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Dr. Takayuki ITO is Professor of Kyoto University. He received the Doctor of Engineering from the Nagoya Institute of Technology in 2000. He was a JSPS research fellow, an associate professor of JAIST, and a visiting scholar at USC/ISI, Harvard University, and MIT twice. He was a board member of IFAAMAS, the PC-chair of AAMAS2013, PRIMA2009, General-Chair of PRIMA2014, IEEE ICA2016, is the Local Arrangements Chair of IJCAI2020, and was a SPC/PC member in many top-level conferences (IJCAI, AAMAS, ECAI, AAAI, etc). He received the JSAI Achievement Award, the JSPS Prize, the Fundamental Research Award of JSSST, the Prize for Science and Technology of the Commendation for Science and Technology by the Minister of Education, Culture, Sports, Science, and Technology (MEXT), the Young Scientists' Prize of the Commendation for Science and Technology by the MEXT, the Nagao Special Research Award of IPSJ, the Best Paper Award of AAMAS2006, the 2005 Best Paper Award of JSSST, and the Super Creator Award of 2004 IPA Exploratory Software Creation Project. He was a JST PREST Researcher, and a principal investigator of the Japan Cabinet Funding Program for Next Generation World-Leading Researchers. He is currently principal investigator of JST CREST project.
Artificial Intelligence is revolutionising our communication practices and the ways in which we interact with each other. This revolution does not only impact how we communicate, but it affects the nature of the partners with whom we communicate. Online discussion platforms now allow humans to communicate with artificial agents in the form of socialbots. Such agents have the potential to moderate online discussions and even manipulate and alter public opinions. In this paper, we propose to study this phenomenon using a constructed large-scale agent platform. At the heart of the platform lies an artificial agent that can moderate online discussions using argumentative messages. We investigate the influence of the agent on the evolution of an online debate involving human participants. The agent will dynamically react to their messages by moderating, supporting, or attacking their stances. We conducted two experiments to evaluate the platform while looking at the effects of the conversational agent. The first experiment is a large-scale discussion with 1076 citizens from Afghanistan discussing urban policy-making in the city of Kabul. The goal of the experiment was to increase the citizen involvement in implementing Sustainable Development Goals. The second experiment is a small-scale debate between a group of 16 students about globalisation and taxation in Myanmar. In the first experiment, we found that the agent improved the responsiveness of the participants and increased the number of identified ideas and issues. In the second experiment, we found that the agent polarised the debate by reinforcing the initial stances of the participant.
Rafik Hadfi; Jawad Haqbeen; Sofia Sahab; Takayuki Ito. Argumentative Conversational Agents for Online Discussions. Journal of Systems Science and Systems Engineering 2021, 1 -15.
AMA StyleRafik Hadfi, Jawad Haqbeen, Sofia Sahab, Takayuki Ito. Argumentative Conversational Agents for Online Discussions. Journal of Systems Science and Systems Engineering. 2021; ():1-15.
Chicago/Turabian StyleRafik Hadfi; Jawad Haqbeen; Sofia Sahab; Takayuki Ito. 2021. "Argumentative Conversational Agents for Online Discussions." Journal of Systems Science and Systems Engineering , no. : 1-15.
Good discussions are essential for group decisions, especially when a group is large. But large group discussions are often plagued by antisocial behavior such as flaming, the sending or posting of offensive messages. Fortunately, several case studies have provided an important lesson: When a large-scale online decision support system with facilitator support functions was deployed in several real-world online discussion cases, no flaming was observed. Thus, for large online discussion groups, good support is critical to establishing and maintaining coherent prosocial discussions. The success of this approach led to the proposal of a facilitator-mediated online discussion model that seems likely to lead discussions in profitable directions, enabling even very large groups to reach good decisions. The ultimate goal is an automated facilitator agent that can help participants exchange viewpoints, negotiate together, and attain reasonable outcomes. There is now good reason to believe that, by supporting productive discussion, the social presence of a facilitator will ensure success in large-scale negotiations.
Takayuki Ito. Discussion and Negotiation Support for Crowd-Scale Consensus. Handbook of Group Decision and Negotiation 2021, 371 -393.
AMA StyleTakayuki Ito. Discussion and Negotiation Support for Crowd-Scale Consensus. Handbook of Group Decision and Negotiation. 2021; ():371-393.
