Olivier Boissier, "Ethics by Reasoning in Socio-Technical and Cognitive Systems"
Abstract: Socio-technical systems bring together the social and physical worlds where people, things and services interact altogether. With the development of Artificial Intelligence, these systems are increasingly incorporating automated cognitive processes, which are delegated to autonomous services and things acting on behalf of humans. The ever enlarging scope of activity of these systems raises many challenging issues, among which Ethics appears as crucial and is strongly discussed. In this talk, we present the current landscape of approaches and challenges related to the development of socio-technical and cognitive systems with ethical behaviors. We focus on models and technics to program such systems based on collective autonomous agents that are able to reason at the individual, social and collective levels on the ethical dimensions of their behaviors. This work is part of the ETHICAA project funded by the French National Agency for Research (ANR). In this project, Philosophers, Economists, Robotic and AI scholars develop models and a methodological framework in which to lay out the development of Ethics by Reasoning in Multi-Agent in Systems.
Short CV: Olivier Boissier is Full Professor of Computer Science at Mines Saint-Etienne, School of the Institut Mines Telecom, France. He received his PhD in Computer Science at INP Grenoble and his Habilitation à Diriger des Recherches (HDR) at Mines Saint-Etienne and University Jean Monnet Saint-Etienne. He is the coordinator of the Connected Intelligence Research Group at Laboratoire Hubert Curien, UMR CNRS 5516. Olivier Boissier is active in the domain of multi-agent systems for 25 years. His main research focus are coordination and control of multi-agent systems and multi-agent oriented programming models, tools and methodologies to develop socio-technical systems. With other colleagues, he was one of the founders of the Coordination, Organization, Institutions and Norms in Agent Systems (COIN) successful international workshop series. He has published more than 200 papers in national and international conferences and journals. He has organized several workshops and international conferences and workshops. These last years, he has started to develop ethics by reasoning models and tools in the context of the development of AI technologies within socio-technical systems.
Piotr Faliszewski, "How to Choose a Committee Based on Agents' Preferences?"
There are numerous situations where people (or, more broadly, a group of agents) need to select a set of individuals of a given size, based on preferences
of these people (these agents). For example, democratic societies elect parliaments, judges in competitions choose finalists, Internet stores choose what
items to present on their homepages. In this talk we will argue that all these settings can be modeled in the language of multiwinner elections.
Specifically, in a multiwinner election we are given a set of candidates, a set of voters (with preferences over the candidates), and a target committee size.
The goal is to chose a subset of candidates of a given size, in a way that is most satisfying for the voters.
We will show that exact meaning of the phrase "most satisfying" strongly depends on the context, but we will argue that the language of committee scoring rules is sufficiently rich to capture many interesting interpretations of this phrase. Then we will analyze axiomatic and computational properties of committee scoring rules. We will argue that even though computing committee scoring rules is, typically, NP-hard, there are numerous means of dealing with this issue. We will also show some examples regarding how one can design committee scoring rules that match practical applications.
Short CV: Piotr Faliszewski is an associate professor at the Department of Computer Science at the AGH University of Science and Technology in Krakow, Poland. He received his PhD in 2009 from the Department of Computer Science at the University of Rochester, USA, under the supervision of Prof. Lane A. Hemaspaandra. After his PhD studies, he has taken a faculty position at the AGH University, but also held visiting professor positions at the University of Auckland, New Zealand, at the Universite Paris-Dauphine, France, and was Mercator fellow in the group of Prof. Rolf Niedermeier at TU Berlin, Germany. His research regards various areas of computational social choice theory, ranging from the complexity of strategic behavior, through cooperative game theory, to axiomatic analysis of voting rules. More broadly, his research regards multiagent systems in the context of decision-making. He is a (newly nominated) associate editor of the Journal of Artificial Intelligence Research.
Przemysław Kazienko, "Computational Network Science: from Data to Social Models"
Abstract: Through its data-driven approach computer science change all other sciences. It also refers network science and more specific domain: social network analysis. Social networks can be studied from four main perspectives: data processed by computer science, models developed by physics, human perception analyzed by cognitive science and neuroscience as well as survey research provided by sociology. All four complement each other making social networks one of the most interdisciplinary field. Our new studies on temporal social networks combining automatically traced human activities with their perception derived from periodical interviews will be presented as an example for such cohabitation. Additionally, recent research on information diffusion in complex networks will be discussed.
Short CV: Przemysław Kazienko, Ph.D. is a full professor and leader of ENGINE - the European Centre for Data Science at Wroclaw University of Science and Technology, Poland. He received his M.Sc. and Ph.D. degrees in computer science with honours, from Wroclaw University of Technology, Poland, in 1991 and 2000, respectively, his habilitation degree from Silesian University of Technology, Poland, in 2009 and professorship from the President of Poland in 2016. He has authored over 200 scholarly and research articles, including 35 in journals with impact factor within a variety of topics related to social network analysis, complex networks, spread of influence, collective classification, machine learning, sentiment analysis, DSS in medicine, finances and telecommunication, knowledge management, collaborative systems, data mining, recommender systems, information retrieval, and data security. He also initialized and led over 50 projects, including large European ones, chiefly in cooperation with companies. He gave 12 keynote/invited speeches for international audience and served as a co-chair of over 20 and a member of over 60 programme committees of international scientific conferences and workshops as well as a guest editor of eight special issues in prestige journals. He is an IEEE Senior Member, a member of the Editorial Board of several journals including Social Network Analysis and Mining, International Journal of Knowledge Society Research, International Journal of Human Capital and Social Informatics. He is also on the board of Network Science Society.