Introduction
This page reports a synthesis of the main elements that characterise the national AI strategy with a specific focus on the public sector. It extracts the information related to a single country from a comparative analysis done by the AI Watch team and reported in full in the science for policy report “AI Watch. European Landscape on the Use of Artificial Intelligence by the Public Sector”.
Main highlights
- Implement a Public data policy and a new open data legislation to improve data exchange between administrations and foster AI applications;
- Support public administrations in developing AI projects through a cross-sectors “Lab IA”, such as developing a pseudonymization tool for national jurisdictions;
- Animate AI and Data community of the public ecosystem;
- Offer specific remunerations for AI and data science expert profiles;
- Database of pre-trained AI models used in public administration for reuse;
- Train civil servants in AI/digital tools, as part of a broader education plan in AI;
- Building a strategy for green AI both at the national/local levels (smart cities);
- Increase AI-based disrupting projects through additional funding (“FTAP”), like for instance forecast firms bankruptcies by weak signals AI analysis or improve littoral cartography through AI-based laser detection (Lidar)
Strategy analysis
Learning by doing |
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Stimulating awareness and knowledge sharing |
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Ethical and legal framework |
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Improving data access and quality |
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Funding and procurement |
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Improving internal capacity |
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Comment
The AI strategy established a National consultative committee for AI ethics and started the development of new legal frameworks for public AI
New public bodies will be created and growth of AI teams in public bodies will be stimulated. High Officer for AI will be nominated, responsible for the coordination of the networks and contacts with ministries and other administrations. Skills will be fostered with specific remunerations for expert profiles required
There will be an increasing of funding towards AI-based projects (“FTAP”)
Lastly, there is a focus on training civil servants: (i) in public assistance and digital tools (ii) to prevent subjective biases of automated procedures and (iii) to understand and tackle any form of algorithmic discrimination.
General Information
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Data of release |
Mar 2018 (phase 1) ; Nov 2021 (phase 2) |
Specific actions to public sector |
Support public administrations in developing AI projects through a cross-sectors “Lab IA” ; Fund public transformation projects, such as forecasting firms bankruptcies by weak signals AI analysis; Set up a Health Data Hub, to facilitate the usage of data from the French health system for research and innovation.
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