A Policy Framework for Harnessing Artificial Intelligence Systems in Urban Settings Using a Meta Synthesis Approach

Document Type : Research Paper

Authors

1 Prof., Department of Management, Faculty of Management, University of Tehran, Tehran, Iran.

2 Ph.D. Candidate, Department of Leadership and Human Capital, Faculty of Management, University of Tehran, Tehran, Iran.

3 Associate Prof., Department of Management, Faculty of Management, University of Tehran, Tehran, Iran.

10.22059/jipa.2023.355649.3298

Abstract

Objective
This systematic study aims to analyze qualitative research related to the use of Artificial Intelligence (AI) systems in urban management. The study seeks to achieve a comprehensive understanding of the current state of AI policy experiences in cities. By systematically reviewing and synthesizing prior findings in this domain, this research aims to contribute to the development of more effective policies for the responsible and efficient use of AI in urban management.
Methods
In this study, a meta synthesis approach was employed, relying on the seven-step framework proposed by Sandelowski and Barroso (2007). Thematic analysis was used as the tool for qualitative data analysis. To assess research quality, inter-coder agreement, provision of coded text samples, reporting of research process steps, and iterative reviewer discussions were utilized.
Results
Relevant articles were identified and analyzed. The findings from the coding process were categorized twice, first within a contextual framework following PESTLE’s analysis, and secondly into 27 proposed thematic categories. Furthermore, three dimensions of sustainability (data-driven, algorithmic, and ethical) in AI systems relevant to urban management were identified.
 
 
Conclusion
As a final outcome of this research, we propose a metaphorical framework called the "AI Policy Staircase for Cities." This framework comprises five steps: World view, Sociey, Legal system, Urban Governance, and Technology Management. Researchers of this metaphorical framework take a cross-disciplinary approach to prioritize among these five high-level concepts and introduce key dimensions within each, providing guidance to stakeholders involved in AI policy-making for urban management.
Objective
This systematic study aims to analyze qualitative research related to the use of Artificial Intelligence (AI) systems in urban management. The study seeks to achieve a comprehensive understanding of the current state of AI policy experiences in cities. By systematically reviewing and synthesizing prior findings in this domain, this research aims to contribute to the development of more effective policies for the responsible and efficient use of AI in urban management.
Methods
In this study, a meta synthesis approach was employed, relying on the seven-step framework proposed by Sandelowski and Barroso (2007). Thematic analysis was used as the tool for qualitative data analysis. To assess research quality, inter-coder agreement, provision of coded text samples, reporting of research process steps, and iterative reviewer discussions were utilized.
Results
Relevant articles were identified and analyzed. The findings from the coding process were categorized twice, first within a contextual framework following PESTLE’s analysis, and secondly into 27 proposed thematic categories. Furthermore, three dimensions of sustainability (data-driven, algorithmic, and ethical) in AI systems relevant to urban management were identified.
 
 
Conclusion
As a final outcome of this research, we propose a metaphorical framework called the "AI Policy Staircase for Cities." This framework comprises five steps: World view, Sociey, Legal system, Urban Governance, and Technology Management. Researchers of this metaphorical framework take a cross-disciplinary approach to prioritize among these five high-level concepts and introduce key dimensions within each, providing guidance to stakeholders involved in AI policy-making for urban management.

