{"id":40,"date":"2018-07-04T03:01:01","date_gmt":"2018-07-04T03:01:01","guid":{"rendered":"http:\/\/gdnconference.org\/gdn2019\/?page_id=40"},"modified":"2019-03-12T15:02:58","modified_gmt":"2019-03-12T15:02:58","slug":"keynote-speakers","status":"publish","type":"page","link":"https:\/\/gdnconference.org\/gdn2019\/keynote-speakers\/","title":{"rendered":"Keynote Speakers"},"content":{"rendered":"

Sylvain Bouveret<\/h3>\n

Computational Social Choice in the Wild: Lessons Learned from Two\u00a0<\/strong>Voting Experiments in Political Elections<\/strong><\/h4>\n

Abstract:<\/em> The problem of electing a set of representatives that stand for a given\u00a0society is at the heart of any reasonable democracy. This problem has\u00a0been discussed for ages, and social choice theorists have proposed\u00a0dozens of voting methods, that all have their own merits and properties\u00a0(but all suffer from the same paradoxes). There exist many voting\u00a0rules. Yet, mainly the most simple ones like plurality or\u00a0first-past-the-post are commonly used for crucial political elections\u00a0(except in a few countries). Suppose that we change the voting rule for\u00a0such high-stake political elections. What impact would it have on the\u00a0voters’ behaviour and on the result of the election itself? This has\u00a0been the main topic of two different experiments that have been carried\u00a0out in France in 2017. The first one was run during the French\u00a0presidential election and involved more than 40,000 voters that were\u00a0asked to test alternative voting rules to elect the French president.\u00a0The second one was run after the legislative election and aimed at\u00a0using computer simulations to evaluate the impact of a reform of this\u00a0election. In his talk, Sylvain Bouveret will use these two experiments\u00a0to illustrate what happens when computational social choice theorists\u00a0go out of the labs in the wild world of political elections.<\/p>\n

ShortBio:<\/em>\u00a0Sylvain Bouveret is an Associate Professor in Computer Science at\"\"
\nGrenoble INP, University Grenoble-Alpes. He obtained an engineering\u00a0degree in 2004 and a PhD in Computer Science from the University of\u00a0Toulouse in 2007. From 2007 to 2011 he worked as a Research Engineer at\u00a0Onera Toulouse. His current research mainly concerns various aspects of\u00a0Computational Social Choice, with a special focus on fair division of\u00a0indivisible goods and voting. Although his main technical background is\u00a0on algorithmics and complexity, he recently extended his research\u00a0activities to data visualization and experiments in voting.<\/p>\n

<\/h3>\n

Elizabeth Stokoe<\/h3>\n

The myths and science of negotiation and other conversational practices<\/strong><\/h4>\n

Abstract:<\/em> Why do we think we know so much about negotiation, communication, and conversation when social scientists of all disciplines so often fail to capture and study actual talk in the wild? In this talk, Professor Elizabeth Stokoe will describe her work in conversation analysis, a field rooted in sociology and one which has been producing some of the most cited \u2013 yet relatively unknown – research in academia. Drawing on a variety of workplace and organizational settings, including crisis negotiation, medical communication, police interviews and commercial sales encounters, she will show how the analysis of conversation reveals its highly organized and systematic nature, and how research findings about what is (in)effective can underpin evidence-based communication training with integrity and impact.<\/p>\n

\"\"<\/h3>\n

Short Bio:<\/em> Elizabeth Stokoe is Professor of Social Interaction in the School of Social Sciences at Loughborough University. She uses conversation analysis to understand how talk works – from first dates to medical communication and from sales encounters to hostage negotiation. Outside the university, she runs workshops with doctors, mediators, salespeople, police and other professionals using her research-based communication training method called the “Conversation Analytic Role-play Method”. She is a WIRED Innovation Fellow and her research and biography were featured on the BBC Radio 4\u2019s The Life Scientific. In addition to publishing over 100 scientific papers and books, she is passionate about science communication, translating the world of conversation analysis for audiences of all kinds. She has given TED, New Scientist, Google\u00a0and\u00a0Royal Institution lectures, and performed at Latitude Festival (in the Wellcome Trust\/British Psychological Society stage) and Cheltenham Science Festivals. Her book, Talk: The Science of Conversation, is published by Little, Brown (2018).<\/p>\n

