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


 

Expected Preparation


Obligatory for Students

None.

Optional for Students

None.

References and background for students

None.

Recommended for Teachers

None.

 

Lesson materials


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

HCAIM Consortium