“The complexity of artificial learning” is a workshop organised by two working groups of CNR Foresight Project, namely “MAD4Future” and “CompleXXI”.
The Science and Technology Foresight Project seeks to define a medium to long-term vision to elaborate coherent research strategies relevant to socially critical problems in the field of environment, health, food, energy, and security. The Project is also promoting cross-sectional research pathways related to intelligent systems, complex systems and smart materials.
In the Foresight style, the joint workshop hold on May 5th 2029 is a private event for a cross-disciplinary discussion of research challenges and open gaps with lead scientists in the field of complex systems, data science, Artificial Intelligence and Machine Learning.
The core session consisted in the scientific talks on cogent topics, namely:
• Marc Mézard, “Learning and data structure”
• Lenka Zdeborová, “How many samples are really needed?”
• Enrico Capobianco, “AI and Machine Learning in Precision and Translational Biomedicine”
• Angelo Vulpiani, “Some Thoughts about Complexity, Data and Models”
• Riccardo Zecchina, “Challenges in contemporary machine learning”
• Fosca Giannotti, “Explainable Machine Learning for Trustworthy AI”
A second event will draw the main conclusions and prepare a position paper, as previous project workshops did.