Prof. Stefano A. Cerri

DKTS Milan, Italy

University of Montpellier, France

Keynote Speech:

Towards foundational principles in Interactive AI:

From stamp collecting to Physics

1. Abstract

The presentation will consist of three parts :

A general premise on the scientific and technical nature of IT in general and Artificial Intelligence in particular, with examples that demonstrate the progressive convergence towards disciplines structured around a few general principles from which many, apparently very different, applications can be derived as happens in Physics. This is why the paradox of the transition from “stamp collecting” to Physics.

A central part which discusses the speaker’s choice of three large pre-competitive research projects – with European projects and concrete results – carried out by him over the years, from which it is understood that the three lines chosen to announce the conference (Adaptive and Personalized Systems, Service Science and Software Engineering, Semantic and Social Web) are actually strongly interdependent. From each of these projects there are a few essential lessons useful for the future.

A conclusion with some personal speculation on the priorities to be adopted, in the era of surprises such as ChatGPT and similar Augmented Intelligence (or Interactive Artificial Intelligence) services; fascinating and equally worrying tools.

At the end, unscheduled but upon request, a brief suggestion offered by the DKTS President months ago to the EU Parliament. which is legislating on AI in Europe. This proposal may lead to reflection on how to reduce fears and increase trust among the general public, as happens in the case of medicines legislation.

2. Premise

Rutherford aphorism, the concept of Informatics, Interactive Artificial Intelligence as Augmented Intelligence (AI).

Historical examples: SCHEME vs LISP, OZ as a multiparadigm language, Biology and DNA, the evolution of ITS.

3. Unifying the three tracks of NIDS by three foundational concepts of IAI: Roles, state, collective intelligence

3.1. Track I: Adaptive and Personalized Systems.

Roles in partner modeling; inverted dialogues (DELTA EU project NAT*LAB et al 1990).

3.2. Track III: Service Science and Software Engineering.

Stateful conversations for personalized services (Vth FP EU project ELEGI 2005).

3.3 Track II: Semantic and Social Web.

Collective wisdom (From ENCORE to ViewpointS 2020 +).

4. What is missing for the future of AI ? Conclusion

4.1. Emotions, personality traits, neuroinformatics (eg: Frasson).

4.2. Deep learning, Large language models (eg: ChatGPT) and integration with GOFAI.

5. References (including download links from HAL-LIRMM, CNRS when available)

About Semantic and Social Web (recent research):

Stefano A Cerri. Information, knowledge, and human learning for chemistry: the visionary contribution of Professor Alain Krief. Chemical Synthesis, 3(2):18, April 2023. doi: 10.20517/cs.2022.37. URL

Philippe Lemoisson, Stefano A. Cerri, Vincent Douzal, Pascal Dugenie, and Jean-Philippe Tonneau. Collective and Informal Learning in the ViewpointS Interactive Medium. Information, 12(5):183–214, May 2021. doi: 10.3390/info12050183. URL

Stefano A. Cerri and Philippe Lemoisson. Sovereignty by Personalization of Information Search: A Collective Wisdom May Influence My Knowledge. In ITS 2021 – 17th International Conference on Intelligent Tutoring Systems, volume 12677 of Lecture Notes in Computer Science, pages 376–383, Athens, Greece, June 2021. doi: 10.1007/978-3-030-80421-3 42. URL

Philippe Lemoisson and Stefano A. Cerri. ViewpointS: A Collective Brain. In Claude Frasson, Panagiotis Bamidis, and Panagiotis Vlamos, editors, BFAL 2020 – 2nd International Conference on Brain Function Assessment in Learning, volume 12462 of Lecture Notes in Computer Science, pages 34–44, Heraklion, Crete, Greece, October 2020. doi: 10.1007/978-3-030-60735-7 4. URL

Stefano A. Cerri and Philippe Lemoisson. Serendipitous Learning Fostered by Brain State Assessment and Collective Wisdom. In BFAL 2020 – 2nd International Conference on Brain Function Assessment in Learning, volume 12462 of Lecture Notes in Computer Science, pages 125–136, Heraklion, Crete, Greece, October 2020. doi: 10.1007/978-3-030-60735-7 14. URL

Raoudha Chebil, Wided Lejouad Chaari, and Stefano A. Cerri. A Generic Approach to Evaluate the Success of Online Communities. In ICCCI: International Conference on Computational Collective Intelligence, volume LNCS, pages 212–222, Nicosia, Greece, September 2017. doi: 10.1007/978-3-319-67074-4 21. URL

