The Role of Artificial Intelligence in Sustainable Development

Dear Colleagues,

The role of crowd collaborations in innovative urban solutions is vital for solving complex (wicked) urban challenges and progressing communities towards the United Nations Sustainable Development Goals (SDGs) (Ito 2019) [1]. Specifically, SDG-11 emphasizes the need to introduce a deliberative means of establishing open lines of communication to promote participatory and inclusive ways for making a sustainable city (The UN 2030 Agenda on SD 2015) [2]. As a result, responding to goal No. 11 on the agenda, the efforts to create a deliberative and democratic line of communication to make the urban planning process accessible to all, and to “leaving no one behind” must be pushed forward (Haqbeen, Sahab, Ito, and Rizzi 2021) [3].

Conventionally, improving crowd collaboration in solving common problems has been the primary focus of communicative and participatory planning research reported in the literature (Forester 1999) [4]. However, over the past two decades, increasing attention has been paid to reframing participative ways by introducing new emerging internet-based tools and artificial intelligence (AI) technologies as a complement to support civic engagement and their collaboration in order to harness the crowd’s wisdom for inclusive policy-making (Macintosh, and Whyte 2008；Saad-Sulonen 2014) [5-6]. These tools constitute a supportive vehicle to socially engage and negotiate the unique and common qualities amongst the diverse opinions at every scale, linking the notions of collective arguments with proposed solutions, and most importantly, binding the individual agreement with collective consensus-building (Hadfi, Haqbeen, Sahab, and Ito 2021) [7]. In addition, these methods organize the collected insights in real-time to help policy-making institutions better understand the urban sentiments (Haqbeen, Ito, Hadfi, Sahab, Sahab, Nishda, Roghamal, and Amiryar 2020) [8]. Indeed, a necessary connection between crowd and government is necessary to adopt these methods as a mixture of AI and urban participatory practices (Haqbeen, Sahab, and Ito 2020) [9].

One of the challenges lies in the fact that we need to create more supportive means using fewer physical resources, namely, space and time constraints with in-person town meetings and town planning processes (Haqbeen, Ito, Hadfi, Sahab, Nishda, and Amiryar 2020) [10]. Unlike conventional participatory planning, these methods preserve diversity through meaningful consultation, preventing human bias and decreasing all possibilities of leaving community members’ suggestions and needs behind while making urban policies (Ito, Hadfi, Haqbeen, Suzuki, Kawamura, and Yamaguchi 2020) [11]. Last but not least, we also need not only to find solutions to decrease the effect of humans without jeopardizing the role of fair human decision-making but also to improve human trust in AI. For this reason, it is necessary to study various factors that link the participatory process to the actions, such as the evaluation of the impact of crowd–government and crowd–agent collaboration impact on the mandate of the participatory process after the time horizon of planning cycles by studying the ground truths.

The aim of this Special Issue is to collect research papers related to various Sustainable Development Goals from the perspective of effective collaboration among crowd and government and symbiosis between the human and artifact (i.e. AI, agent, and machine). We especially favor contributions that combine experimental AI methodologies for sustainable social good reflections with concrete research and project experiences in the real-world in response to SDGs (Haqbeen, Ito, Sahab, Hadifi, Sato, and Okuhara 2020) [12].

In the face of these conditions, we solicit contributions on potential topics that include, but are not limited to, the following:

• Perspectives of prompting crowd collaboration through large-scale decision support systems;
• Role of AI in extracting the crowd wisdom for solving complex urban issues;
• Role of AI towards collaborative intelligence and systems in symbiotic society;
• Trust in the role of AI to promote collective action and crowdsourcing from a sustainable point of view;
• The role of AI in harnessing the wisdom of the crowd from a sustainable point of view (SDG-11);
• The role of AI in promoting civic technologies;
• Deliberative and democratic systems;
• Online discussion support systems and their application in symbiotic society;
• Internet-based participatory and decision support systems.

