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Fosca Giannotti

Towards a Synergistic human-machine Interaction and Collaboration

The future of AI lies in enabling people to collaborate with machines to solve complex problems. Like any efficient collaboration, this requires good communication, trust, clarity, and understanding. Explaining to humans how AI reasons is only a part of the problem: we also must be able to design AI systems that understand and collaborate with humans. Hybrid decision-making systems aim at leveraging the strengths of both human and machine agents to overcome the limitations that arise when either agent operates in isolation.

The lecture will highlight the steps needed for promoting human-AI collaboration and seamless interaction maintaining the human responsibility of choice through a progressive disclosure to prevent cognitive overload. Three distinct paradigms, characterized by a different degree of human agency and machine autonomy will be discussed: i) human oversight, with a human expert monitoring AI prediction augmented by explanation; ii) Learning to defer, in which the machine learning model is given the possibility to abstain from making a prediction when it receives an instance where the risk of making a misprediction is too high; iii) collaborative and interactive learning, in which human and AI engage in communication to integrate their distinct knowledge and facilitate the human ability to make informed decisions.

Fosca Giannotti

is a pioneering scientist in mobility data mining, social network analysis, and privacy-preserving data mining. Fosca leads the Pisa KDD Lab – Knowledge Discovery and Data Mining Laboratory, a joint research initiative of the University of Pisa and ISTI-CNR. Fosca’s research focus is on social mining from big data: smart cities, human dynamics, social and economic networks, ethics and trust, diffusion of innovations. Her keynote speech will be on Explainable AI and LLMs.