Generative AI policy updated by Australian Research Council

The Australian Research Council has updated its policy on the use of generative AI in its grants programmes, setting out how the rules apply to applicants, administering organisations, and assessors in the National Competitive Grants Program.

The revised policy has officially taken effect and applies to applications and assessments for Discovery Indigenous 2027 and all scheme rounds opening after that date.

The policy says applicants may use generative AI tools to support tasks such as testing ideas, improving language, and summarising text, but remain responsible for the content they submit and are considered the authors of that content.

Administering organisations are also responsible for ensuring that applications are complete, accurate, and free from false or misleading information, while delegated research leaders must certify that participants are responsible for the authorship and intellectual content of applications and that they have not infringed the intellectual property rights of others.

A notable change in the revised policy is that assessors are now permitted to use generative AI tools in limited ways. The ARC says assessors may use AI only to correct or improve grammar, spelling, formatting, and the readability of drafted assessments.

At the same time, the policy states that assessors must not use AI to help form an opinion on the quality of an application and must preserve the confidentiality of all application materials. Inputting any application material into public generative AI tools such as ChatGPT, Gemini, Claude, or Perplexity is described by the ARC as a serious breach of confidentiality and is not permitted.

The ARC also says assessors will be asked about their use of AI and must be transparent when requested. Where assessors’ inappropriate use of generative AI is suspected, the ARC may remove that assessment from the process. If a breach is established following investigation, the ARC may impose consequential actions in addition to any imposed by the assessor’s employing institution.

The revised policy explains that its approach is shaped by concerns including intellectual integrity and authorship, safeguarding intellectual property, culturally appropriate use of data, content reliability and bias, human oversight and expert judgement, and energy and environmental impacts. It also states that the ARC will continue to monitor developments in generative AI and update the policy as required.

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Azerbaijan explores regulatory framework for AI and intellectual property

Azerbaijani lawmakers and experts discussed the legal status of AI systems and their implications for intellectual property (IP) at a policy roundtable in Baku, Trend News Agency reported.

Speaking at the event marking World Intellectual Property Day, Member of the Azerbeijani Parliament Hijran Huseynova said that defining the legal nature of AI remains a key issue as the technology advances.

Participants highlighted differing views on whether AI should be treated as a legal entity or regarded solely as a tool. While some experts argued that AI lacks independent legal standing, others suggested that its ability to make autonomous decisions requires deeper legal examination.

The discussion also addressed whether outputs generated by AI systems can qualify for patent protection, an issue that remains under debate in many jurisdictions.

Huseynova noted that the growing use of AI is raising complex questions about ownership and rights, as traditional intellectual property frameworks are based on human creativity.

Why does it matter?

The debate comes as Azerbaijan advances its national AI strategy for 2025–2028, which includes efforts to establish legal and institutional frameworks for the development and regulation of AI technologies. Officials say these measures aim to address emerging legal challenges and support the responsible adoption of AI as part of the country’s broader digital transformation agenda.

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Georgia hosts EPO talks on patents and technology transfer

European Patent Office President António Campinos visited Tbilisi for high-level meetings and a joint conference with Georgia’s National Intellectual Property Center, Sakpatenti, focused on the role of patents in technology transfer.

During the visit, Campinos met Georgia’s Minister of Education, Science and Youth, Givi Mikanadze. Discussions covered the contribution of patent systems to economic development, innovation policy, international technology cooperation, and Georgia’s alignment with European patent practices.

The meetings also highlighted cooperation between the European Patent Office and Sakpatenti, including Georgia’s validation agreement with the EPO, which the statement says has resulted in more than 300 validation requests in two years. Mikanadze said:

The validation agreement supports IP development in Georgia by establishing an environment where knowledge transforms into innovation.

At the conference, titled ‘From Research to Impact: The Role of Patents in Technology Transfer’, Campinos said:

Technology transfer, foreign investment, and the development of new technologies depend on strong research, skilled intellectual property professionals, and solid legal frameworks. Patents and our validation agreement, by providing legal certainty, predictability, and clear professional standards, support researchers, universities, businesses of all sizes, and individual inventors in moving ideas from the laboratory to the market.

The programme also addressed professional qualifications and patent skills, with the EPO highlighting certification frameworks such as the European Qualifying Examination and the European Patent Administration Certification.

Why does it matter?

Stronger patent cooperation can affect how easily research moves into commercial use, how attractive a market is for technology investment, and how predictable protection is for innovators operating across borders. In Georgia, the validation agreement is presented as part of a broader effort to strengthen the country’s innovation ecosystem and its links with European patent practice.

