I was happy to present my research during the Machine Learning and Signal Processing on Graphs. The whole week was full of interesting discussions with all the participants. The beauty of the Calanques and the sea made it perfect.

Three years after my work on the predictive justice software Compas during my Philosophy Degree, and taking advantage of my experience as a PhD student, I did a presentation at the interdisciplinary meeting Algorythms

I attended CAp for the first time, a good opportunity to discover several French Machine Learning teams. I did an oral presentation of the paper Privacy amplification by decentralization.

I was the only woman with oral presentation of paper in this conference.

Two years after my work on the predictive justice software Compas during my Philosophy Degree, I wanted to summarize my takeaways from this use case, using also my new experience coming from my PhD team that works on fairness as well. Alain Desrosières was a statistician who succeeds in highlighting how the processus of getting numbers used for the statistics and how they are performed embed political decisions. Numbers are built, and thus come from choices which relevance can be discussing by opening the black lox of their creation and analysis.

Even if I believe that the content of his book La politique des grands nombres is integrated to the culture of every good engineer, this book is a seminal work when one wants to deepen the relationship between social impact and data-based learning. This workshop was the opportunity to see how sociologists and some of his former colleague approach his work.

My contribution was on the controversy on racial bias in Compas, and how it has been quantified by the company selling the software, by the newspaper Propublica and by machine learning community on fairness, especially pointing shortcomings on the use of biased dataset for checking bias.

I was invited to give a talk my paper Privacy Amplification by Decentralization at the seminar of the Argo team at Inria Paris.