Legal Transformation of Artificial Intelligence Technology to Strike a Balance Between Law and Technology
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Indonesia, Legal Certainty, Online Motorcycle Taxis, Public Transportation, Transportation Policy
Abstract
Background: Artificial Intelligence (AI) is transforming various sectors globally, including business and healthcare. In Indonesia, this transformation is supported by initiatives like the Palapa Ring project and 5G infrastructure. However, the rapid growth of AI poses legal and ethical challenges. Current regulations, such as the Personal Data Protection Act, are insufficient to address the complexities of AI technology, creating a gap between legal frameworks and technological advancements.
Objective: This study aims to identify the gaps in Indonesia’s AI-related legal frameworks and propose strategies for balancing the development of law and technology to ensure ethical and accountable AI integration.
Methodology: Using a normative legal research approach, the study examines existing AI-related legal frameworks, compares international regulations, and analyzes their implications for Indonesia.
Findings: The study reveals that while online motorcycle taxis contribute significantly to the transportation sector, current legislation does not fully recognize them as legitimate public transport providers. This gap affects passenger protection and the certainty of service standards.
Conclusion: To ensure safety, reliability, and legal clarity, it is imperative to establish a comprehensive legal framework that formally categorizes online motorcycle taxis as recognized public transportation.
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References
Ahmed, I., Jeon, G., & Piccialli, F. (2022). From Artificial Intelligence to Explainable Artificial Intelligence in Industry 4.0: A Survey on What, How, and Where. IEEE Transactions on Industrial Informatics, 18(8), 5031–5042. https://doi.org/10.1109/TII.2022.3146552
Ali, S., Abuhmed, T., El-Sappagh, S., Muhammad, K., Alonso-Moral, J. M., Confalonieri, R., Guidotti, R., Del Ser, J., Díaz-Rodríguez, N., & Herrera, F. (2023). Explainable Artificial Intelligence (XAI): What we know and what is left to attain Trustworthy Artificial Intelligence. Information Fusion, 99, 101805. https://doi.org/10.1016/j.inffus.2023.101805
Ameen, N., Tarhini, A., Reppel, A., & Anand, A. (2021). Customer experiences in the age of artificial intelligence. Computers in Human Behavior, 114, 106548. https://doi.org/10.1016/j.chb.2020.106548
Barredo Arrieta, A., Díaz-Rodríguez, N., Del Ser, J., Bennetot, A., Tabik, S., Barbado, A., Garcia, S., Gil-Lopez, S., Molina, D., Benjamins, R., Chatila, R., & Herrera, F. (2020). Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI. Information Fusion, 58, 82–115. https://doi.org/10.1016/j.inffus.2019.12.012
Bragazzi, N. L., Dai, H., Damiani, G., Behzadifar, M., Martini, M., & Wu, J. (2020). How Big Data and Artificial Intelligence Can Help Better Manage the COVID-19 Pandemic. International Journal of Environmental Research and Public Health, 17(9), 3176. https://doi.org/10.3390/ijerph17093176
Briganti, G., & Le Moine, O. (2020). Artificial Intelligence in Medicine: Today and Tomorrow. Frontiers in Medicine, 7, 27. https://doi.org/10.3389/fmed.2020.00027
Chen, L., Chen, P., & Lin, Z. (2020). Artificial Intelligence in Education: A Review. IEEE Access, 8, 75264–75278. https://doi.org/10.1109/ACCESS.2020.2988510
Deng, S., Zhao, H., Fang, W., Yin, J., Dustdar, S., & Zomaya, A. Y. (2020). Edge Intelligence: The Confluence of Edge Computing and Artificial Intelligence. IEEE Internet of Things Journal, 7(8), 7457–7469. https://doi.org/10.1109/JIOT.2020.2984887
Glikson, E., & Woolley, A. W. (2020). Human Trust in Artificial Intelligence: Review of Empirical Research. Academy of Management Annals, 14(2), 627–660. https://doi.org/10.5465/annals.2018.0057
Hao, M., Li, H., Luo, X., Xu, G., Yang, H., & Liu, S. (2020). Efficient and Privacy-Enhanced Federated Learning for Industrial Artificial Intelligence. IEEE Transactions on Industrial Informatics, 16(10), 6532–6542. https://doi.org/10.1109/TII.2019.2945367
