Responsible Urban Innovation Working with Local Authorities a Framework for Artificial Intelligence (AI)

Ida Farida(1), Wahyu Ningsih(2), Ninda Lutfiani(3), Qurotul Aini(4), Eka Purnama Harahap(5),


(1) Nursing Science Yatsi College of Health Sciences Tangerang, Indonesia
(2) Science and Technology, University of Raharja, Indonesia
(3) Science and Technology, University of Raharja, Indonesia
(4) Science and Technology, University of Raharja, Indonesia
(5) Science and Technology, University of Raharja, Indonesia

Abstract

Purpose: By demonstrating that by adopting the principles of responsible urban innovation, we can harness the potential of digital technology to address urbanization issues and can minimize potential negative impacts.

Methods: The paper proposes a conceptual framework for accountable urban innovation, focusing on government AI systems, and draws on a literature review, practical examples, and research. The authors argue that responsible urban innovation must balance the costs, benefits, risks, and impacts of developing, implementing, and using AI systems in local government management. This approach emphasizes the importance of achieving desired urban outcomes while ensuring accountability.

Results: The framework provides potential directions for future research and development, offering an overview of recognized topics and a schedule for analysis. This research may assist urban managers, planners, and decision-makers in understanding the critical role that government AI systems play in achieving accountable outcomes. By adopting responsible urban innovation principles, we can harness the potential of digital technology to address urbanization issues while minimizing potential negative impacts.

Novelty: The conceptual framework presented in this study offers a new view in understanding the role of local government AI systems in achieving accountable outcomes.

Keywords

Responsible urban innovation; Artificial intelligence (AI); Local government AI; Revolution

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References

P. Seuwou, E. Banissi, and G. Ubakanma, “The Future of Mobility with Connected and Autonomous Vehicles in Smart Cities,” 2020, pp. 37–52.

A. Heidari, N. J. Navimipour, and M. Unal, “Applications of ML/DL in the management of smart cities and societies based on new trends in information technologies: A systematic literature review,” Sustain. Cities Soc., vol. 85, p. 104089, Oct. 2022, doi: 10.1016/j.scs.2022.104089.

M. Azeem, M. Ahmed, S. Haider, and M. Sajjad, “Expanding competitive advantage through organizational culture, knowledge sharing and organizational innovation,” Technol. Soc., vol. 66, p. 101635, Aug. 2021, doi: 10.1016/j.techsoc.2021.101635.

Z. Ullah, F. Al-Turjman, L. Mostarda, and R. Gagliardi, “Applications of Artificial Intelligence and Machine learning in smart cities,” Comput. Commun., vol. 154, pp. 313–323, Mar. 2020, doi: 10.1016/j.comcom.2020.02.069.

G. D’Amico, P. L’Abbate, W. Liao, T. Yigitcanlar, and G. Ioppolo, “Understanding Sensor Cities: Insights from Technology Giant Company Driven Smart Urbanism Practices,” Sensors, vol. 20, no. 16, p. 4391, Aug. 2020, doi: 10.3390/s20164391.

O. Golubchikov and M. Thornbush, “Artificial Intelligence and Robotics in Smart City Strategies and Planned Smart Development,” Smart Cities, vol. 3, no. 4, pp. 1133–1144, Oct. 2020, doi: 10.3390/smartcities3040056.

U. Rahardja, Q. Aini, D. Manongga, I. Sembiring, and Y. P. A. Sanjaya, “Enhancing Machine Learning with Low-Cost P M2.5 Air Quality Sensor Calibration using Image Processing,” APTISI Trans. Manag., vol. 7, 2023, [Online]. Available: https://ijc.ilearning.co/index.php/ATM/article/view/2062.

H. M. K. K. M. B. Herath and M. Mittal, “Adoption of Artificial Intelligence in Smart Cities: A Comprehensive Review,” Int. J. Inf. Manag. Data Insights, vol. 2, no. 1, p. 100076, Apr. 2022, doi: 10.1016/j.jjimei.2022.100076.

M. Wahyudi, V. Meilinda, and A. Khoirunisa, “The Digital Economy’s Use of Big Data Technologies and Data Science,” Int. Trans. Artif. Intell., vol. 1, no. 1, pp. 62–70, 2022, [Online]. Available: https://journal.pandawan.id/italic.

S. Secinaro, V. Brescia, D. Calandra, and P. Biancone, “Towards A Hybrid Model for The Management of Smart City Initiatives,” Cities, vol. 116, p. 103278, Sep. 2021, doi: 10.1016/j.cities.2021.103278.

A. S. Bist, B. Rawat, U. Rahardja, Q. Aini, and A. G. Prawiyogi, “An Exhaustive Analysis of Stress on Faculty Members Engaged in Higher Education,” IAIC Trans. Sustain. Digit. Innov., vol. 3, no. 2, pp. 126–135, Feb. 2022, doi: 10.34306/itsdi.v3i2.533.

