Overall Objectives
Research Program
Application Domains
Highlights of the Year
New Software and Platforms
New Results
Bilateral Contracts and Grants with Industry
Partnerships and Cooperations
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Section: Application Domains

Computational Social Sciences: Toward AI Fairness

Several TAU projects are related to computational social and economic sciences. This activity is at the core of the French DataIA Institut de Convergence, (head Nozha Boujemaa), gathering 19 partners in the Paris-Saclay area to explore the scientific and ethical impacts of data science and artificial intelligence on the academic, industrial and societal sectors.

Many projects in the domain are related to Causal Modelling (see Section 7.1.1). Some are internal to our team; others involve collaborations with external partners, with a transfer dimension. Others are closely related to some Software platform and are desribed in the corresponding Sections (io.datascience, Section 6.1 and Catolabe, Section 6.3).

Scientific challenges are related to the FAT (Fairness, Accountability and Transparency) criteria: Metric learning, where the distance/topology to be learned must reflect prior knowledge (e.g. ontologies); Interpretation of clusters built from heterogeneous textual and quantitative data, using the learnt metric/distance; Integration of the human-in-the-loop ("dire d'experts"); Assessment of the models w.r.t. their causality (as opposed to their predictive accuracy) in order to support further interventions.