The emergence of artificial intelligence (AI) across global economies has redefined the contours of legal responsibility. While AI offers efficiency, prediction, and automation, it simultaneously introduces new forms of harm that traditional legal doctrines cannot easily accommodate. From biased algorithms in recruitment platforms to autonomous vehicles that misinterpret sensory data, the law faces a fundamental dilemma: who should bear the burden of error when harm arises from a decision made by a machine? This article explores this issue through the prism of the European Union’s AI Liability Directive and Bahrain’s Draft Artificial Intelligence Regulation Law, proposing a hybrid compensation model that reconciles innovation with justice.
In Bahrain and the wider GCC region, the legislative framework governing artificial intelligence is still in its infancy. Bahrain has, however, established itself as a regional pioneer through the Personal Data Protection Law (Law No. 30 of 2018), which provides mechanisms for compensation in cases of unlawful data processing. Although this law does not directly regulate AI, it offers a legal foundation for accountability where AI systems misuse or mishandle personal data. Moreover, the Draft Artificial Intelligence Regulation Law introduced in 2024 aims to institutionalize AI governance through licensing, administrative control, and civil liability provisions. This draft marks an important shift toward explicit regulation of algorithmic responsibility, signaling Bahrain’s readiness to align with international trends in AI ethics and accountability.
The European Union’s AI Liability Directive (2022 proposal, refined in 2024) offers a complementary perspective. It acknowledges that existing tort law principles, especially fault and causation—are insufficient when dealing with complex, autonomous systems. The Directive introduces procedural innovations, including an eased burden of proof for victims, a right to obtain disclosure of evidence from AI providers, and a presumption of causality when claimants can show that the AI malfunctioned and caused damage. These measures recognize the “black box” nature of AI systems, where algorithmic opacity makes it nearly impossible for ordinary users to demonstrate negligence in the traditional sense. Bahrain’s draft law follows a parallel logic by emphasizing the obligations of AI developers and deployers to maintain transparency, validation records, and safety assurance mechanisms. While the EU model seeks to integrate these principles within a mature civil liability regime, Bahrain’s initiative represents the first regional attempt to construct such a regime from the ground up.
Both systems share a normative core: a desire to balance innovation incentives with victim protection. Yet they diverge in structure and institutional design. The EU approach remains judicially driven, relying on courts to interpret liability under harmonized standards. Bahrain’s draft framework, by contrast, envisions a more administrative mechanism—potentially through a specialized AI authority—where liability, compensation, and compliance may be managed through licensing conditions and financial guarantees. This distinction reflects different regulatory philosophies: Europe’s is reactive and rights-based, whereas Bahrain’s is preventive and governance-oriented. In both cases, however, the goal is the same—to ensure that victims of AI-related harm are not left without remedy, while developers and innovators retain clarity about their legal exposure.
A sustainable approach for Bahrain and the GCC would therefore adopt a hybrid liability model inspired by both traditions. Such a model would include a no-fault compensation fund, financed by licensed AI providers and insurers, to handle straightforward cases where fault is indeterminable. Above this foundation, a rebuttable presumption of liability could be imposed on developers and deployers, shifting the burden of proof toward those best placed to control risk. Finally, traditional fault-based liability could be preserved for cases involving gross negligence or willful misconduct. This tripartite structure mirrors the European risk-based model while accommodating Bahrain’s administrative strengths. It would guarantee compensation to victims without paralyzing the innovation ecosystem that Bahrain is actively fostering under its Economic Vision 2030.
Ultimately, the future of AI regulation in Bahrain depends on the ability of lawmakers to merge the flexibility of regional governance with the precision of European legal reasoning. The proposed hybrid model ensures that compensation for algorithmic harm becomes both predictable and fair, while fostering accountability and technological trust. As Bahrain positions itself as a regional hub for ethical AI, adopting such a forward-looking liability framework will align national legislation with the global movement toward responsible and human-centered artificial intelligence.
Keywords: AI liability, algorithmic errors, compensation model, Bahrain AI law, EU AI directive, ethical AI, civil responsibility, AI regulation, data protection, legal framework, Gulf University (GU)
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