Keywords

Main Subjects

References

References
Abedi Jafari, H., Taslimi, M. S., Faghihi, A., & Sheikhzadeh, M. (2011). Content analysis and content network: A simple and efficient method for elucidating patterns in qualitative data. Strategic Management Thought, 5(2), 151-198. (in Persian)
Aizenberg, E. & van den Hoven, J. (2020). Designing for human rights in AI. Big Data & Society, https://doi.org/10.1177/2053951720949566
Allam, Z. & Dhunny, Z. A. (2019). On big data, artificial intelligence and smart cities. Cities, 89, 80–91. https://doi.org/10.1016/j.cities.2019.01.032
Angelidou, M. (2014). Smart city policies: A spatial approach. Cities, 41, S3–S11. https://doi.org/10.1016/j.cities.2014.06.007
Ayoub, K., & Payne, K. (2016). Strategy in the Age of Artificial Intelligence. Journal of Strategic Studies, 39(5–6), 793–819. https://doi.org/10.1080/01402390.2015.1088838
Badawi, H. F., Laamarti, F., & Saddik, A. el. (2021). Devising digital twins DNA paradigm for modeling ISO-based city services. Sensors (Switzerland), 21(4). https://doi.org/10.3390/s21041047
Bannister, F., & Connolly, R. (2020). Administration by algorithm: A risk management framework. Information Polity, 25(4), 471–490. https://doi.org/10.3233/IP-200249
Bao, J., & Bian, J. (2018). Application of artificial intelligence in urban landscape design. Journal of Advanced Oxidation Technologies, 21(2). https://doi.org/10.26802/jaots.2018.11632
Bratton, B. (2021). AI urbanism: a design framework for governance, program, and platform cognition. AI and Society. https://doi.org/10.1007/s00146-020-01121-9
Butcher, J., & Beridze, I. (2019). What is the State of Artificial Intelligence Governance Globally? RUSI Journal, 164(5–6), 88–96. https://doi.org/10.1080/03071847.2019.1694260
Calzada, I. (2019). Technological Sovereignty: Protecting Citizens’ Digital Rights in the AI-driven and post-GDPR Algorithmic and City-Regional European Realm. Regions. https://doi.org/10.1080/13673882.2018.00001038
Chatterjee, S. (2020). AI strategy of India: policy framework, adoption challenges and actions for government. Transforming Government: People, Process and Policy, 14(5), 757–775. https://doi.org/10.1108/TG-05-2019-0031
Criado, J. I., Valero, J., & Villodre, J. (2020). Algorithmic transparency and bureaucratic discretion: The case of SALER early warning system. Information Polity, 25(4), 449–470. https://doi.org/10.3233/IP-200260
de Almeida, P. G. R., dos Santos, C. D., & Farias, J. S. (2021). Artificial Intelligence Regulation: a framework for governance. Ethics and Information Technology, 23(3), 505–525. https://doi.org/10.1007/s10676-021-09593-z
Desouza, K. C., Dawson, G. S., & Chenok, D. (2020). Designing, developing, and deploying artificial intelligence systems: Lessons from and for the public sector. Business Horizons, 63(2), 205–213. https://doi.org/10.1016/j.bushor.2019.11.004
Dwivedi, Y. K., Hughes, L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., Duan, Y., Dwivedi, R., Edwards, J., Eirug, A., Galanos, V., Ilavarasan, P. V., Janssen, M., Jones, P., Kar, A. K., Kizgin, H., Kronemann, B., Lal, B., Lucini, B., … Williams, M. D. (2021). Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. International Journal of Information Management, 57, 101994. https://doi.org/10.1016/j.ijinfomgt.2019.08.002
Engin, Z., van Dijk, J., Lan, T., Longley, P. A., Treleaven, P., Batty, M., & Penn, A. (2020). Data-driven urban management: Mapping the landscape. Journal of Urban Management, 9(2), 140–150. https://doi.org/10.1016/j.jum.2019.12.001
Fernandes, E., Holanda, M., Victorino, M., Borges, V., Carvalho, R., & Erven, G. van. (2019). Educational data mining: Predictive analysis of academic performance of public school students in the capital of Brazil. Journal of Business Research, 94, 335–343. https://doi.org/10.1016/j.jbusres.2018.02.012
