Alapfogalmak
The author explores the legal and regulatory implications of Generative AI, focusing on liability, privacy, intellectual property, and cybersecurity within the EU context. The paper identifies gaps in existing legislation and proposes recommendations for safe deployment of generative models.
Kivonat
The paper delves into the paradigm shift brought by Generative AI, particularly Large Language Models (LLMs), analyzing their impact on liability, privacy, intellectual property, and cybersecurity within the EU. It highlights challenges in predictability and legal compliance while proposing recommendations to ensure lawful deployment of generative models. The discussion covers liability concerns related to damage compensation for LLMs adoption obstacles and proposed regulatory frameworks like the Artificial Intelligence Act (AIA). Additionally, it addresses privacy issues arising from data processing by LLMs trained on personal data and potential violations under GDPR. The analysis extends to intellectual property challenges concerning copyright issues during LLM training using copyrighted materials or web scraping techniques. Recommendations include implementing opt-out tools for website owners to address IP concerns.
Statisztikák
33% of firms view “liability for damage” as the top external obstacle to AI adoption.
A new efficient liability regime may address concerns by securing compensation to victims.
Two recent EU regulatory proposals update Product Liability Directive (PLD) for defective products.
The Artificial Intelligence Liability Directive (AILD) introduces procedures for fault-based liability for AI-related damages.
PLD extended scope includes all AI systems except open-source software.
AILD covers claims against non-professional users of AI systems.
Both proposals introduce disclosure mechanisms shifting burden of proof to providers or deployers.
Idézetek
"The advent of Generative AI marks a paradigm shift in the landscape."
"LLMs exhibit multimodality handling diverse data formats."
"Concerns over lawfulness and accuracy arise from unpredictable outputs."