Pi Tech with Silvia Chiappa

Teaching Fairness to Machines

May 30, 2019 @ Pi 6 (via Indonesia 23, Rome)

by invitation only

Today, AI systems and products are becoming widespread in many aspects of everyday life, from insurance to policing and online platforms. However, fully data-driven systems raise essential concerns on their ethics and accountability: can we ensure that machine learning systems do not propagate existing biases and stereotypes from data? More in general, can we ensure that an algorithm is fair to everyone? While fairness has now become an essential concept in machine learning, its adoption still requires a fundamental shift in how we view and perceive intelligent systems.

On May 30th we will host a discussion on this topic with Silvia Chiappa, Staff Data Scientist at DeepMind, who will describe the significance of the problem and some of the work she conducted over the last years.


Silvia Chiappa

Silvia received a Diploma di Laurea in Mathematics from the University of Bologna and a Ph.D. in Statistical Machine Learning from École Polytechnique Fédérale de Lausanne. Before DeepMind, she has worked in many leading machine learning research groups: The Empirical Inference Department at the Planck Institute for Intelligent Systems, the Machine Intelligence and Perception Group at Microsoft Research Cambridge, and the Statistical Laboratory, University of Cambridge. Silvia’s research interests are based around Bayesian and causal reasoning, ML fairness, graphical models, approximate inference, and time-series models.


6:30 PM – Welcome to Pi Campus
by Marco Trombetti, Pi Campus founder and CEO

6:45 PM – Introducing Pi Tech Events
by Simone Scardapane, IAML founder

7:00 PM – Tackling bias in machine learning
Silvia Chiappa, Deepmind scientist

7:30 PM – Q&A

7:40 PM – Networking Aperitif

This seminar is part of the IAML tech talks, a serie of lectures co-organized and sponsored by the Italian Association for Machine Learning and Pi Campus, to promote discussion on topics of wide significance and societal impact, and bringing together researchers, professionals, and policy makers to discuss the future of machine learning in Italy.

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