Workshop: Philosophy of XAI - State of the Field
This workshop aims to bring together philosophers working on explainability/interpretability/transparency in machine learning, to share recent work and discuss future directions for the field.
Info about event
Time
Location
1532-122 (Aud G2): Department of Mathematics, Aarhus University, Ny Munkegade 118, 8000 Aarhus C, Denmark
Lunch, coffee/tea, cake, and fruit will be served at the workshop for those who have signed up by now.
Below you find the full program:
Day 1: June 18
9.30: Registration
10.00: Session 1
Thomas Grote - "Shaking up the dogma: Solving trade-offs without (moral) values in machine learning"
11.00: Break
11.15: Session 2
Will Fleisher – “XAI, Disagreement, and Idealized Models”
12.15: Lunch
13.30: Session 3
Joshua James Hatherley - “Federated Learning, Ethics, and the Double Black Box Problem in Medical AI”
14.30: Break
14.45: Session 4
Jens Ulrik Hansen - “Achieving legitimization and trust in AI projects: Data issues and model explainability”
15.45: Break
16.00: Session 5
Juan Manuel Duran + Emma-Jane Spencer - "The Limits of Reliability in Healthcare AI: What It Means and What We Can Do"
17.00: End
Day 2: June 19
9.00: Session 6
Eva Schmidt - "The Reasons of AI"
10.00: Break
10.15: Session 7
Kate Vredenburgh – “The distributive consequences of a right to explanation, XAI, and credit”
11.15: Break
11.30: Session 8
Lauritz Munch - “A fourth account of the right to explanation”
12.30: Lunch
13.30: Session 9
Lena Kastner
14.30: Break
14.45: Session 10
Carlos Zednik - "Explanation, Interpretation, and Deep Alignment"
15.45: Closing
16.00: End