This paper examines the rise of algorithmic harms from AI, such as privacy erosion and inequality, exacerbated by accountability gaps and algorithmic opacity. It critiques existing legal frameworks in the US, EU, and Japan as insufficient, and proposes refined impact assessments, individual rights, and disclosure duties to enhance AI governance and mitigate harms.
The paper examines the EU AI Act's impact on banking supervision, highlighting the ECB's role. It discusses legal frameworks, obligations for high-risk AI systems, AI governance, and the balance between innovation and prudential requirements. Strategic policy recommendations are provided to enhance oversight and financial system integrity.
“... we argue there are good reasons for skepticism, as many of its key operative provisions delegate critical regulatory tasks to AI providers themselves, without adequate oversight or redress mechanisms. Despite its laudable intentions, the AI Act may deliver far less than it promises.”
“... we analyse the regulatory necessity in introducing a coercive regulatory framework, and second, present the regulatory concept of the AI Act with its fundamental decisions, core provisions and risk typology. Lastly, a critical analysis points to shortcomings, tensions and watered down assessments of the Act.”
“... the paper analyses (i) how the AI Act should be applied and implemented according to its original intention of a risk-based approach, (ii) how the AI Act should be complemented by sector-specific legislation in the future to avoid inconsistencies and over-regulation, and (iii) what lessons legislators around the world can learn from the AI Act in regulating AI.”
“This paper discusses and analyses the regulatory approach underlying the AI Act, the main issues surrounding the proposed regulation, and the implications for the AI Act's ability to achieve its goals.”
“This paper provides a comprehensive analysis of the recent EU AI Act, the regulatory framework surrounding Artificial Intelligence (AI), focusing on foundation models, open-source exemptions, remote biometric identification (RBI), copyright, high-risk classification, innovation, and the implications for fundamental rights and employment.”
The AI Act, initially overlooking multifunctional AI like foundation models, led to debates. Industry sought exemption, civil groups pushed for inclusion, foreseeing safety gaps and burdens on users. "General Purpose AI systems" (GPAIS) emerged in discussions, aiming to extend Act requirements to adaptable models, addressing operator responsibility. Current debate focuses on adapting the Act to cover these advanced AI, revealing its initial limitations. The paper will delve into this evolution, highlighting challenges and proposing policy adjustments for GPAIS regulation within the AI Act's framework.
Determining liability for AI-caused harm lacks clear answers. In cases involving Tesla autopilot accidents, unfair discrimination by AI in HR, or medical procedures, responsibility is blurry. The EU's proposed AI liability regime and AI Act aim to address these complexities, bridging gaps in risk regulation and liability for AI-human interactions.