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Commissioner Advocates Stronger GDPR Safeguards In Tax Reform

Commissioner Maria Christofidou, the authoritative figure in personal data protection, has recently reiterated her support for the government’s ambitious tax reform measures. On both November 14 and November 21, she underscored the need for a balanced approach that safeguards citizens’ privacy while reinforcing the fiscal system.

Addressing Previous Concerns

Earlier, the Commissioner expressed worries about the excessive centralization of power within the Tax Department, a concern detailed in a recent analysis. Her latest recommendations echo these early concerns by emphasizing that any adoption of advanced artificial intelligence systems by the tax authority must be accompanied by robust data protection measures.

Integrating Safety Valves With Artificial Intelligence

The Commissioner is calling for the integration of explicit safety mechanisms within the legislative framework governing tax reform. This provision is critical to ensure that the collection, analysis, and processing of mass data—spanning both public and private sources—remain strictly aligned with the overarching principles of the General Data Protection Regulation (Gdpr). The proposed measures would mitigate risks of bias, discrimination, and potential infringements on individual privacy that could arise from algorithm-driven decision-making.

A Call For Transparent And Effective Governance

In her communication with the Parliamentary Committee on Finance, Christofidou welcomed the government’s initiatives aimed at curbing tax evasion and avoidance. However, she stressed that any legal framework established must be robust, transparent, and capable of balancing effective tax collection with stringent data protection standards. Central to this balance is the necessity for comprehensive data governance and mandatory impact assessments under Articles 35 and 36 of the Gdpr.

Legislative Timetable And Future Implications

The Commissioner further argued that the forthcoming tax reform legislation, particularly the Guarantee and Collection Act, should include a general provision that refers explicitly to the Gdpr. This measure is intended to ensure that all data collection and processing activities conducted by the tax authority are performed within an established regulatory framework that upholds legality, integrity, objectivity, transparency, and proportionality.

Additionally, she recommended that, should the Tax Department employ artificial intelligence systems in its operations, an in-depth data protection impact assessment must be completed. This proactive approach would provide a crucial safeguard both for the tax authority and any entity that contributes data, thereby bolstering confidence in the public administration’s handling of sensitive information.

Imminent Parliamentary Review

Simultaneously, deliberations continue in the Parliamentary Committee on Finance, where six draft bills are under discussion. Owing to time constraints, an emergency session has been scheduled for Thursday. In response to government directives, the legislature is expected to approve the tax reform initiative before year-end to facilitate its implementation by January 1, 2026. It is anticipated that the draft bills will be presented before the full Parliament during the first half of December.

The Commissioner’s remarks underscore the critical intersection of technological innovation and regulatory oversight in contemporary tax administration—a balance that will define the future of both fiscal policy and data privacy.

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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