Artificial Intelligence & Legal Risk (The "Accountability" Era) скачать в хорошем качестве

Artificial Intelligence & Legal Risk (The "Accountability" Era)

In this video, we explore Artificial Intelligence & Legal Risk (The “Accountability” Era), offering a clear, structured, and practical examination of how liability, responsibility, and regulatory governance are evolving in response to increasingly autonomous AI systems. As AI transitions from supportive tools to agentic systems capable of independent decision-making, legal doctrine must address new challenges in contract, tort, fraud, enterprise risk, product liability, and regulatory compliance. We carefully explain how traditional legal principles—agency, negligence, product liability, vicarious liability, contractual authority, and enterprise risk—are being adapted to address AI-driven conduct. The video examines how courts and regulators attribute responsibility when AI systems negotiate contracts, generate misrepresentations, execute trades, make medical recommendations, or operate physical systems. We clarify how doctrines such as foreseeability, proximate cause, burden shifting, strict liability, and regulatory presumptions are increasingly central to AI-related disputes. Through comparative analysis, we examine how different jurisdictions are structuring AI governance. We reference the European Union’s risk-based regulatory model under the Artificial Intelligence Act, the litigation-driven and sectoral regulatory approach in the United States, the principles-based oversight framework advanced by the Financial Conduct Authority and other UK regulators, and emerging governance initiatives within Nigeria’s common law and digital finance ecosystem. Viewers will understand how regulatory compliance, civil liability, and enterprise accountability intersect across jurisdictions. The discussion outlines the layered architecture of AI liability: regulatory compliance at the foundational level; enterprise responsibility and risk internalization at the operational level; product liability exposure for developers and integrators; agency attribution for deployers; and insurance-backed compensation as a stabilizing mechanism. We demonstrate how liability is rarely singular and instead operates through overlapping doctrinal frameworks designed to distribute risk across multi-actor AI ecosystems. We also analyze key harm categories—contractual breach by AI agents, AI-generated misrepresentation and fraud, algorithmic trading instability, antitrust concerns involving algorithmic price convergence, physical injury from autonomous systems, and pure financial loss from automated decision errors. Particular attention is given to the doctrinal tension between fault-based negligence models and risk-based or strict liability regimes as AI autonomy increases. Special emphasis is placed on policy trade-offs. We examine how high-liability regimes may strengthen victim compensation but risk chilling innovation; how low-liability systems may encourage experimentation but create under-compensation and uncertainty; and how calibrated, moderate liability models seek equilibrium between innovation incentives and public protection. The video frames liability not merely as compensation, but as an instrument of technological governance shaping market incentives, institutional behavior, and societal values. What viewers will benefit from this video: A comprehensive understanding of how AI liability is structured across contract, tort, fraud, and regulatory law Insight into comparative AI governance models in the EU, United States, United Kingdom, and Nigeria Clarity on distributed causation, enterprise risk, and multi-actor accountability in AI ecosystems Structured analysis of fault-based, risk-based, and strict liability approaches to autonomous systems Practical guidance on applying AI liability principles in academic research, regulatory analysis, litigation strategy, and policy design A coherent framework for understanding AI accountability as a central pillar of modern legal risk management Whether you are a law student, researcher, regulator, policy analyst, technology professional, or legal practitioner, this video provides a systematic and forward-looking exploration of AI liability in the Accountability Era—integrating doctrine, regulation, comparative insight, and policy reflection into a unified analytical framework.