Risk-based ai regulatory reconstruction for legal certainty and digital rights protection in Indonesia
Main Article Content
Abstract
This study examines Indonesia's AI regulatory position through normative legal research, comparative regulatory analysis, and quantitative analysis of the AI Regulation Map using a 13 June 2026 snapshot. The comparison covers Indonesia and seven comparator jurisdictions, Singapore, South Korea, Japan, Spain, Italy, Sweden, and the United States, across Regulation Status, Policy Lever, Governance Type, Actor Involvement, and Enforcement Level. The findings indicate that Indonesia has lower scores than the comparator mean on the three normative dimensions used by the AI Regulation Map's Maturity Index, with gaps of 2.29 points for Regulation Status, 1.93 points for Policy Lever, and 1.54 points for Enforcement Level. Because the map is a derived indicator rather than a direct legal-validity or enforcement measure, the results are interpreted as comparative regulatory signals and are cross-checked against Indonesian and comparator primary legal sources. The normative reconstruction proposes a legal architecture that distinguishes enacted rules from guidance and draft instruments, classifies AI by risk, assigns proportionate obligations to relevant actors, embeds human oversight and digital-rights safeguards, and connects supervision with incident reporting, sanctions, and individual remedies.
Article Details
How to Cite
Primawati, D. S. . (2026). Risk-based ai regulatory reconstruction for legal certainty and digital rights protection in Indonesia. Journal of Law Science, 8(4), 330-344. https://doi.org/10.35335/jls.v8i4.7464
References
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Botero Arcila, B. (2025). AI Liability Along the Value Chain: Lessons from the Liability of Suppliers of Components in Product Liability Law. Journal of Tort Law, 18(1), 247–281. https://doi.org/10.1515/jtl-2025-0021
Buiten, M. C., De Streel, A., & Peitz, M. (2023). The law and economics of AI liability. Computer Law & Security Review, 48, 105794. https://doi.org/10.1016/j.clsr.2023.105794
Ebers, M. (2025). Truly Risk-based Regulation of Artificial Intelligence: How to Implement the EU’s AI Act. European Journal of Risk Regulation, 16(2), 684–703. https://doi.org/10.1017/err.2024.78
Enqvist, L. (2023). “Human oversight” in the EU artificial intelligence act: what, when and by whom? Law, Innovation and Technology, 15(2), 508–535. https://doi.org/10.1080/17579961.2023.2245683
Feldstein, S. (2024). Evaluating Europe’s push to enact AI regulations: how will this influence global norms? Democratization, 31(5), 1049–1066. https://doi.org/10.1080/13510347.2023.2196068
Gianni, R., Lehtinen, S., & Nieminen, M. (2022). Governance of Responsible AI: From Ethical Guidelines to Cooperative Policies. Frontiers in Computer Science, 4, 873437. https://doi.org/10.3389/fcomp.2022.873437
Government of Italy. (2025). Legge 23 September 2025, n. 132.
Government of Spain. (2024). Artificial Intelligence Strategy 2024.
Government Offices of Sweden. (2026). AI Strategy for Sweden.
Hani, A. A., Paserangi, H., & Cahyani, A. V. (2025). The Urgency of Regulation and Governance of Artificial Intelligence (AI) in Indonesian Finance: Comparison and Risk-Based Implementation. POLICY, LAW, NOTARY AND REGULATORY ISSUES, 4(4), 642–657. https://doi.org/10.55047/polri.v4i4.1901
Infocomm Media Development Authority (IMDA). (2024). Model AI Governance Framework.
Kajava, K., Gonzalez Torres, A. P., Rannisto, A., & Sakai, S. (2025). Justifying AI regulation: Examining multi-stakeholder responses to the AI Act. Telematics and Informatics, 99, 102278. https://doi.org/10.1016/j.tele.2025.102278
Laux, J., Wachter, S., & Mittelstadt, B. (2024). Trustworthy artificial intelligence and the European Union AI act: On the conflation of trustworthiness and acceptability of risk. Regulation & Governance, 18, 3–32. https://doi.org/10.1111/rego.12512
Lazcoz, G., & de Hert, P. (2023). Humans in the GDPR and AIA governance of automated and algorithmic systems: Essential pre-requisites against abdicating responsibilities. Computer Law & Security Review, 50, 105833. https://doi.org/10.1016/j.clsr.2023.105833
Mäntymäki, M., Minkkinen, M., Birkstedt, T., & Viljanen, M. (2022). Defining organizational AI governance. AI and Ethics, 2, 603–609. https://doi.org/10.1007/s43681-022-00143-x
Ministry of Economy, Trade and Industry (METI), & Ministry of Internal Affairs and Communications (MIC). (2024). {AI} Guidelines for Business, Version 1.0.
