Algorithmic Fairness, Accountability and Ethics

IT University of Copenhagen (Spring 2024)

ALFAE course is an overview on the topics of bias and fairness in data, models, and algorithms, and on the associated ethical and accountability issues. This repository contains exercises for Spring semester 2024.

Lectures:

1. Introduction with Vedran Sekara (2th February 2024)
2. Fairness metrics with Martin Aumüller (9th February 2024)
3. Explainability: Motivation and White-box models with Martin Aumüller (16th February 2024)
4. Explainability: Black-box models with Martin Aumüller (23th February 2024)
5. Bias sources with Vedran Sekara (1st March 2024)
6. Debiasing models with Vedran Sekara (8th March 2024)
7. Debiasing data with Vedran Sekara (15th March 2024)
8. Robustness of Models with Anders Weile Larsen (22th March 2024)
9. Auditing Algorithms with Vedran Sekara (5th April 2024)
10. Fairness & Generative AI with Vedran Sekara (12th April 2024)
11. The ethics of Fairness with Pawel Grabarczyk (19th April 2024)
12. The dream of AI. From GOFAI to modern AI with Pawel Grabarczyk (26th April 2024)
13. Philosophy of big data with Pawel Grabarczyk (3rd May 2024)
14. Recap, Evaluation and Feedback with Vedran Sekara (10th May 2024)

Submissions

1. Assignment 1 deadline 7th March 2024
2. Assignment 2 deadline 4th April 2024
3. Group Project: deadline May 2 2024

Team:

• Vedran Sekara (Course manager & Teacher)
• Martin Aumüller (Teacher)
• Pawel Grabarczyk (Teacher)
• Anders Weile Larsen (Teaching Assistant)