Chicago/Turabian StyleTakayuki Ito. 2021. "Discussion and Negotiation Support for Crowd-Scale Consensus." Handbook of Group Decision and Negotiation , no. : 371-393.
Planning a city is a systematic process that includes time, space, and groups of people who must communicate. However, due to security problems in such war-ravaged countries as Afghanistan, the traditional forms of public participation in the planning process are untenable. In particular, due to gathering space difficulties and culture issues in Afghanistan, women and religious minorities are restricted from joining male-dominated powerholders’ face-to-face meetings which are nearly always held in fixed places called masjids (religious buildings). Furthermore, conducting such discussions with human facilitation biases the generation of citizen decisions that stimulates an atmosphere of confrontation, causing another decision problem for urban policy-making institutions. Therefore, it is critical to find approaches that not only securely revolutionize participative processes but also provide meaningful and equal public consultation to support interactions among stakeholders to solve their shared problems together. Toward this end, we propose a joint research program, namely, crowd-based communicative and deliberative e-planning (CCDP), a blended approach, which is a mixture of using an artificial-intelligence-led technology, decision-support system called D-Agree and experimental participatory planning in Kabul, Afghanistan. For the sake of real-world implementation, Nagoya Institute of Technology (Japan) and Kabul Municipality (Afghanistan) have formed a novel developed and developing world partnership by using our proposed methodology as an emerging-deliberation mechanism to reframe public participation in urban planning processes. In the proposed program, Kabul municipality agreed to use our methodology when Kabul city needs to make a plan with people. This digital field study presents the first practical example of using online decision support systems in the context of the neighborhood functions of Gozars, which are Kabul’s social and spatial urban units. The main objective was to harness the wisdom of the crowd to innovative suggestions for helping policymakers making strategic development plans for Gozars using open call ideas, and for responding to equal participation and consultation needs, specifically for women and minorities. This article presents valuable insights into the benefits of this combined approach as blended experience for societies and cities that are suffering long-term distress. This initiative has influenced other local Afghan governments, including the cities of Kandahar and Herat as well as the country’s central government’s ministry of urban planning and land, which has officially expressed its intention to collaborate with us.
Jawad Haqbeen; Sofia Sahab; Takayuki Ito; Paola Rizzi. Using Decision Support System to Enable Crowd Identify Neighborhood Issues and Its Solutions for Policy Makers: An Online Experiment at Kabul Municipal Level. Sustainability 2021, 13, 5453 .
AMA StyleJawad Haqbeen, Sofia Sahab, Takayuki Ito, Paola Rizzi. Using Decision Support System to Enable Crowd Identify Neighborhood Issues and Its Solutions for Policy Makers: An Online Experiment at Kabul Municipal Level. Sustainability. 2021; 13 (10):5453.
Chicago/Turabian StyleJawad Haqbeen; Sofia Sahab; Takayuki Ito; Paola Rizzi. 2021. "Using Decision Support System to Enable Crowd Identify Neighborhood Issues and Its Solutions for Policy Makers: An Online Experiment at Kabul Municipal Level." Sustainability 13, no. 10: 5453.
Good discussions are essential for group decisions, especially when a group is large. But large group discussions are often plagued by antisocial behavior such as flaming, the sending or posting of offensive messages. Fortunately, several case studies have provided an important lesson: When a large-scale online decision support system with facilitator support functions was deployed in several real-world online discussion cases, no flaming was observed. Thus, for large on-line discussion groups, good support is critical to establishing and maintaining coherent prosocial discussions. The success of this approach led to the proposal of a facilitator-mediated online discussion model that seems likely to lead discussions in profitable directions, enabling even very large groups to reach good decisions. The ultimate goal is an automated facilitator agent that can help participants exchange viewpoints, negotiate together, and attain reasonable outcomes. There is now good reason to believe that, by supporting productive discussion, the social presence of a facilitator will ensure success in large-scale negotiations.
Takayuki Ito. Discussion and Negotiation Support for Crowd-Scale Consensus. Handbook of Group Decision and Negotiation 2021, 1 -23.
AMA StyleTakayuki Ito. Discussion and Negotiation Support for Crowd-Scale Consensus. Handbook of Group Decision and Negotiation. 2021; ():1-23.
Chicago/Turabian StyleTakayuki Ito. 2021. "Discussion and Negotiation Support for Crowd-Scale Consensus." Handbook of Group Decision and Negotiation , no. : 1-23.