M.-L. Marsal-Llacuna and M. E. Segal, “The Intelligenter Method (I) for Making ‘Smarter’ City Projects and Plans,” Cities, vol. 55, pp. 127–138, Jun. 2016, doi: 10.1016/j.cities.2016.02.006.

C. Gonzales-Gemio, C. Cruz-Cázares, and M. J. Parmentier, “Responsible Innovation in SMEs: A Systematic Literature Review for a Conceptual Model,” Sustainability, vol. 12, no. 24, p. 10232, Dec. 2020, doi: 10.3390/su122410232.

S. E. Bibri, “Data-Driven Smart Sustainable Cities of The Future: Urban Computing and Intelligence for Strategic, Short-Term, and Joined-Up Planning,” Comput. Urban Sci., vol. 1, no. 1, pp. 1–29, 2021, doi: 10.1007/s43762-021-00008-9.

S. Curry, S. de Rijcke, A. Hatch, D. Pillay, I. van der Weijden, and J. Wilsdon, “The Changing Role of Funders in Responsible Research Assessment : Progress, Obstacles and The Way Ahead,” Res. Res. Inst., 2020, [Online]. Available: https://eprints.whiterose.ac.uk/171602/1/.

E. Ismagilova, L. Hughes, Y. K. Dwivedi, and K. R. Raman, “Smart cities: Advances in Research—An Information Systems Perspective,” Int. J. Inf. Manage., vol. 47, pp. 88–100, Aug. 2019, doi: 10.1016/j.ijinfomgt.2019.01.004.

G. L. Tortorella, R. Giglio, and D. H. van Dun, “Industry 4.0 Adoption As A Moderator of The Impact of Lean Production Practices on Operational Performance Improvement,” Int. J. Oper. Prod. Manag., vol. 39, no. 6/7/8, pp. 860–886, Dec. 2019, doi: 10.1108/IJOPM-01-2019-0005.

T. Yigitcanlar, J. M. Corchado, R. Mehmood, R. Y. M. Li, K. Mossberger, and K. Desouza, “Responsible Urban Innovation with Local Government Artificial Intelligence (AI): A Conceptual Framework and Research Agenda,” J. Open Innov. Technol. Mark. Complex., vol. 7, no. 1, p. 71, Mar. 2021, doi: 10.3390/joitmc7010071.

A. A. Zaidan and B. B. Zaidan, “A review on Intelligent Process for Smart Home Applications Based on IoT: Coherent Taxonomy, Motivation, Open Challenges, and Recommendations,” Artif. Intell. Rev., vol. 53, no. 1, pp. 141–165, Jan. 2020, doi: 10.1007/s10462-018-9648-9.

U. Rahardja, T. Hariguna, and Q. Aini, “Understanding the Impact of Determinants in GameLearning Acceptance: An Empirical Study,” Int. J. Educ. Pract., vol. 7, no. 3, pp. 136–145, 2019, doi: 10.18488/journal.61.2019.73.136.145.

B. P. L. Lau et al., “A survey of data fusion in smart city applications,” Inf. Fusion, vol. 52, pp. 357–374, Dec. 2019, doi: 10.1016/j.inffus.2019.05.004.

Z. Allam and Z. A. Dhunny, “On big data, artificial intelligence and smart cities,” Cities, vol. 89, pp. 80–91, Jun. 2019, doi: 10.1016/j.cities.2019.01.032.

T. Yigitcanlar, L. Butler, E. Windle, K. C. Desouza, R. Mehmood, and J. M. Corchado, “Can Building ‘Artificially Intelligent Cities’ Safeguard Humanity from Natural Disasters, Pandemics, and Other Catastrophes? An Urban Scholar’s Perspective,” Sensors, vol. 20, no. 10, p. 2988, May 2020, doi: 10.3390/s20102988.

J. R. L. Arellano, K. I. Duarte, and R. R. Ruiz, “Innovation parks and their impact on competitiveness in northwestern México,” South Florida J. Dev., vol. 3, no. 3, pp. 3689–3696, Jun. 2022, doi: 10.46932/sfjdv3n3-052.

U. Rahardja, Q. Aini, P. A. Sunarya, D. Manongga, and D. Julianingsih, “The Use of TensorFlow in Analyzing Air Quality Artificial Intelligence Predictions PM2.5,” Aptisi Trans. Technopreneursh., vol. 4, no. 3, pp. 313–324, Oct. 2022, doi: 10.34306/att.v4i3.282.

J. J. Yun, X. Zhao, K. Jung, and T. Yigitcanlar, “The Culture for Open Innovation Dynamics,” Sustainability, vol. 12, no. 12, p. 5076, Jun. 2020, doi: 10.3390/su12125076.