Hwang, G.-J., & Chien, S.-Y. (2022). Definition, roles, and potential research issues of the metaverse in education: An artificial intelligence perspective. Computers and Education: Artificial Intelligence, 3, 100082. https://doi.org/10.1016/j.caeai.2022.100082
Jamshidi, M., Lalbakhsh, A., Talla, J., Peroutka, Z., Hadjilooei, F., Lalbakhsh, P., Jamshidi, M., Spada, L. L., Mirmozafari, M., Dehghani, M., Sabet, A., Roshani, S., Roshani, S., Bayat-Makou, N., Mohamadzade, B., Malek, Z., Jamshidi, A., Kiani, S., Hashemi-Dezaki, H., & Mohyuddin, W. (2020). Artificial Intelligence and COVID-19: Deep Learning Approaches for Diagnosis and Treatment. IEEE Access, 8, 109581–109595. https://doi.org/10.1109/ACCESS.2020.3001973
Janssen, M., Brous, P., Estevez, E., Barbosa, L. S., & Janowski, T. (2020). Data governance: Organizing data for trustworthy Artificial Intelligence. Government Information Quarterly, 37(3), 101493. https://doi.org/10.1016/j.giq.2020.101493
Laguarta, J., Hueto, F., & Subirana, B. (2020). COVID-19 Artificial Intelligence Diagnosis Using Only Cough Recordings. IEEE Open Journal of Engineering in Medicine and Biology, 1, 275–281. https://doi.org/10.1109/OJEMB.2020.3026928
Lee, D., & Yoon, S. N. (2021). Application of Artificial Intelligence-Based Technologies in the Healthcare Industry: Opportunities and Challenges. International Journal of Environmental Research and Public Health, 18(1), 271. https://doi.org/10.3390/ijerph18010271
Letaief, K. B., Shi, Y., Lu, J., & Lu, J. (2022). Edge Artificial Intelligence for 6G: Vision, Enabling Technologies, and Applications. IEEE Journal on Selected Areas in Communications, 40(1), 5–36. https://doi.org/10.1109/JSAC.2021.3126076
Ma, Y., Wang, Z., Yang, H., & Yang, L. (2020). Artificial intelligence applications in the development of autonomous vehicles: A survey. IEEE/CAA Journal of Automatica Sinica, 7(2), 315–329. https://doi.org/10.1109/JAS.2020.1003021
Nishant, R., Kennedy, M., & Corbett, J. (2020). Artificial intelligence for sustainability: Challenges, opportunities, and a research agenda. International Journal of Information Management, 53, 102104. https://doi.org/10.1016/j.ijinfomgt.2020.102104
Shneiderman, B. (2020). Human-Centered Artificial Intelligence: Reliable, Safe & Trustworthy. International Journal of Human–Computer Interaction, 36(6), 495–504. https://doi.org/10.1080/10447318.2020.1741118
Singh, S. K., Rathore, S., & Park, J. H. (2020). BlockIoTIntelligence: A Blockchain-enabled Intelligent IoT Architecture with Artificial Intelligence. Future Generation Computer Systems, 110, 721–743. https://doi.org/10.1016/j.future.2019.09.002
Tjoa, E., & Guan, C. (2021). A Survey on Explainable Artificial Intelligence (XAI): Toward Medical XAI. IEEE Transactions on Neural Networks and Learning Systems, 32(11), 4793–4813. https://doi.org/10.1109/TNNLS.2020.3027314
Tussyadiah, I. (2020). A review of research into automation in tourism: Launching the Annals of Tourism Research Curated Collection on Artificial Intelligence and Robotics in Tourism. Annals of Tourism Research, 81, 102883. https://doi.org/10.1016/j.annals.2020.102883
Vaishya, R., Javaid, M., Khan, I. H., & Haleem, A. (2020). Artificial Intelligence (AI) applications for COVID-19 pandemic. Diabetes & Metabolic Syndrome: Clinical Research & Reviews, 14(4), 337–339. https://doi.org/10.1016/j.dsx.2020.04.012
Vrontis, D., Christofi, M., Pereira, V., Tarba, S., Makrides, A., & Trichina, E. (2022). Artificial intelligence, robotics, advanced technologies and human resource management: A systematic review. The International Journal of Human Resource Management, 33(6), 1237–1266. https://doi.org/10.1080/09585192.2020.1871398
Yang, H., Alphones, A., Xiong, Z., Niyato, D., Zhao, J., & Wu, K. (2020). Artificial-Intelligence-Enabled Intelligent 6G Networks. IEEE Network, 34(6), 272–280. https://doi.org/10.1109/MNET.011.2000195
Zhang, L., & Zhang, L. (2022). Artificial Intelligence for Remote Sensing Data Analysis: A review of challenges and opportunities. IEEE Geoscience and Remote Sensing Magazine, 10(2), 270–294. https://doi.org/10.1109/MGRS.2022.3145854
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Copyright (c) 2024 Francisca Romana Nanik Alfiani, Faisal Santiago
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