« Synthèse des prospectives 2019 » : différence entre les versions
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* Need to recreate systems and infrastructures that require less energy, resources, maintainance, etc. |
* Need to recreate systems and infrastructures that require less energy, resources, maintainance, etc. |
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=== Confidentiality === |
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=== System safety (software, hardware and cyber-physical) === |
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== Problems to solve == |
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=== Certified construction of systems === |
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=== Error correction === |
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=== Explainability and accountability of embarked and cyber-physical systems === |
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The increasing complexity and autonomy of CPS have made accountability and explainability requirements more crucial: in order to be socially acceptable, the behaviors of CPS must be explainable. This is particularly the case for systems in which decision making is based on AI, but it is not limited to this case. Along with safety, the respect - and violation - of properties such as security and privacy must be explainable. This explainability should in particular be used to understand were the blame lies from a legal point of view when a CPS malfunctions. |
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Avec la complexité et l'autonomie croissantes des CPS les besoins d'accountability et d'explicabilité deviennent cruciaux : pour être socialement acceptables les comportements des CPS doivent être explicables. Ce besoin touche particulièrement les systèmes dont la prise de décisions est basée sur l'intelligence artificielle, mais il n'est pas limité à l'IA. Outre la sûreté, le respect - et la violation - de propriétés comme la sécurité et la vie privée doivent être rendus explicables. Cette explicabilité doit servir, en particulier, à départager les responsabilités juridiques entre acteurs en cas de dysfonctionnements des CPS. |
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== Research themes == |
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=== Concepts, |
=== Concepts, languages and tools for modelling and verifying complex systems === |
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* Graph rewriting |
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* réécriture de graphes |
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* Automated reasoning |
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* raisonnement automatisé, etc. |
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=== Embedded IA === |
=== Embedded IA === |
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"Embedded IA" |
"Embedded IA" and more specifically "embedded machine learning". There are now FPGA and ASIC implementations for ML and CNN (convolutional neural networks), as well as multicore deployments. |
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=== Proof formalisation in applied mathematics and theoretical computer science === |
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=== Formalisation de preuve en mathématiques appliquées et en informatique théorique === |
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E.g.: |
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* Development of libraries of certified definitions |
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* développement de corpus certifiés de définitions |
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* Theorems and algorithms for financial mathematics, logic, etc. |
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* théorèmes et algorithmes pour les mathématiques financières, la logique, etc. |
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=== Quantum information science === |
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=== Typed high-level languages for data science === |
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The preparation of data (clean-up, requests, distributed handling, etc.) is of paramount importance in the construction of AI applications. Construction of type systems for the analysis and handling of data. Construction of analysis methods and optimized compilation for these languages; in particular for requests. |
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Importance prépondérante de la préparation des données (nettoyage, |
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requêtage, manipulation distribuée des données, etc.) dans la |
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construction d'applications en intelligence artificielle. Construction de systèmes de types pour l'analyse de la manipulation de données. Construction de méthodes d'analyse et de compilation optimisante pour ces langages et en particulier pour le requêtage. |
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Version du 11 février 2019 à 10:10
Societal challenges
Adapting digital technology to the ecological transition
Digital technology needs to be adapted to the major challenge that is the ecological transition:
- Methods to better understand the environmental and societal impact of digital technology
- More important need for resiliency
- Need to recreate systems and infrastructures that require less energy, resources, maintainance, etc.
Confidentiality
System safety (software, hardware and cyber-physical)
Problems to solve
Certified construction of systems
Error correction
Explainability and accountability of embarked and cyber-physical systems
The increasing complexity and autonomy of CPS have made accountability and explainability requirements more crucial: in order to be socially acceptable, the behaviors of CPS must be explainable. This is particularly the case for systems in which decision making is based on AI, but it is not limited to this case. Along with safety, the respect - and violation - of properties such as security and privacy must be explainable. This explainability should in particular be used to understand were the blame lies from a legal point of view when a CPS malfunctions.
Research themes
Concepts, languages and tools for modelling and verifying complex systems
- Graph rewriting
- Automated reasoning
Embedded IA
"Embedded IA" and more specifically "embedded machine learning". There are now FPGA and ASIC implementations for ML and CNN (convolutional neural networks), as well as multicore deployments.
Proof formalisation in applied mathematics and theoretical computer science
E.g.:
- Development of libraries of certified definitions
- Theorems and algorithms for financial mathematics, logic, etc.
Quantum information science
Typed high-level languages for data science
The preparation of data (clean-up, requests, distributed handling, etc.) is of paramount importance in the construction of AI applications. Construction of type systems for the analysis and handling of data. Construction of analysis methods and optimized compilation for these languages; in particular for requests.