A. Muzakir, H. Syaputra, and F. Panjaitan, “A Comparative Analysis of Classification Algorithms for Cyberbullying Crime Detection: An Experimental Study of Twitter Social Media in Indonesia,” Sci. J. Informatics, vol. 9, no. 2, pp. 133–138, Oct. 2022, doi: 10.15294/sji.v9i2.35149.

T. Yigitcanlar, R. Mehmood, and J. M. Corchado, “Green Artificial Intelligence: Towards an Efficient, Sustainable and Equitable Technology for Smart Cities and Futures,” Sustainability, vol. 13, no. 16, p. 8952, Aug. 2021, doi: 10.3390/su13168952.

A. Beltagui, A. Rosli, and M. Candi, “Exaptation in a Digital Innovation Ecosystem: The Disruptive Impacts of 3D Printing,” Res. Policy, vol. 49, no. 1, p. 103833, Feb. 2020, doi: 10.1016/j.respol.2019.103833.

L. Lämmle, E. von Lindern, D. Rummel, M. Michaeli, and M. Ziegler, “Shedding Light onto The City Blues Myth—The Potential of Stimulating and Activating Effects of Urban Public Spaces and the Role of City Relatedness,” Int. J. Environ. Res. Public Health, vol. 19, no. 13, p. 7606, Jun.2022, doi: 10.3390/ijerph19137606.

A. Das and P. Rad, “Opportunities and Challenges in Explainable Artificial Intelligence (XAI): A Survey,” arXiv, vol. 1, 2020, doi: https://doi.org/10.48550/arXiv.2006.11371.

S. Fatima, K. C. Desouza, and G. S. Dawson, “National strategic artificial intelligence plans: A multi-dimensional analysis,” Econ. Anal. Policy, vol. 67, pp. 178–194, Sep. 2020, doi: 10.1016/j.eap.2020.07.008.

B. W. Wirtz, J. C. Weyerer, and C. Geyer, “Artificial Intelligence and The Public Sector—Applications and Challenges,” Int. J. Public Adm., vol. 42, no. 7, pp. 596–615, May 2019, doi: 10.1080/01900692.2018.1498103.

wahyuningsih, N. N. Azizah, and T. Mariyanti, “Education and Technology Management Policies and Practices in Madarasah,” Int. Trans. Educ. Technol., vol. 1, no. 1, pp. 29–34, Nov. 2022, doi: 10.34306/itee.v1i1.177.

Po Abas Sunarya, Alexander Williams, Alfiah Khoirunisa, Adrian Sean Bein, and Delfi Martika Sari, “A Blockchain Based Online Business Intelligence Learning System,” Blockchain Front. Technol., vol. 1, no. 01, pp. 87–103, Jul. 2021, doi: 10.34306/bfront.v1i01.17.

T. Yigitcanlar, K. Desouza, L. Butler, and F. Roozkhosh, “Contributions and Risks of Artificial Intelligence (AI) in Building Smarter Cities: Insights from a Systematic Review of the Literature,” Energies, vol. 13, no. 6, p. 1473, Mar. 2020, doi: 10.3390/en13061473.

K. Kusrini et al., “Developing a Digital Scales System using Internet of Things Technology on Indonesia Digital Farm,” Sci. J. Informatics, vol. 10, 2023, [Online]. Available: https://journal.unnes.ac.id/nju/index.php/sji/article/view/40956.

N. Lutfiani, S. Wijono, U. Rahardja, A. Iriani, Q. Aini, and R. A. D. Septian, “A Bibliometric Study : Recommendation based on Artificial Intelligence for iLearning Education,” Aptisi Trans. Technopreneursh., vol. 5, no. 2, pp. 112–119, Nov. 2022, doi: 10.34306/att.v5i2.279.

A. Purwanto and L. P. Manik, “Software Effort Estimation Using Logarithmic Fuzzy Preference Programming and Least Squares Support Vector Machines,” Sci. J. Informatics, vol. 10, 2023, [Online]. Available: https://journal.unnes.ac.id/nju/index.php/sji/article/view/39865.

I. Amsyar, E. Cristhopher, U. Rahardja, N. Lutfiani, and A. Rizky, “Application of Building Workers Services in Facing Industrial Revolution 4.0,” Aptisi Trans. Technopreneursh., vol. 3, no. 1, pp. 32–41, Mar. 2021, doi: 10.34306/att.v3i1.117.

F. Fouad, “The Fourth Industrial Revolution is the AI Revolution An Academy Prospective,” Int. J. Inf. Syst. Comput. Sci., vol. 8, no. 5, pp. 155–167, Oct. 2019, doi: 10.30534/ijiscs/2019/01852019

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