Abstract
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.
Article PDF
Similar content being viewed by others
Avoid common mistakes on your manuscript.
References
Al-Zubaide H, Issa AA (2011). Ontbot: Ontology based chatbot. International Symposium on Innovations in Information and Communications Technology, IEEE. Amazon (2020). Amazon.com “Elastic Compute Cloud (EC2)”. http://aws.amazon.com/ec2.
Amgoud L, Parsons S, Maudet N (2000). Arguments, dialogue, and negotiation. European Conference on Artificial Intelligence (ECAI2000). Berlin, Germany, August 20–25, 2000.
Amgoud L, Cayrol C, Lagasquie-Schiex MC, Livet P (2008). On bipolarity in argumentation frameworks. International Journal of Intelligent Systems 23(10):1062–1093.
Bail CA, Argyle LP, Brown TW, Bumpus JP, Chen H, Hunzaker MF, Lee J, Mann M, Merhout F, Volfovsky A (2018). Exposure to opposing views on social media can increase political polarization. Proceedings of the National Academy of Sciences 115(37):9216–9221.
Baroni P, Giacomin M (2007). On principle-based evaluation of extension-based argumentation semantics. Artificial Intelligence 171(10–15):675–700.
Bistarelli S, Rossi F, Santini F (2017). A conarg-based library for abstract argumentation. 2017 IEEE 29th International Conference on Tools with Artificial Intelligence (ICTAI). Boston, USA.
Bojanowski P, Grave E, Joulin A, Mikolov T (2017). Enriching word vectors with subword information. Transactions of:the Association for Computational Linguistics 5:135–146.
Cayrol C, Lagasquie-Schiex MC (2005). On the acceptability of arguments in bipolar argumentation frameworks. Conference on Symbolic and Quantitative Approaches to Reasoning and Uncertainty, Springer.
Chen H, Liu X, Yin D, Tang J (2017). A survey on dialogue systems: Recent advances and new frontiers. Sigkdd Explorations Newsletter 19(2):25–35.
Csaky R (2019). Deep learningbased chatbot models. arXiv preprint arXiv:190808835.
Dung PM (1995). On the acceptability of arguments and its fundamental role in nonmonotonic reasoning, logic programming and n-person games. Artificial Intelligence 77(2):321–357.
Ferrara E (2017). Disinformation and social bot operations in the run up to the 2017 French presidential election. arXiv preprint arXiv:170700086.
Fox J, Parsons S (1997). On using arguments for reasoning about actions and values. Proceedings of the AAAI Spring Symposium on Qualitative Preferences in Deliberation and Practical Reasoning, Stanford.
Graves A, Schmidhuber J (2005). Framewise phoneme classification with bidirectional lstm and other neural network architectures. Neural Networks 18(5–6):602–610.
Haqbeen J, Ito T, Hadfi R, Nishida T, Sahab Z, Sahab S, Roghmal S, Amiryar R (2020a). Promoting discussion with AI-based facilitation: Urban dialogue with Kabul city. Proceeding of the 8th ACM Collective Intelligence Conference.
Haqbeen J, Ito T, Sahab S, Hadfi R, Okuhara S, Saba N, Hofiani M, Baregzai U (2020b). A contribution to covid-19 prevention through crowd collaboration using conversational AI & social platforms. AI for Social Good Workshop.
Hussain S, Sianaki OA, Ababneh N (2019). A survey on conversational agents/chatbots classification and design techniques. Workshops of the International ConferenceonAdvanced Information Networking and Applications, Springer.
Iandoli L, Klein M, Zollo G (2007). Can we exploit collective intelligence for collaborative deliberation? The case of the climate change collaboratorium. MIT Sloan Research Paper No. 4675-08.
Ito T, Imi Y, Ito T, Hideshima E (2014). Collagree: A faciliator-mediated large-scale consensus support system. Collective Intelligence. 2014.
Ito T, Imi Y, Sato M, Ito T, Hideshima E (2015). Incentive mechanism for managing large-scale internet-based discussions on collagree. Collective Intelligence. 2015.
Ito T, Shibata D, Suzuki S, Yamaguchi N, Nishida T, Hiraishi K, Yoshino K (2019). Agent that facilitates crowd discussion. 7th ACM Collective Intelligence. Pitttsburgh, USA, June 13–14, 2019.
Keuschnigg M, Lovsjö N, Hedström P (2018). Analytical sociology and computational social science. Journal of Computational Social Science 1(1):3–14.
Kolko J (2012). Wicked Problems: Problems Worth Solving. Ac4d Austin, TX.
Kunz W, Rittel HW (1970). Issues as elements of information systems, vol 131. CiteSeer.
Malone TW (2018). Superminds: The surprising power of people and computers thinking together. Little, Brown Spark.
Malone TW, Klein M (2007). Harnessing collective intelligence to address global climate change. Innovations: Technology, Governance, Globalization 2(3):15–26.
Nofal S, Atkinson K, Dunne PE (2019). On deciding admissibility in abstract argumentation frameworks. The 11th International Conference on Knowledge Engineering and Ontology Development. Vienna, Austria, September 17–19, 2019.
Nofal S, Atkinson K, Dunne PE, Hababeh I (2019). A new labelling algorithm for generating preferred extensions of abstract argumentation frameworks. Proceedings of the 21st International Conference on Enterprise Information Systems — Volume 2: ICEIS, INSTICC, SciTePress.
