Institut DATAIA
Science des données, Intelligence Artificielle et Société

DATAIA Institute
Data Science, Artificial Intelligence and Society

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la journée de lancement du 15 février

Data are the natural resource of the 21st century: digitalization makes data central to virtually all sectors, from manufacturing and sales to education and health. New industrial players with data-intensive innovative models challenge the historical leaders of existing economic sectors (e.g., transportation, insurance, tourism).

Data-intensive players have demonstrated their potential to change our way of life, our social structures and even our entire social landscape. More and better is to come: data-agile organisms will be in position to support global economic growth, social innovation, and improved health and well-being.

In brief, data-driven economy is a new game, that relies on a disruptive technology; it faces huge scientific and technical challenges on the one hand --acquire, store and process an amount of data that is doubled every two years-- and gigantic social, legal and ethical challenges on the other hand.

The objective of DATAIA Institute is to face both types of challenges in an integrated way, simultaneously advancing data science through:

  1. cutting edge research (algorithms, software, demonstrations);
  2. empowering human sciences to face the digital revolution;
  3. forging a shared vision of socially sustainable data sciences.

Specifically, this goal involves:

  1. advancing toward interdisciplinary overarching challenges, measured by joint actions and programs between players from different disciplines who tackle a given problem together;
  2. achieving a high-level of integration between academia and industry players in thescope of DATAIA Institute;
  3. developing novel initial and lifelong education curricula with interdisciplinary expertise and vision;
  4. consolidating the international visibility of the Paris-Saclay data science community, attracting world scientific leaders.

These curricula aim to both form the next generation of data scientists, and educate managers and policy makers to leverage responsibly data resources.