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Algorithmic bias and ethics of ML systems
 - Data Science PhD Course

Speaker: 
Francesco Bonchi (ISI Torino & Eurecat), Carlos Castillo (UPF Barcelona), Chris Schwiegelshohn (Sapienza)
Data dell'evento: 
Monday, 27 May, 2019 - 11:45 to Tuesday, 28 May, 2019 - 16:00
Luogo: 
DIAG - Via Ariosto 25, Room B203
Contatto: 
leonardi@diag.uniroma1.it

Monday 27th May 2019 09:00 - 16:00, DIAG, Via Ariosto 25, room B203

1.                   09:00-11:00 Introduction to Algorithmic Bias (Carlos Castillo - UPF)

                                          Introduction to Algorithmic Discrimination 

                                          The Discrimination Discovery Task 

2.                   11:15-13:15 Mitigating Algorithmic Bias (Francesco Bonchi - ISI Torino & Eurecat)

                                          Mitigation of Algorithmic Bias in Data Mining 

3.                   14:00-16:00 Fairness in Machine Learning (Carlos Castillo - UPF)

                                          Discrimination in supervised classification 

                                           Practice on criminal recidivism: https://bitbucket.org/chato/savry-exploration/src/master/ 

 

Tuesday May 28  2019, 9.00 - 16.00, DIAG, Via Ariosto 25, room B203

4.                   09:00-11:00 Tools for Algorithmic Bias Detection and Mitigation (Francesco Bonchi - ISI Torino & Eurecat)

                                          Tools for Algorithmic Bias Detection and Mitigation

5.                   11:15-13:15 Fairness in Rankings + Ethics discussion (Carlos Castillo - UPF)

                                          Fairness in Rankings

                                      Ethics of Social Media Research; group discussion of case studies.

6.                   14:00 - 16:00 Algorithmic Fairness (Chris Schwiegelshohn - Sapienza)

               The Notion of Disparate Impact

               Fair algorithms for Clustering and Recommendation  

© Università degli Studi di Roma "La Sapienza" - Piazzale Aldo Moro 5, 00185 Roma