Nuez Ezquerra A (2018). Implementing chatbots using neural machine translation techniques. B.S. thesis, Universitat Politècnica de Catalunya.
Ozer M, Yildirim MY, Davulcu H (2019). Measuring the polarization effects of bot accounts in the us gun control debate on social media. Proceedings of ACM Conference (Conference’17). New York, USA, 2019.
Savaget P, Chiarini T, Evans S (2019). Empowering political participation through artificial intelligence. Science and Public Policy 46(3):369–380.
Shao C, Ciampaglia GL, Varol O, Yang KC, Flammini A, Menczer F (2018). The spread of low-credibility content by social bots. Nature Communications 9(1):1–9.
Stella M, Ferrara E, De Domenico M (2018). Bots increase exposure to negative and inflammatory content in online social systems. Proceedings of the National Academy of Sciences 115(49):12435–12440.
Sunstein CR (2001). Echo Chambers: Bush v. Gore, Impeachment, and Beyond. Princeton University Press Princeton, NJ.
Suzuki S, Yamaguchi N, Nishida T, Moustafa A, Shibata D, Yoshino K, Hiraishi K, Ito T (2019). Extraction of online discussion structures for automated facilitation agent. Annual Conference of the Japanese Society for Artificial Intelligence, Springer.
Varol O, Ferrara E, Davis CA, Menczer F, Flammini A (2017). Online human-bot interactions: Detection, estimation, and characterization. Eleventh International AAAI Conference on Web and Social Media. Montreal, Canada, May 15–18, 2017.
Wallace RS (2009). The anatomy of Alice. Parsing the Turing Test, Springer.
Weizenbaum J (1966). Eliza — A computer program for the study of natural language communication between man and machine. Communications of the ACM 9(1):36–45.
Wittig M, Wittig A, Whaley B (2016). Amazon Web Services in Action. Manning.
Woolley AW, Chabris CF, Pentland A, Hashmi N, Malone TW (2010). Evidence for a collective intelligence factor in the performance of human groups. Science 330(6004):686–688.
Yan Z, Duan N, Chen P, Zhou M, Zhou J, Li Z (2017). Building task-oriented dialogue systems for online shopping. Thirty-First AAAI Conference on Artificial Intelligence.
Acknowledgments
The authors would like to thank the anonymous reviewers for their helpful comments. This work was supported by JST CREST Grant Number JPMJCR15E1, Japan.
Author information
Authors and Affiliations
Corresponding author
Additional information
Rafik Hadfi is currently an assistant professor in the Department of Social Informatics at Kyoto University. He received his M.Eng. and D.Eng. degrees from Nagoya Institute of Technology in 2012 and 2015. His work spans a broad range of disciplines and R&D activities including automated decision-making and the simulation of smart cities, online debates, and biological organisms. He is currently working on AI-enabled platforms to foster democratic deliberation, sustainable development, and gender equality.
Jawad Haqbeen received the B.S. and M.S. degrees in computer science from Nangarhar University, Afghanistan and Waseda University, Japan, in 2010 and 2013, respectively. He is currently pursuing his Ph.D. degree in artificial intelligence from Nagoya Institute of Technology, Japan. His main research interests include conversational agents, collective intelligence, crowdsourcing and applying artificial intelligence to civic technologies. He was the recipient of the Global Young Scientist Summit award in 2021 and Best International Conference Paper Award in 2020. He is a member of IEEE and IPSJ societies.
Sofia Sahab received the B.S. degree in architectural engineering from Kabul University in 2009, and M.E., and doctor of engineering degrees in urban planning from Nagoya Institute of Technology, Japan, in 2014 and 2017, respectively. She is currently specially appointed researcher at Kyoto University, Japan. She previously worked as assistant professor with Nagoya Institute of Technology, Japan, and Kabul University, Afghanistan. Her current research interests include participative decision support system, participatory urban planning, participatory e-planning, and civic technologies. She has published research articles in journals, such as Journal of Simulation and Gaming (SAGE Publications) and Journal of Architecture and Planning (Transections of Architectural Institute of Japan).
Takayuki Ito is professor of Kyoto University. He received the B.E., M.E, and Doctor of Engineering from the Nagoya Institute of Technology (NIT) in 1995, 1997, and 2000, respectively. From 1999 to 2001, he was a research fellow of the JSPS. From 2000 to 2001, he was a visiting researcher at USC/ISI. From April 2001 to March 2003, he was an associate professor of JAIST. From April 2004 to March 2013, he was an associate professor of NIT. From April 2014 to September 2020, he was a professor of NIT. From October 2020, he is a professor of Kyoto University. From 2005 to 2006, he is a visiting researcher at Division of Engineering and Applied Science, Harvard University and a visiting researcher at the Center for Coordination Science, MIT Sloan School of Management. From 2008 to 2010, he was a visiting researcher at the Center for Collective Intelligence, MIT Sloan School of Management. From 2017 to 2018, he is an invited researcher of Artificial Intelligence Center of AIST, JAPAN. From March 5 2019 he is the CTO of AgreeBit inc. as an entrepreneur.
Rights and permissions
About this article
Cite this article
Hadfi, R., Haqbeen, J., Sahab, S. et al. Argumentative Conversational Agents for Online Discussions. J. Syst. Sci. Syst. Eng. 30, 450–464 (2021). https://doi.org/10.1007/s11518-021-5497-1
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11518-021-5497-1