<\/h3>\n

Raimo P. H\u00e4m\u00e4l\u00e4inen<\/h3>\n

From Systems Thinking to Systems Intelligence – Foregrounding human behaviour in the Operations Research profession<\/strong><\/h4>\n

Abstract:<\/em> Systems Thinking is the basis of all Operations Research (OR) modelling and problem solving. The way we see the context and\u00a0 frame the problem determines the problem solving approach we take. However, in any practical OR project we also need to take into account the system created by the participatory problem solving\u00a0 process in which the OR professional, the problem owner and the stakeholders interact and co-operate. This brings in systemic\u00a0 human\u00a0 elements and dynamics which should not be ignored. They can include\u00a0 human cognitive characteristics and heuristics as well as emotional, cultural and social factors. These topics have earlier been discussed in the area of group decision making. The behavioural turn in OR has brought these themes into the attention of \u00a0wider OR audiences. The practicing OR professional needs to learn to cope with \u00a0communicational, emotional\u00a0 and social challenges as is the case in any other profession in the modern world. Understanding and describing systems from outside is not enough. We also need to learn to act intelligently from within the related ovelall system.\u00a0 Systems Intelligence (SI) is a perspective which addresses behavioural skills for the successfull engagement with systems created by\u00a0 people in systemic settings. In this talk I will discuss the systemic challenges in OR-based participatory problem solving and introduce the ideas and tools provided by the SI approach.<\/p>\n

Short Bio:\u00a0<\/em>Raimo P. H\u00e4m\u00e4l\u00e4inen is Emeritus Professor in the Systems\"\" Analysis Laboratory of \u00a0Aalto University, Finland and Visiting Professor in Loughborough University, UK. He is the author of over 200 publications on decision making and negotiations, control and dynamic games, energy modelling and environmental decision making, and biological systems. He is also the designer of many widely used decision support systems. As a consultant he has helped to solve problems especially in the areas of environmental policy and risk analysis. Recently he has actively worked on the concept of Systems Intelligence and its use in organizational contexts. He is chair of the EURO Working Group on Behavioural OR and one of the initiators of this emerging new area in OR. Professor Raimo P. H\u00e4m\u00e4l\u00e4inen is the Honorary President of the Finnish Operations Research Society and recipient of the Edgeworth-Pareto Award of the International Society on Multiple Criteria Decision Making.<\/p>\n","protected":false},"excerpt":{"rendered":"

Sylvain Bouveret Computational Social Choice in the Wild: Lessons Learned from Two\u00a0Voting Experiments in Political Elections Abstract: The problem of electing a set of representatives that stand for a given\u00a0society is at the heart of any reasonable democracy. This problem has\u00a0been discussed for ages, and social choice theorists have proposed\u00a0dozens of voting methods, that all […]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-40","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/gdnconference.org\/gdn2019\/wp-json\/wp\/v2\/pages\/40","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/gdnconference.org\/gdn2019\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/gdnconference.org\/gdn2019\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/gdnconference.org\/gdn2019\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/gdnconference.org\/gdn2019\/wp-json\/wp\/v2\/comments?post=40"}],"version-history":[{"count":18,"href":"https:\/\/gdnconference.org\/gdn2019\/wp-json\/wp\/v2\/pages\/40\/revisions"}],"predecessor-version":[{"id":437,"href":"https:\/\/gdnconference.org\/gdn2019\/wp-json\/wp\/v2\/pages\/40\/revisions\/437"}],"wp:attachment":[{"href":"https:\/\/gdnconference.org\/gdn2019\/wp-json\/wp\/v2\/media?parent=40"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}