Finger, M., & Razaghi, M. (2017). Conceptualizing “Smart Cities.” Informatik-Spektrum, 40(1), 6–13. https://doi.org/10.1007/s00287-016-1002-5
Floridi, L., Cowls, J., Beltrametti, M., Chatila, R., Chazerand, P., Dignum, V., Luetge, C., Madelin, R., Pagallo, U., Rossi, F., Schafer, B., Valcke, P., & Vayena, E. (2018). AI4People—An Ethical Framework for a Good AI Society: Opportunities, Risks, Principles, and Recommendations. Minds and Machines, 28(4), 689–707. https://doi.org/10.1007/s11023-018-9482-5
Geerlings, M. (2020). CERTIFIED. http://resolver.tudelft.nl/uuid:44b3e1f2-b25d-4e94-bfd5-00ded546ac37
Gharabaghi, M., Moghimi, S. M., & Latifi, M. (2021). Superstructure of public policy implementation studies in Iran. Public Policy Quarterly, 7(3), 243-260. (in Persian)
Giffinger, R., Fertner, C., Kramar, H., & Meijers, E. (2007). City-ranking of European Medium-Sized Cities. Undefined.
Gill, A. S., & Germann, S. (2022). Conceptual and normative approaches to AI governance for a global digital ecosystem supportive of the UN Sustainable Development Goals (SDGs). AI and Ethics, 2(2), 293–301. https://doi.org/10.1007/s43681-021-00058-z
Hagendorff, T. (2020). The Ethics of AI Ethics: An Evaluation of Guidelines. Minds and Machines, 30(1), 99–120. https://doi.org/10.1007/s11023-020-09517-8
Ho, C. W. L., Soon, D., Caals, K., & Kapur, J. (2019). Governance of automated image analysis and artificial intelligence analytics in healthcare. In Clinical Radiology (Vol. 74, Issue 5, pp. 329–337). W.B. Saunders Ltd. https://doi.org/10.1016/j.crad.2019.02.005
Hosseininezhad, F., Sarafi, M., & Sharifzadegan, M. H. (2017). The role of urban service provision policies in the quality of life satisfaction system. Amayesh Mohit, 10(38), 145-168. (in Persian)
Inclezan, D., & Prádanos, L. I. (2017a). Viewpoint: A critical view on smart cities and AI. In Journal of Artificial Intelligence Research (Vol. 60). https://doi.org/10.1613/jair.5660
Inclezan, D., & Prádanos, L. I. (2017b). Viewpoint: A critical view on smart cities and AI. In Journal of Artificial Intelligence Research (Vol. 60, pp. 681–686). AI Access Foundation. https://doi.org/10.1613/jair.5660
Ismagilova, E., Hughes, L., Rana, N. P., & Dwivedi, Y. K. (2020). Security, Privacy and Risks Within Smart Cities: Literature Review and Development of a Smart City Interaction Framework. Information Systems Frontiers. https://doi.org/10.1007/s10796-020-10044-1
ITU Smart Sustainable Cities. (2021, July). ITUPublications. moz-extension://efbb654b-780a-4154-be36-6fef2e2e6515/enhanced-reader.html?openApp&pdf=https%3A%2F%2Fwww.itu.int%2Fen%2FITU-T%2Fssc%2Funited%2FDocuments%2FReports-on-SSC%2FITU_smart_sustainable_cities_brochure.pdf%3Fcsf%3D1%26e%3DyIueWP
Jain, V., Singh, N., Pradhan, S., & Gupta, P. (2020). Factors Influencing AI Implementation Decision in Indian Healthcare Industry: A Qualitative Inquiry. IFIP Advances in Information and Communication Technology, 617, 635–640. https://doi.org/10.1007/978-3-030-64849-7_56
Janssen, M., Hartog, M., Matheus, R., Yi Ding, A., & Kuk, G. (2020). Will Algorithms Blind People? The Effect of Explainable AI and Decision-Makers’ Experience on AI-supported Decision-Making in Government. Social Science Computer Review. https://doi.org/10.1177/0894439320980118
Kang, J. S., Kuznetsova, P., Luca, M., & Choi, Y. (2013). Where not to eat? Improving public policy by predicting hygiene inspections using online reviews. EMNLP 2013 - 2013 Conference on Empirical Methods in Natural Language Processing, Proceedings of the Conference, 1443–1448. https://doi.org/10.2139/ssrn.2293165
Kankanhalli, A., Charalabidis, Y., & Mellouli, S. (2019). IoT and AI for Smart Government: A Research Agenda. In Government Information Quarterly (Vol. 36, Issue 2, pp. 304–309). Elsevier Ltd. https://doi.org/10.1016/j.giq.2019.02.003
