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CySEC Unveils New Guidelines For ICT Loss Estimation Under Dora

The Cyprus Securities and Exchange Commission (CySEC) has taken a pivotal regulatory step by adopting new joint guidelines that require financial institutions to accurately estimate the aggregated annual costs and losses arising from significant information and communications technology (ICT) incidents. These measures, aligned with the Digital Operational Resilience Act (DORA Regulation), were set forth by the European Supervisory Authorities on July 17, 2024.

Regulatory Mandate and Industry Scope

Under Article 11(11) of the DORA Regulation, all financial entities under CySEC’s jurisdiction are now mandated to report aggregated annual losses from major ICT incidents. This comprehensive requirement covers a spectrum of market participants, including Cyprus Investment Firms, crypto-asset service providers, asset-referenced token issuers, central securities depositories, central counterparties, trading venues, alternative investment fund managers, management companies, and crowdfunding service providers authorized by CySEC.

Establishing Uniform Reporting Standards

The implemented guidelines aim to standardize the methodology for loss estimation by specifying a uniform framework and template for reporting. This initiative is designed to bolster the consistency and reliability of financial reporting and risk management across the board, ensuring that all regulated entities adhere to a common framework in quantifying operational digital risks.

Enhancing Digital Operational Resilience

Enshrined as Regulation (EU) 2022/2554, the DORA Regulation underscores the imperative for robust digital operational resilience within the financial sector. CySEC’s regulatory action reinforces the broader European initiative to enhance ICT oversight and fortify the industry’s ability to withstand digital disruptions, a move that is critical in today’s increasingly tech-dependent financial landscape.

Future Perspectives

As financial institutions begin to comply with these rigorous standards, the industry is poised to benefit from enhanced transparency and more effective risk mitigation. These measures not only safeguard the financial system against the evolving landscape of digital threats but also contribute to a more resilient and stable economic environment.

Copyright Law Struggles To Keep Up With AI Training

Courts Are Still Applying Old Copyright Rules To AI

AI companies train models on enormous amounts of published material, including books, articles and academic research. Whether using that content without authors’ permission violates copyright law remains unresolved.

Much of the debate centres on fair use, which allows copyrighted material to be used without permission in certain circumstances. Courts consider factors such as the purpose of the use, how much material was involved and its impact on the original market.

Anthropic Case Sets An Important Precedent

A major case involving Anthropic and a group of authors provided one of the clearest rulings so far. Judge William Alsup found that using copyrighted books to train AI models was lawful, comparing the process to people reading and studying literature before creating something new.

Anthropic was nevertheless ordered to pay $1.5 billion in a settlement. The penalty concerned books the company had obtained from illegal online libraries rather than the AI training itself.

For AI companies, that distinction could prove significant because it separates studying copyrighted material from directly copying it.

Competition Could Be The Key Issue

A case involving Thomson Reuters and Ross Intelligence offers a different perspective. A court ruled that Ross could not claim fair use after using Reuters’ copyrighted material to develop a competing AI-powered legal research platform.

The decision suggests courts may be less willing to consider AI training fair use when copyrighted content is used to build a product that directly competes with the original.

For authors, an unresolved question is whether AI-generated content should be considered competition for the works used to train these models.

The Law Has Yet To Catch Up

US copyright law predates generative AI by decades, leaving courts to apply old principles to new technology. Questions also remain over copyright protection for AI-generated works. In Thaler v. Perlmutter, a court ruled that material created entirely by AI cannot receive copyright protection.

Major AI companies remain involved in copyright litigation, and different courts could reach different conclusions. For now, there is no universal rule: the legality of AI training will depend on the circumstances of each case and how courts ultimately interpret copyright and fair use.

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