Mökander, J., & Floridi, L. (2022). From algorithmic accountability to digital governance. Nature Machine Intelligence, 4, 508–509. https://doi.org/10.1038/s42256-022-00504-5
Mökander, J., & Floridi, L. (2023). Operationalising AI governance through ethics-based auditing: an industry case study. AI and Ethics, 3, 451–468. https://doi.org/10.1007/s43681-022-00171-7
Monteiro, N., & Singh, V. (2025). The wheel of artificial intelligence governance. Sustainable Futures, 10, 101279. https://doi.org/10.1016/j.sftr.2025.101279
National Institute of Standards and Technology (NIST). (2023). Artificial Intelligence Risk Management Framework ({AI} RMF 1.0). https://doi.org/10.6028/NIST.AI.100-1
Noto La Diega, G., & Bezerra, L. C. T. (2024). Can there be responsible AI without AI liability? Incentivizing generative AI safety through ex-post tort liability under the EU AI liability directive. International Journal of Law and Information Technology, 32, eaae021. https://doi.org/10.1093/ijlit/eaae021
Novelli, C., Taddeo, M., & Floridi, L. (2024). Accountability in artificial intelligence: what it is and how it works. AI & SOCIETY, 39, 1871–1882. https://doi.org/10.1007/s00146-023-01635-y
Okuno, M. J., & Okuno, H. G. (2025). Legal frameworks for AI service business participants: a comparative analysis of liability protection across jurisdictions. AI & SOCIETY, 40, 5667–5683. https://doi.org/10.1007/s00146-025-02288-9
Papagiannidis, E., Enholm, I. M., Dremel, C., Mikalef, P., & Krogstie, J. (2023). Toward AI Governance: Identifying Best Practices and Potential Barriers and Outcomes. Information Systems Frontiers, 25, 123–141. https://doi.org/10.1007/s10796-022-10251-y
Paul, R. (2024). European artificial intelligence “trusted throughout the world”: Risk-based regulation and the fashioning of a competitive common AI market. Regulation & Governance, 18(4), 1065–1082. https://doi.org/10.1111/rego.12563
Porter, Z., Ryan, P., Morgan, P., Al-Qaddoumi, J., Twomey, B., Noordhof, P., McDermid, J., & Habli, I. (2025). Unravelling responsibility for AI. Journal of Responsible Technology, 23, 100124. https://doi.org/10.1016/j.jrt.2025.100124
Putra, R. K., Wardhani, L. T. A. L., Juchnevicius, E., & Leoni, S. (2025). Human Rights Protection in the Era of Artificial Intelligence: A Comparative Legal Analysis of Ethical Governance and Regulatory Frameworks. Discourse Journal on Law and Society, 1(2), 15–29. https://doi.org/10.70062/djls.v1i2.147
Putri, E., & Adinda, F. A. (2025). Artificial Intelligence, Digital Rights, and Human Dignity in Indonesia’s Tech Regulation. Contemporary Issues on Indonesian Human Rights Law and Policy, 2(1). https://doi.org/10.65815/5ef5c858
Ramadhan, M. S., Utama, M., Irsan, I., Anditya, A. W., & Aprita, S. (2024). Algorithmic Discrimination and the Challenges of Artificial Intelligence Regulation in Indonesia: A Pluralistic Justice Perspective. Jurnal Studi Sosial Dan Politik, 8(2), 158–173. https://doi.org/10.19109/jssp.v8i2.36617
Rangone, N., & Megale, L. (2025). Risks Without Rights? The EU AI Act’s Approach to AI in Law and Rule-Making. European Journal of Risk Regulation, 16(3), 1082–1097. https://doi.org/10.1017/err.2025.13
Republic of Indonesia. (2022). Law No. 27 of 2022 concerning Personal Data Protection. https://peraturan.bpk.go.id/Details/229798/uuno-27-tahun-2022
Republic of Korea. (2025). Framework Act on Development of Artificial Intelligence and Creation of Foundation for Trust.
Republic of Korea. (2026). Amendment to the Framework Act on Development of Artificial Intelligence and Creation of Foundation for Trust.
Schuett, J. (2024). Risk Management in the Artificial Intelligence Act. European Journal of Risk Regulation, 15(2), 367–385. https://doi.org/10.1017/err.2023.1
Stahl, B. C., Antoniou, J., Bhalla, N., Brooks, L., Jansen, P., Lindqvist, B., Kirichenko, A., Marchal, S., Rodrigues, R., Santiago, N., Warso, Z., & Wright, D. (2023). A systematic review of artificial intelligence impact assessments. Artificial Intelligence Review, 56(11), 12799–12831. https://doi.org/10.1007/s10462-023-10420-8
Sulistyantoro, G. T., Khaq, A., Khan, M. Z. K., Amin, A., & Hussain, A.-A.-M. (2024). Shaping Artificial Intelligence Governance and Risk Management in the Public Sector: Regulatory Insights. Lex Publica, 11(1). https://doi.org/10.58829/lp.11.1.2024.261
Trisnawati. (2024). Artificial Intelligence Governance and Regulation: A Roadmap to Developing Legal Policies for Artificial Intelligence Deployment. Journal of Governance and Administrative Reform, 5(2). https://doi.org/10.20473/jgar.v5i2.65194
Wang, X., Wu, Y. C., Ji, X., & Fu, H. (2024). Algorithmic discrimination: examining its types and regulatory measures with emphasis on US legal practices. Frontiers in Artificial Intelligence, 7, 1320277. https://doi.org/10.3389/frai.2024.1320277
Wirtz, B. W., Weyerer, J. C., & Kehl, I. (2022). Governance of artificial intelligence: A risk and guideline-based integrative framework. Government Information Quarterly, 39(4), 101685. https://doi.org/10.1016/j.giq.2022.101685
Zaidan, E., & Ibrahim, I. A. (2024). AI Governance in a Complex and Rapidly Changing Regulatory Landscape: A Global Perspective. Humanities and Social Sciences Communications, 11, 1121. https://doi.org/10.1057/s41599-024-03560-x
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