Krafft, T. D., Zweig, K. A., & König, P. D. (2022). How to regulate algorithmic decision-making: A framework of regulatory requirements for different applications. Regulation and Governance, 16(1), 119–136. https://doi.org/10.1111/rego.12369
Ku, C. H., & Leroy, G. (2014). A decision support system: Automated crime report analysis and classification for e-government. Government Information Quarterly, 31(4), 534–544. https://doi.org/10.1016/j.giq.2014.08.003
Lee, J., & Lee, H. (2014). Developing and validating a citizen-centric typology for smart city services. Government Information Quarterly, 31(SUPPL.1). https://doi.org/10.1016/j.giq.2014.01.010
Leslie, D. (2020). Understanding Artificial Intelligence Ethics and Safety: A Guide for the Responsible Design and Implementation of AI Systems in the Public Sector. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3403301
Liu, S. M., & Kim, Y. (2018). Special issue on internet plus government: New opportunities to solve public problems? In Government Information Quarterly (Vol. 35, Issue 1, pp. 88–97). Elsevier Ltd. https://doi.org/10.1016/j.giq.2018.01.004
Mahmoodi-Azar, A., Hashempour, R., & Foadmarashi, S. M. (2017). An analysis of the interaction of physical and mental quality of life based on access to public services in the historical texture of Urmia city. Applied Research in Geographical Sciences (Geographical Sciences), 17(45), 207-225. (in Persian)
Mark, R., & Anya, G. (2019). Ethics of Using Smart City AI and Big Data: The Case of Four Large European Cities. The ORBIT Journal, 2(2), 1–36. https://doi.org/10.29297/orbit.v2i2.110
Matheus, R., Janssen, M., & Maheshwari, D. (2020). Data science empowering the public: Data-driven dashboards for transparent and accountable decision-making in smart cities. Government Information Quarterly, 37(3), 101284. https://doi.org/10.1016/j.giq.2018.01.006
Mehr, H. (2017). Artificial Intelligence for Citizen Services and Government. In Harvard Ash Center Technology & Democracy. https://ash.harvard.edu/files/ash/files/artificial_intelligence_for_citizen_services.pdf
Mikalef, P., Fjørtoft, S. O., & Torvatn, H. Y. (2019). Artificial Intelligence in the Public Sector: A Study of Challenges and Opportunities for Norwegian Municipalities. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). https://doi.org/10.1007/978-3-030-29374-1_22
Mohabbati-Zahani, H., Yaghoubi, N. M., Mohammadi, M., & Mahmoudzadeh Vashan, M. (2020). Designing a phased crisis management model with a community capacity-building approach using the superstructure method. Public Management, 12(2), 175-203. (in Persian)
Mohammadi, M., & Al-Fuqaha, A. (2018). Enabling Cognitive Smart Cities Using Big Data and Machine Learning: Approaches and Challenges. IEEE Communications Magazine, 56(2), 94–101. https://doi.org/10.1109/MCOM.2018.1700298 (in Persian)
Mohammadpour, A. (2010). Quality assessment in qualitative research: Principles and strategies for validity and generalization. Social Sciences, 17(48), 73-107. (in Persian)
Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G., Altman, D., Antes, G., Atkins, D., Barbour, V., Barrowman, N., Berlin, J. A., Clark, J., Clarke, M., Cook, D., D’Amico, R., Deeks, J. J., Devereaux, P. J., Dickersin, K., Egger, M., Ernst, E., … Tugwell, P. (2009). Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. In Annals of Internal Medicine (Vol. 151, Issue 4, pp. 264–269). American College of Physicians. https://doi.org/10.7326/0003-4819-151-4-200908180-00135
Moshfeghifar, S., Ezzatpanah, B., & Mousavi, M. (2021). Evaluation of urban services in the ten major regions of Tabriz. Geography and Environmental Studies, 10(37), 79-98.
(in Persian)
Navarathna, P. J., & Malagi, V. P. (2018). Artificial intelligence in smart city analysis. Proceedings of the International Conference on Smart Systems and Inventive Technology, ICSSIT 2018. https://doi.org/10.1109/ICSSIT.2018.8748476
