Legal Responsibility in Systems without Human Decision Makers

Sumiyati Sumiyati

doi:10.59890/ijla.v4i1.160

Authors

Sumiyati Sumiyati Politeknik Negeri Bandung

DOI:

https://doi.org/10.59890/ijla.v4i1.160

Keywords:

Legal Responsibility, Autonomous Systems, Artificial Intelligence, Accountability

Abstract

The rapid development of artificial intelligence (AI) technology, autonomous systems, and algorithms that can make decisions without direct human intervention has raised significant new legal challenges. This study analyzes the construction of legal accountability in autonomous systems that operate without direct human decision-makers, focusing on challenges related to legal subjectivity, fault attribution, and responsibility mechanisms. Employing a juridical-normative and comparative law approach, the study demonstrates that traditional fault-based liability frameworks are increasingly inadequate when applied to algorithmic and AI-driven systems. The findings indicate an emerging shift toward risk-based liability models and the distribution of responsibility among actors involved in the design, development, and operation of autonomous systems. This research contributes to the reconceptualization of legal responsibility in the context of technological autonomy and provides normative guidance for the development of adaptive legal and regulatory frameworks.

References

Abbott, R. (2022). The reasonable computer: Disrupting the paradigm of tort liability. Georgetown Law Journal, 110(1), 1–50.

Ananny, M., & Crawford, K. (2020). Seeing without knowing: Limitations of the transparency ideal and its application to algorithmic accountability. New Media & Society, 22(1), 973–989. https://doi.org/10.1177/1461444816676645.

Binns, R. (2021). Algorithmic accountability and public reason. Philosophy & Technology, 34(3), 543–556. https://doi.org/10.1007/s13347-020-00404-5.

Bix, B. (2021). Legal theory: The foundations of law (5th ed.). Oxford University Press.

Black, J. (2021). Reconceiving financial markets—from the economic to the social. Journal of Corporate Law Studies, 21(1), 1–40. https://doi.org/10.1080/14735970.2021.1879543.

Brownsword, R. (2021). Law, technology, and society: Re-imagining the regulatory environment. Modern Law Review, 84(4), 719–744. https://doi.org/10.1111/1468-2230.12605.

Brownsword, R. (2023). Law 4.0: Rules, regulation and technology. Routledge.

Bryson, J. J., Diamantis, M. E., & Grant, T. D. (2021). Of, for, and by the people: The legal lacuna of synthetic persons. Artificial Intelligence and Law, 29(3), 273–291. https://doi.org/10.1007/s10506-021-09279-1.

Buitelaar, J. C., et al. (2022). Responsibility gaps in AI governance. AI & Society, 37(2), 657–668. https://doi.org/10.1007/s00146-021-01285-3.

Calo, R. (2021). Artificial intelligence policy: A primer and roadmap. UC Davis Law Review, 51(2), 399–435.

Calo, R., & Citron, D. K. (2021). The automated administrative state. University of Pennsylvania Law Review, 170(3), 797–843.

Calo, R., & Rosenblat, A. (2021). The taking economy: Uber, information, and power. Columbia Law Review, 121(6), 1623–1690.

Crootof, R. (2022). Autonomous weapon systems and accountability. Journal of International Criminal Justice, 20(1), 95–123. https://doi.org/10.1093/jicj/mqac001.

Custers, B., et al. (2025). Autonomous decision-making systems and liability gaps. Computer Law & Security Review, 51, 105893.

Drexl, J. (2021). Liability for artificial intelligence and the EU product liability regime. Journal of European Consumer and Market Law, 10(1), 20–28.

European Commission. (2021). Proposal for a regulation laying down harmonised rules on artificial intelligence (Artificial Intelligence Act). Brussels.

European Union. (2024). Regulation (EU) 2024/... Artificial Intelligence Act. Official Journal of the European Union.

Ferrari, V., et al. (2023). Risk-based liability in AI governance. Law, Innovation and Technology, 15(2), 289–314. https://doi.org/10.1080/17579961.2023.2189914.

Ferreira, A., & Sousa, N. (2022). Moral agency and artificial intelligence. Ethics and Information Technology, 24(1), 1–13. https://doi.org/10.1007/s10676-021-09603-5.

Floridi, L. (2023). Ethics, governance, and policies for AI. Springer.

Floridi, L., et al. (2021). AI governance: A blueprint for a global framework. Minds and Machines, 31(2), 259–270. https://doi.org/10.1007/s11023-021-09563-6.

Gless, S., & Dziobek, J. (2021). AI and criminal responsibility. Criminal Law Forum, 32(1), 1–24.

Gless, S., Silverman, E., & Weigend, T. (2022). If robots cause harm—Who is to blame? Criminal Law Review, 2022(4), 243–259.

Helberger, N., et al. (2020). Governing online platforms: From contested to cooperative responsibility. Information, Communication & Society, 23(12), 1789–1806.

Hevelke, A., & Nida-Rümelin, J. (2021). Responsibility for risks posed by artificial intelligence. Ethics and Information Technology, 23(3), 243–255.

Hildebrandt, M. (2022). Law for computer scientists and other folk. Oxford University Press.

Kahn, J. P. (2023). Distributed responsibility in AI systems. AI & Ethics, 3(1), 25–36. https://doi.org/10.1007/s43681-022-00185-4.

Li, F., et al. (2022). Autonomous systems and legal responsibility. Technology in Society, 69, 101971.

List, C., & Pettit, P. (2023). Group agency revisited. Oxford University Press.

Maras, M.-H. (2023). Artificial intelligence and legal responsibility. Journal of Law and Society, 50(2), 302–320.

McCrudden, C. (2020). Legal research and social science. Oxford Journal of Legal Studies, 40(4), 632–659.

OECD. (2022–2024). OECD AI principles: Implementation reports. OECD Publishing.

Pagallo, U. (2021). The laws of robots: Crimes, contracts, and torts. Artificial Intelligence and Law, 29(1), 1–20.

Pagallo, U., et al. (2022). Risk-based regulation of AI. Philosophy & Technology, 35(2), 1–19.

Power, M. (2023). The risk management of everything (Updated ed.). Demos.

Price, W. N. (2023). Regulating black-box medicine. Michigan Law Review, 121(4), 1–45.

Rammert, W., et al. (2021). Accountability in hybrid systems. Soziale Welt, 72(3), 271–290.

Saputra, A. (2025). Legal accountability of the autonomous system in Indonesian law. Journal of Law and Technology, 5(1), 1–25.

Selbst, A. D., & Barocas, S. (2021). The intuitive appeal of explainable machines. Fordham Law Review, 89(3), 1085–1139.

Veale, M., & Borgesius, F. Z. (2021). Demystifying the draft EU Artificial Intelligence Act. Computer Law Review International, 22(4), 97–112.

Veale, M., & Borgesius, F. Z. (2022). Regulating AI: Lessons from the EU. Harvard Journal of Law & Technology, 35(2), 1–45.

White House Office of Science and Technology Policy. (2022). Blueprint for an AI Bill of Rights. Washington, DC.

Winfield, A. F. T., & Jirotka, M. (2020). Ethical governance is essential to building trust in robotics and AI systems. Philosophical Transactions of the Royal Society A, 378(2180), 20190585.

Yeung, K. (2022). Algorithmic regulation. Regulation & Governance, 16(1), 1–20.

Zetzsche, D. A., et al. (2020). The future of data-driven regulation. European Business Organization Law Review, 21(3), 529–565.

Zhang, Y., & Chen, L. (2024). Machine learning opacity and legal accountability. AI & Society, 39(1), 113–126.