Public Sector Hiring Reforms Gain Union Support In Cyprus

by THEFUTURE.TEAM

April 20, 2026

Modernization Efforts Gain Union Approval

Civil service union Pasydy has endorsed three draft laws submitted to parliament to reform public sector recruitment. Union representatives noted that several previously proposed recommendations have been incorporated, particularly those aimed at updating procedures and addressing long-standing inefficiencies.

Streamlined Recruitment Process

Finance Minister Makis Keravnos is leading the reform effort, with a focus on reducing the time required to secure permanent public sector positions. Stratis Mattheou, general secretary of Pasydy, stated that the proposed changes aim to align recruitment more closely with departmental needs. Candidates will receive clearer information about available roles and requirements before sitting examinations, which often involve additional costs.

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Addressing Systemic Shortcomings

Existing recruitment procedures have been widely criticized for inefficiency and lack of transparency. Applicants have frequently faced uncertainty regarding the positions linked to examinations, sometimes incurring unnecessary expenses due to misaligned applications. Concerns have also been raised by departmental leadership regarding delays and administrative complexity.

Key Legislative Changes

Three bills form the core of the reform package: the Evaluation of Candidates for Appointment to the Public Service Law of 2026, the Public Service (Amendment) Law of 2026, and the Evaluation of Candidates for Appointment to the Public Service (Temporary Provisions) Law of 2026.

Approved by the cabinet on April 8 and submitted to parliament, the proposals introduce several structural changes:

Transition from pre-announced to post-announced written examinations, allowing candidates to identify vacancies before preparing
Publication of vacancies within the first two months of each year to accelerate recruitment timelines
Removal of the annual requirement to submit lists of positions requiring written exams, with authority shifting to the Public Service Commission
Increased weighting of departmental head evaluations during the oral examination stage

Ongoing Commitment To Improvement

Pasydy indicated it will continue reviewing the proposals and may submit further recommendations during parliamentary discussions. Reforms are expected to improve efficiency, reduce administrative delays, and create a more transparent and candidate-focused recruitment system.

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Copyright Law Struggles To Keep Up With AI Training

by News Editor

August 24, 2026

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.

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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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