References

1. Ito, T.; Shibita, D.; Suzaki, S.; Yamaguchi, N.; Nishida, T.; Hiraishi, K.; Yoshino, K. Agent that Facilitates Crowd Discussion. In Proceedings of the 7th ACM Collective Intelligence, Pittsburgh, PA, USA, 13–14 June 2019; Association for Computing Machinery: New York, NY, USA, 2019.
2. United Nation. UN Sustainable Development Group. Available online: https://unsdg.un.org/2030-agenda/universal-values/leave-no-one-behind (accessed on 10 May 2021).
3. Haqbeen, J.; Sahab, S.; Ito,T.; Rizzi, P. 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.
4. Fischer, F.; Forester, J. The Argumentative Turn in Policy Analysis and Planning, 1st ed.; Duke University Press: Durham, UK, 1993; pp. 1–21.
5. Macintosh, A. Characterizing e-Participation in Policy-making. In Proceedings of the 37th Annual Hawaii International Conference on System Sciences, Big Island, HI, USA, 5–8 January 2004; pp. 1–10.
6. Saad-Sulonen, J. Combining Participations. Expanding the Locus of Participatory e-Planning by Combining Participatory Approaches in the Design of Digital Technology and in Urban Planning. Doctoral Dissertation, Aalto University, Espo, Finland, 2014.
7. Hadfi, R.; Haqbeen, J.; Sahab, S.; Ito, T. Argumentative Conversational Agents for Online Discussions. J. Scie. Syst. Eng. 2021.
8. Haqbeen, J.; Ito, T.; Hadfi, R.; Nishida, T.; Sahab, Z.; Sahab, S.; Roghaml, S.; Amiryar, R. Promoting Discussion with AI-based Facilitation: Urban Dialogue with Kabul City. In Proceedings of the 8th ACM Collective Intelligence, ACM Collective Intelligence Conference Series, Boston (Virtual Conference), USA, 18 June 2020.
9. Haqbeen, J.; Ito, T.; Sahab, S. AI-based mediation improves opinion solicitation in a large-scale online discussion: Experimental evidence from Kabul Municipality. In Proceedings of the 29th International Joint Conference on Artificial Intelligence (IJCAI) Workshop on AI for Social Good, Yokohama, Japan, 7–15 January 2021; Center for Research on Computation and Society, Harvard University: Cambridge, MA, USA, 2021.
10. Haqbeen, J.; Ito, T.; Hadfi, R.; Sahab, Z.; Sahab, S.; Amiryar, R.; Nishida, T. Usage & Application of AI-based Discussion Facilitation System for Urban Renewal in Selected Districts of Kabul City: Afghanistan Experimental View. In Proceedings of the 34th Annual Conference of the Japanese Society for Artificial Intelligence, Kumamoto, Japan, 9–12 June 2020; pp. 1–4.
11. Ito, T.; Hadfi, R.; Haqbeen, J.; Suzuki, S.; Sakai, A.; Kawamura, N.; Yamaguchi, N. Agent-Based Crowd Discussion Support System and Its Societal Experiments. In Advances in Practical Applications of Agents, Multi-Agent Systems, and Trustworthiness, 1st ed.; Demazeau, Y., Holvoet, T., Corchado, J., Costantini, S., Eds.; Springer: L’Aquila, Italy, 2020; pp. 430–433.
12. Haqbeen, J.; Ito, T.; Sahab, S.; Hadfi, R.; Sato, T, Okuhara, S. Meeting the SDGs: Enabling the Goals by Cooperation with Crowd using Conversational AI Platform. In Proceedings of the 15th International Conference on Knowledge, Information and Creativity Support Systems, Nagoya, Japan, 24–26 November 2020.

Prof. Dr. Takayuki Ito
Dr. Sofia Sahab
Dr. Ryuta Arisaka
Dr. Hadfi Rafik
Guest Editors

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• artificial intelligence
• collective intelligence
• participatory e-planning
• communicative planning
• bottom-up practices
• deliberative planning
• open urbanism
• tools and techniques