HumanE-AI

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The Humane AI Flagship will develop the scientific foundations and technological breakthroughs needed to shape the ongoing artificial intelligence (AI) revolution.

The goal is to design and deploy AI systems that enhance human capabilities and empower people -- both as individuals and society as a whole -- to develop AI that extends rather than replaces human intelligence. This vision fits very well into the ambitions articulated by the EC in its Communication on AI but cannot be achieved by legislation or political directives alone. Instead it needs fundamentally new solutions to core research problems in AI and human-computer interaction (HCI), especially to help people understand actions recommended or performed by AI systems.

Challenges include: learning complex world models; building effective and fully explainable machine learning systems; adapting AI systems to dynamic, open-ended real world environments (in particular robots and autonomous systems in general); achieving in-depth understanding of humans and complex social contexts; and enabling self-reflection within AI systems.

The focus is on human-centered AI, with a strong emphasis on ethics, values by design, and appropriate consideration of related legal and social issues. The HumanE AI project will mobilize a research landscape far beyond the direct project funding and create a unique innovation ecosystem that offers substantial return on investment. It will result in significant disruption across its socio-economic impact areas, including Industry 4.0, health & well-being, mobility, education, policy and finance. It will spearhead the efforts required to help Europe achieve a step-change in AI uptake across the economy.

The preparatory action consortium, with 35 partners from 17 countries, including four large industrial members, will define the details of all aspects necessary to implement a full Flagship project, and mobilize major scientific, industrial, political and public support for this vision.

Manager: 
Guidotti, R., and S. Ruggieri, "On The Stability of Interpretable Models", 2019 International Joint Conference on Neural Networks (IJCNN): IEEE, 2019.
Guidotti, R., A. Monreale, and L. Cariaggi, "Investigating Neighborhood Generation Methods for Explanations of Obscure Image Classifiers", Pacific-Asia Conference on Knowledge Discovery and Data Mining: Springer, 2019.
Guidotti, R., and S. Ruggieri, "On The Stability of Interpretable Models", 2019 International Joint Conference on Neural Networks (IJCNN): IEEE, 2019.
Panigutti, C., R. Guidotti, A. Monreale, and D. Pedreschi, "Explaining multi-label black-box classifiers for health applications", International Workshop on Health Intelligence: Springer, 2019.
Guidotti, R., A. Monreale, and L. Cariaggi, "Investigating Neighborhood Generation Methods for Explanations of Obscure Image Classifiers", Pacific-Asia Conference on Knowledge Discovery and Data Mining: Springer, 2019.
Guidotti, R., A. Monreale, and D. Pedreschi, "The AI black box Explanation Problem", ERCIM NEWS, no. 116, pp. 12–13, 2019.
Guidotti, R., A. Monreale, S. Ruggieri, F. Turini, F. Giannotti, and D. Pedreschi, "A survey of methods for explaining black box models", ACM computing surveys (CSUR), vol. 51, no. 5, pp. 93, 2018.

Dino Pedreschi has been interviewed for the Workshops to design a Human Centered AI roadmap in Europe, in the context of the Humane-AI project.

Salvatore Rinzivillo has been interviewed for the Workshops to design a Human Centered AI roadmap in Europe, in the context of the Humane-AI project.

Franco Turini has been interviewed for the Workshops to design a Human Centered AI roadmap in Europe, in the context of the Humane-AI project.

Fosca Giannotti has been interviewed for the Workshops to design a Human Centered AI roadmap in Europe, in the context of the Humane-AI project.

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Acronym
HumanE-AI
Code
820437
Web Site
Start Date
1 March 2019
End Date
29 February 2020
Funded
Type
Area
Affiliation
Department of Computer Science, University of Pisa (DI-UNIPI)
Istituto di Scienza e Tecnologie dell’Informazione, National Research Council of Italy (ISTI-CNR)