
An interdisciplinary team
Our interdisciplinary team federates six academic fields (applied math, statistics, computer science, economics, law and sociology) around the ethical issues raised by artificial intelligence.
- Florence D'Alché-Buc
Professor in Computer Science and Applied Mathematics
Holder of the Télécom Paris « Data Science and Artificial Intelligence for Digitalised Industry and Services » Chair - Valérie Beaudouin
Professor of Sociology
Co-head of the Sociology Information Communication Design team - Albert Bifet
Full Professor in Computer Science specializing in data streams
- Isabelle Bloch
Professor in the field of image understanding and artificial intelligence
- Thomas Bonald
Professor
Head of the DIG (Data, Intelligence and Graphs) team - David Bounie
Full Professor, specialist in digital finance, Head of the Department of Economics and Social Sciences
- Chloé Clavel
Professor in Affective Computing
- Stéphan Clémençon
Professor in Applied Mathematics and Machine Learning
- Jean-Louis Dessalles
Associate Professor in artificial intelligence and cognitive sciences
- James Eagan
Associate professor in information visualization and human-computer interaction
- Winston Maxwell
Director, Law and Technology Studies
- Pavlo Mozharovskyi
Associate professor in machine learning
- Fabian Suchanek
Professor in semantic web and knowledge bases.
Developer of YAGO, a large public general-purpose knowledge base
Five research pillars
Algorithmic bias and fairness
Algorithmic explainability
AI and General Interest
AI liability
Governance and regulation
Blog
Training offers
The production of data from networks, connected objects, sensors or industrial processes has largely contributed to the digital transition of companies, which now consider data as a resource in its own right. All of a company’s activities and jobs have now been impacted, resulting in a growing need for training for teams and managers. Télécom Paris offers a variety of training options tailored to meet all needs.
Post-Master’s Degrees
Specialized Studies Certificates
Télécom Évolution offers two specialized studies certificates, Data Scientist and Artificial Intelligence, both of which are delivered by Télécom Paris, with contributions from ENSTA Paris for the second certificate. In collaboration with École polytechnique d’Assurance, it offers an Executive MBA Data Scientist for Insurance Careers.
Télécom Évolution also offers many inter-company training courses as well as the MOOC, The Basics of Big Data, which enrolls 7,000 learners every session.
Short training
Télécom Evolution offers the short training course The ethical challenges of artificial intelligence. This 2-day training course provides an overview of the main ethical, legal and societal issues surrounding AI.
Latest news
Interpretability, Accountability and Robustness in Machine Learning
Digital Trust, Data Science & AI — 16/02/2021Nowadays, data science, machine learning, artificial intelligence based solutions being integrated in [...]Federated learning: the privacy-friendly artificial intelligence?
Digital Trust, Data Science & AI — 18/01/2021Federated learning is a new concept emerged from Google Labs. The aim is to make a computer learn [...]Columbia University “Machine Learning in Science & Engineering” Conference
— 08/12/2020Florence d’Alché-Buc, Professor at Télécom Paris, Institut Polytechnique de Paris, will give a keynote [...]Do machines understand what they read?
Digital Trust, Data Science & AI — 22/10/2020One of the challenges of natural language processing (NLP) is to get the meaning right. Subtle changes in a sentence can [...]Explainability and fundamental rights
Digital Trust, Data Science & AI, Faculty Members — 16/10/2020When does the law require an algorithmic decision to be explained? A number of laws (GDPR, competition law, [...]Four positions opened to work on extracting complex information from natural language text
Data Science & AI — 02/10/2020We are looking for two PhD, one Postdoc, and one Research Engineer.To simplify AI regulation, use the GDPR’s high-risk criteria
Digital Trust, Data Science & AI, Faculty Members — 22/09/2020There are a multitude of contexts where we would expect an AI application to be [...]Facebook: German Supreme Court reopens the way for data regulation under competition law
Digital Trust, Data Science & AI, Faculty Members — 10/09/2020The "Facebook" saga in Germany has a new twist after the [...]The ACPR’s guidelines on explainability: clarifications and ambiguities
Digital Trust, Data Science & AI — 28/08/2020Machine learning can be of great help in the fight against money laundering by helping to [...]Why facial recognition algorithms can’t be perfectly fair
Digital Trust, Faculty Members — 20/07/2020By W. Maxwell and S. Clémençon. Facial recognition algorithms have been shown to be less accurate for [...]
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