Nikitas, A., Michalakopoulou, K., Njoya, E. T., & Karampatzakis, D. (2020). Artificial intelligence, transport and the smart city: Definitions and dimensions of a new mobility era. Sustainability (Switzerland), 12(7). https://doi.org/10.3390/su12072789
Oesterreich, T. D., & Teuteberg, F. (2016). Understanding the implications of digitisation and automation in the context of Industry 4.0: A triangulation approach and elements of a research agenda for the construction industry. In Computers in Industry (Vol. 83). https://doi.org/10.1016/j.compind.2016.09.006
Office of the Supreme Leader's Official Website. (2021). Speech in a meeting with a group of elites and scientific talents. Retrieved from https://www.leader.ir/fa/speech/25368/www.leader.ir (in Persian)
Olsher, D. J. (2015). ScienceDirect New Artificial Intelligence Tools For Deep Conflict Resolution and Humanitarian Response. Procedia Engineering, 107, 282–292. https://doi.org/10.1016/j.proeng.2015.06.083
Pramanik, M. I., Lau, R. Y. K., Demirkan, H., & Azad, M. A. K. (2017). Smart health: Big data enabled health paradigm within smart cities. In Expert Systems with Applications (Vol. 87, pp. 370–383). Elsevier Ltd. https://doi.org/10.1016/j.eswa.2017.06.027
Pratama, A. B. (2018). Smart city narrative in Indonesia: Comparing policy documents in four cities. Public Administration Issues, 2018(6), 65–83. https://doi.org/10.17323/1999-5431-2018-0-6-65-83
Quality of Life Index by City 2021 Mid-Year. (n.d.). Retrieved July 25, 2021, from https://www.numbeo.com/quality-of-life/rankings.jsp
Reddy, S., Allan, S., Coghlan, S., & Cooper, P. (2020). A governance model for the application of AI in health care. In Journal of the American Medical Informatics Association (Vol. 27, Issue 3, pp. 491–497). Oxford University Press. https://doi.org/10.1093/jamia/ocz192
Salamat, N., Ghazanfari, H., & Dabagh Kashani, Z. (2016). Examining the impact of business process management empowerment factors on process success in Bahman automobile manufacturing group using the meta-synthesis approach. International Management and Accounting Conference, Tehran. (in Persian)
Sandelowski, M., Barroso, J., & Voils, C. I. (2007). Using qualitative metasummary to synthesize qualitative and quantitative descriptive findings. Research in Nursing and Health, 30(1), 99–111. https://doi.org/10.1002/nur.20176
Saunders, M. N. K., Lewis, P., & Thornhill, A. (n.d.). Research methods for business students. 741. Retrieved April 28, 2022, from https://books.google.com/books/about/Research_Methods_for_Business_Students_P.html?id=vUdOCgAAQBAJ
Schiff, D. S., Schiff, K. J., & Pierson, P. (2021). Assessing public value failure in government adoption of artificial intelligence. Public Administration. https://doi.org/10.1111/padm.12742
Siddaway, A. P., Wood, A. M., & Hedges, L. v. (2019). How to Do a Systematic Review: A Best Practice Guide for Conducting and Reporting Narrative Reviews, Meta-Analyses, and Meta-Syntheses. In Annual Review of Psychology (Vol. 70, pp. 747–770). Annual Reviews Inc. https://doi.org/10.1146/annurev-psych-010418-102803
Simonofski, A., Asensio, E. S., De Smedt, J., & Snoeck, M. (2019). Hearing the Voice of Citizens in Smart City Design: The CitiVoice Framework. Business and Information Systems Engineering, 61(6). https://doi.org/10.1007/s12599-018-0547-z
Sousa, W. G. de, Melo, E. R. P. de, Bermejo, P. H. D. S., Farias, R. A. S., & Gomes, A. O. (2019). How and where is artificial intelligence in the public sector going? A literature review and research agenda. In Government Information Quarterly. https://doi.org/10.1016/j.giq.2019.07.004
Stavand, M. M., Hajizadeh, F., & Yaghoubi, H. (2020). Spatial exploration of Shiraz urban areas from the perspective of social justice with an emphasis on public services. Applied Research in Geographical Sciences, 19(52), 171-192. (in Persian)