About Service Science and Software Engineering (2003-2008):

Clement Jonquet, Pascal Dugenie, and Stefano A. Cerri. Agent-Grid Integration Language. Multiagent and Grid Systems – An International Journal of Cloud Computing , 4(2):167–211, 2008a. doi: 10.3233/MGS-2008-4203. URL

Pascal Dugenie, Clement Jonquet, and Stefano A. Cerri. The Principle of Immanence in GRID-Multiagent Integrated Systems. In AWeSOMe’08: 4th International Workshop On Agents and Web Services Merging in Distributed Environments – OTM 2008 Workshops, number 5333 in LNCS, pages 98–107, Monterrey, Mexico, November 2008. Springer-Verlag. doi: 10.1007/978-3-540-88875-8 29. URL

Clement Jonquet, Pascal Dugenie, and Stefano A. Cerri. Service-Based Integration of Grid and Multi-Agent Systems Models. In International Workshop on Service-Oriented Computing: Agents, Semantics, and Engineering, SOCASE’08:, volume LNCS, pages 56–68, Estoril, Portugal, May 2008b. Springer Berlin / Heidelberg. doi: 10.1007/978-3-540-79968-9 5. URL

Pascal Dugenie and Stefano A. Cerri. The Principle of Immanence in Event-Based Distributed Systems. In S. Helmer and al., editors, Reasoning in Event-Based Distributed Systems, Studies in Computational Intellligence, pages 239–256. Springer-Verlag, December 2011. URL

Philippe Lemoisson and Stefano A. Cerri. Interactive Knowledge Construction in the Collaborative Building of an Encyclopedia. Applied Artificial Intelligence, 19(9-10):933–966, 2005. doi: 10.1080/08839510500234800. URL

Clement Jonquet and Stefano A. Cerri. The STROBE Model: Dynamic Service Generation on the Grid. Applied Artificial Intelligence, 19(9-10):967–1013, 2005a. doi: 10.1080/08839510500234826. URL

Clement Jonquet and Stefano A. Cerri. I-Dialogue: Modelling Agent Conversation by Streams and Lazy Evaluation. In International Lisp Conference, ILC’05, page 1, Stanford University, United States, June 2005b. URL

Cerri, S.A. (1999). Shifting the Focus from Control to Communication: the STReams OBjects Environments Model of Communicating Agents. In: Padget, J.A. (eds) Collaboration between Human and Artificial Societies. Lecture Notes in Computer Science(), vol 1624. Springer, Berlin, Heidelberg.

About Adaptive and Personalized Systems (“long” ago) :

Nadia Hocine, Abdelkader Gouaich, Stefano A. Cerri, Denis Mottet, Jerome Froger, and Isabelle Laffont. Adaptation in serious games for upper-limb rehabilitation: An approach to improve training outcomes. User Modeling and User-Adapted Interaction, 25(1):65–98, January 2015. doi: 10.1007/s11257-015-9154-6. URL

Cerri, S.a., Loia, V. A Concurrent, Distributed Architecture for Diagnostic Reasoning. User Modeling and User-Adapted Interaction 7, 69–105 (1997).

Cerri, S.A. (1994). The “Natural Laboratory” Methodology Supporting Computer Mediated Generic Dialogues. In: Verdejo, M.F., Cerri, S.A. (eds) Collaborative Dialogue Technologies in Distance Learning. NATO ASI Series, vol 133. Springer, Berlin, Heidelberg.

Cerri, S.A., Cheli, E., McIntyre, A. (1992). Nobile: User Model Acquisition in a Natural Laboratory. In: Jones, M., Winne, P.H. (eds) Adaptive Learning Environments. NATO ASI Series, vol 85. Springer, Berlin, Heidelberg.

Cerri, S.A., Cheli, E., McIntyre, A. (1992). Nobile: Object-Based User Model Acquisition for Second Language Learning. In: Swartz, M.L., Yazdani, M. (eds) Intelligent Tutoring Systems for Foreign Language Learning. NATO ASI Series, vol 80. Springer, Berlin, Heidelberg.

Prof. Michael L. Tee

Vice Chancellor for Planning & Development, University of the Philippines Manila

Keynote Speech:

Healthcare in the time of AI

Ultimately, healthcare is a person-to-person interaction where empathy and compassion play central roles in providing emotional support, understanding, and hope to patients. A significant amount of complex yet personalized decision is made based on non-verbal communication conveyed through body language, facial expressions, and tone of voice. It is in this context that we will explore how AI can be optimally deployed in enhancing this person-to-person interaction.