1st report of the Operational AI Ethics initiative on the issues of explicability and liability of algorithms
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.
Albert BifetFull Professor in Computer Science specializing in data streams
Florence D'Alché-BucProfessor in Computer Science and Applied Mathematics
Holder of the Télécom Paris « Data Science and Artificial Intelligence for Digitalised Industry and Services » Chair
Valérie BeaudouinProfessor of Sociology
Co-head of the Sociology Information Communication Design team
Isabelle BlochProfessor in the field of image understanding and artificial intelligence
Thomas BonaldProfessor
Head of the DIG (Data, Intelligence and Graphs) team
David BounieFull Professor, specialist in digital finance, Head of the Department of Economics and Social Sciences
Chloé ClavelProfessor in Affective Computing
Stéphan ClémençonProfessor in Applied Mathematics and Machine Learning
Jean-Louis DessallesAssociate Professor in artificial intelligence and cognitive sciences
James EaganAssociate professor in information visualization and human-computer interaction
Winston MaxwellDirector, Law and Technology Studies
Pavlo MozharovskyiAssociate professor in machine learning
Fabian SuchanekProfessor 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
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
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[Replay Webinar] What are the ethics of artificial intelligence?
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Digital Trust, Data Science & AI — 27/04/20The development of new technologies, in particular Artificial Intelligence (AI), used in finance, has strongly [...]
Operational AI Ethics: the new research initiative of Télécom Paris
Digital Trust, Data Science & AI — 23/04/20Télécom Paris, has just launched its new multidisciplinary research initiative, bringing [...]
Flexible and Context-Specific AI Explainability: A Multidisciplinary Approach
Digital Trust, Data Science & AI — 23/04/20Telecom Paris' Operational AI Ethics initiative has just published its first report [...]
EU Encourages Voluntary Tracing Apps, Stresses Privacy Safeguards
Digital Trust, Data Science & AI, Faculty Members — 16/04/20On Wednesday 15 April 2020, the European Commission said that one of the means [...]
Netherlands Welfare Case Sheds Light on Explainable AI for AML-CFT
Digital Trust, Faculty Members — 16/04/20The District Court of the Hague, Netherlands found that the government’s use of artificial [...]For remote or local facial recognition, the ethical issues are not the same
Digital Trust, Data Science & AI, Faculty Members — 09/03/20There are many uses of facial recognition, such as local identity [...]