The Discovery Science 2024 Conference serves as an open forum for intensive discussions and the exchange of new ideas among researchers working in the field of Discovery Science. The conference focuses on applying Artificial Intelligence methods to scientific inquiry. It covers developing and analyzing methods for scientific knowledge discovery—including machine learning, data mining, intelligent data analysis, and big data analytics—and their applications across various domains.

Nearly 150 participants attended, coming from across Europe as well as from Canada and the United States.

Professors Anna Monreale, Riccardo Guidotti, and Dino Pedreschi

Conference highlights:

Opening Remarks

Professors Anna Monreale, Riccardo Guidotti, and Dino Pedreschi officially opened the conference.

Keynote on Day 1:

Roberto Navigli, Professor of Computer Science at Sapienza University of Rome, presented a keynote titled “What is Missing in Today’s Large Language Models?” The talk explored key limitations of Large Language Models (LLMs), such as the lack of true understanding and reasoning, vulnerability to biases, challenges with long-term context retention, and difficulties in generating accurate outputs in non-dominant domains. Professor Navigli also discussed research directions that could enhance the capabilities and trustworthiness of future LLMs.

Roberto Navigli, Professor of Computer Science at Sapienza University of Rome

Day 2 Talk:

Carlos Castillo, ICREA Research Professor at Universitat Pompeu Fabra in Barcelona, presented “Human Factors and Algorithmic Fairness.” Their talk focused on ongoing research into the human factors affecting decision-support systems, with a particular emphasis on implications for algorithmic fairness.

Carlos Castillo, ICREA Research Professor at Universitat Pompeu Fabra in Barcelona

Day 3 Talk:

Francesca Toni, Professor in Computational Logic and Royal Academy of Engineering/JP Morgan Research Chair on Argumentation-based Interactive Explainable AI (XAI) at Imperial College London, UK, delivered a talk titled “Bridging Explainable AI and Contestability.” She emphasized that current AI and Explainable AI (XAI) methods often overlook the need for contestability, a requirement highlighted by AI guidelines (such as those from the OECD) and regulations on automated decision-making (such as the GDPR in the EU and UK). Professor Toni advocated for forms of contestable AI that can (1) provide progressive explanations of outputs and reasoning, (2) evaluate contestation grounds offered by humans or other systems, and (3) adjust decision-making processes in response to valid contestation.

Francesca Toni, Professor in Computational Logic and Royal Academy of Engineering/JP Morgan Research Chair on Argumentation-based Interactive Explainable AI (XAI) at Imperial College London, UK

Closing Events

• Closing Remarks: Professors Anna Monreale, Riccardo Guidotti, and Dino Pedreschi provided concluding reflections on the conference.
• Social Dinner: The conference included a social dinner at Villa Scorzi.
• Discovery Science 2024 Cake-Cutting Ceremony: A cake-cutting ceremony was held with Professors Anna Monreale, Riccardo Guidotti, Dino Pedreschi, Michelangelo Ceci (Steering Committee Chair), and Sašo Džeroski from the Jožef Stefan Institute in Ljubljana, Slovenia, which will host the Discovery Science 2025 conference.