Sun, T. Q., & Medaglia, R. (2019). Mapping the challenges of Artificial Intelligence in the public sector: Evidence from public healthcare. Government Information Quarterly, 36(2), 368–383. https://doi.org/10.1016/j.giq.2018.09.008
Tadili, J., & Fasly, H. (2022). Towards a Smart City Stakeholders Classification: Case of Casablanca Smart City Project. Lecture Notes in Networks and Systems, 357 LNNS. https://doi.org/10.1007/978-3-030-91738-8_28
Taeihagh, A., Ramesh, M., & Howlett, M. (2021). Assessing the regulatory challenges of emerging disruptive technologies. Regulation and Governance, 15(4), 1009–1019. https://doi.org/10.1111/rego.12392
The Research Center of the Islamic Consultative Assembly. (2017). Artificial Intelligence and Legislation (Collection of Reports of the Basic Governmental Studies Center on Artificial Intelligence).
Tomor, Z., Meijer, A., Michels, A., & Geertman, S. (2019). Smart Governance for Sustainable Cities: Findings from a Systematic Literature Review. Journal of Urban Technology, 26(4), 3–27. https://doi.org/10.1080/10630732.2019.1651178
Ulnicane, I., Knight, W., Leach, T., Stahl, B. C., & Wanjiku, W. G. (2021). Framing governance for a contested emerging technology: insights from AI policy. Policy and Society, 40(2), 158–177. https://doi.org/10.1080/14494035.2020.1855800
Valle-Cruz, D., Criado, J. I., Sandoval-Almazán, R., & Ruvalcaba-Gomez, E. A. (2020). Assessing the public policy-cycle framework in the age of artificial intelligence: From agenda-setting to policy evaluation. Government Information Quarterly, 37(4). https://doi.org/10.1016/j.giq.2020.101509
Vesnic-Alujevic, L., Nascimento, S., & Pólvora, A. (2020). Societal and ethical impacts of artificial intelligence: Critical notes on European policy frameworks. Telecommunications Policy, 44(6). https://doi.org/10.1016/j.telpol.2020.101961
Weyerer, J. C., & Langer, P. F. (2019). Garbage in, garbage out: The vicious cycle of AI-based discrimination in the public sector. ACM International Conference Proceeding Series, 509–511. https://doi.org/10.1145/3325112.3328220
Wirtz, B. W., & Müller, W. M. (2019). An integrated artificial intelligence framework for public management. Public Management Review, 21(7), 1076–1100. https://doi.org/10.1080/14719037.2018.1549268
Wirtz, B. W., Weyerer, J. C., & Schichtel, F. T. (2019). An integrative public IoT framework for smart government. Government Information Quarterly, 36(2), 333–345. https://doi.org/10.1016/j.giq.2018.07.001
Wirtz, B. W., Weyerer, J. C., & Sturm, B. J. (2020). The Dark Sides of Artificial Intelligence: An Integrated AI Governance Framework for Public Administration. International Journal of Public Administration, 43(9), 818–829. https://doi.org/10.1080/01900692.2020.1749851
Yeghikyan, G. (2020). How will AI and automation transform society and cities? In arXiv.
Yigitcanlar, T., Desouza, K. C., Butler, L., & Roozkhosh, F. (2020). Contributions and risks of artificial intelligence (AI) in building smarter cities: Insights from a systematic review of the literature. In Energies (Vol. 13, Issue 6). https://doi.org/10.3390/en13061473
Zarei, M., Mohammadian, A., & Ghasemi, R. (2016). Internet of things in industries: A survey for sustainable development. In International Journal of Innovation and Sustainable Development (Vol. 10, Issue 4). https://doi.org/10.1504/IJISD.2016.079586
Zeinalou, M., Ali Ahmadi, A., & Nariman, S. (2022). Providing a performance evaluation model for the Islamic Consultative Assembly using the superstructure method. Public Management, 14(1), 74-108. (in Persian)
Zuiderwijk, A., Chen, Y. C., & Salem, F. (2021). Implications of the use of artificial intelligence in public governance: A systematic literature review and a research agenda. Government Information Quarterly, 101577. https://doi.org/10.1016/j.giq.2021.101577
Journal of Public Administration
Volume 15, Issue 3
2023
Pages 512-552

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