What solutions to data bias in machine learning algorithms?
10 mars de 17h à 18h30 - Séminaire Cycle webinar
Séminaire en ligne
While artificial intelligence is more and more used, many AI incidents report data processing biases or discrimination. Good In Tech organizes a research webinar to discuss the biases of artificial intelligence. What solutions to data bias in machine learning algorithms? With Stephan Clemençon (Telecom Paris), Serge Abiteboul (ENS Paris) and Julia Stoyanovich (NYU).
- On bias and fairness issues in Machine-Learning, Stephan Clemençon, Telecom Paris:
- Reponsible Data Science, Julia Stoyanovich, New York University
- Social media regulation, Serge Abiteboul, Inria, Board member at ARCEP
- Stephan Clemençon, Professor at Telecom Paris, Head of the research team S2A
- Serge Abiteboul, Computer science researcher at Ecole Normale Supéreieure de Paris and Inria, Board member at ARCEP
- Julia Stoyanovich, Assistant Professor in the Department of Computer Science and Engineering at the Tandon School of Engineering, and the Center for Data Science
Here is the link of the seminar.