand the advantages and drawbacks of selected approaches to XAI
• Apply selected XAI techniques to a data set
• Identify future directions of XAI

Expected Preparation

Lesson materials

• Information on Data
• Practical part 1
• Practical part 2

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

Instructions for Teachers

Using the tabular example in the notes, using both LIME and SHAP to examine all attributes for four other incorrectly classified instances to describe the predictions. $ Using CNNS and the LIME and SHAP explainability approaches for four other incorrectly classified instances to describe the predictions. $ For a text-based problem, identify four other incorrectly classified instances to describe the predictions and why they may have been incorrect. $ Sum up your efforts, determine if exercises meet all five XAI perspectives, and elaborate if they do.

More information

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

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