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YouTube expands AI deepfake detection tools for celebrities

The expansion of its likeness detection technology to the entertainment industry has been announced by YouTube, extending access beyond content creators to talent agencies, management companies and the individuals they represent.

The move is part of a broader effort by the platform to address the growing misuse of AI to generate misleading or unauthorised videos of public figures. By extending the tool to entertainment industry stakeholders, YouTube is signalling that AI-driven impersonation is no longer treated as a niche creator issue but as a broader identity and rights problem.

The system works in a way broadly comparable to Content ID, allowing eligible users to identify videos that use AI to replicate a person’s face or likeness. Once such content is detected, individuals can request its removal through YouTube’s existing privacy complaint process.

The rollout has been developed with input from major industry players, including Creative Artists Agency, United Talent Agency, William Morris Endeavor, and Untitled Management. Those partnerships are intended to help YouTube refine how the system works in practice and ensure it reflects the needs of artists and rights holders dealing with synthetic media.

Importantly, access to the tool is not limited to people who actively run YouTube channels. Celebrities and public figures can use it even without a direct creator presence on the platform, extending its reach across a much broader part of the entertainment ecosystem.

The significance of the update lies in how platforms are beginning to treat AI impersonation as a governance issue rather than merely a content-moderation problem.

As synthetic media tools become easier to use and more convincing, technology companies are under growing pressure to provide faster and more credible mechanisms for detecting misuse, protecting identity rights, and limiting deceptive content.

YouTube’s latest move shows that platform responses are becoming more structured and rights-based, especially in sectors where a person’s likeness is closely tied to reputation, image, and commercial value. The bigger question now is whether such tools will prove effective enough to keep pace with the scale and speed of AI-generated impersonation online.

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EU updates technology licensing competition rules to reflect data and digital markets

The European Commission has adopted revised rules governing technology transfer agreements (Technology Transfer Block Exemption Regulation and Guidelines on the application of Article 101 of the Treaty to technology transfer agreements), updating a framework originally introduced in 2014.

These changes aim to reflect developments in the digital economy, particularly the growing role of data and standardised technologies in enabling interoperability across markets.

Technology transfer agreements allow firms to license intellectual property such as patents, software and design rights, supporting the dissemination of innovation. While such agreements are often considered pro-competitive, they may also create risks if they restrict market access or distort competition.

The revised framework clarifies how these agreements are assessed under Article 101 of the Treaty on the Functioning of the European Union.

The updated rules introduce specific guidance on data licensing and licensing negotiation groups, addressing new market practices.

They also refine conditions under which agreements benefit from exemptions, including simplified criteria for early-stage technologies and clearer safeguards for technology pools linked to industry standards.

Overall, the revision by the EU seeks to improve legal certainty for businesses while ensuring that licensing practices support innovation, competition and the broader functioning of the single market. The new framework will apply from May 2026.

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EU advances AI copyright safeguards through GPAI taskforce discussions

The European Commission has convened the second meeting of the Signatory Taskforce under the General-Purpose AI Code of Practice (GPAI), focusing on copyright protection in AI systems.

The discussion brought together signatories to exchange early implementation practices and technical approaches.

Participants examined methods to reduce copyright risks in AI-generated outputs, highlighting measures applied across the model’s lifecycle, including data selection, training, and deployment.

Emphasis was placed on combining technical safeguards with organisational processes to improve transparency and effectiveness.

One approach presented involved training models on licensed content alongside attribution systems to identify similarities between generated outputs and source material. Such a method aims to support fair remuneration and strengthen accountability within AI development.

The meeting also addressed mechanisms for handling complaints from rights holders, with participants discussing procedures for accessible and timely responses.

An exchange that forms part of ongoing EU efforts to refine governance standards for AI systems and copyright compliance.

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China sets standards for AI ethics review and algorithm accountability

The introduction of new AI ethics guidelines by China signals a structured attempt to formalise governance frameworks for rapidly expanding AI systems.

Coordinated by the Ministry of Industry and Information Technology of the People’s Republic of China and multiple state bodies, the policy integrates ethical oversight directly into technological development processes.

A central feature of the framework is the emphasis on operationalising ethical principles such as fairness, accountability, and human well-being through technical review mechanisms.

By focusing on data selection, algorithmic design, and system architecture, the guidelines move towards embedding ethical safeguards at the development stage and protecting intellectual property rights in AI ethics review technologies.

Such an approach reflects a broader shift towards anticipatory governance, where risks such as bias, discrimination, and algorithmic manipulation are addressed before deployment.

A policy by China that also highlights the role of infrastructure in ethical governance, including the development of auditing tools, risk assessment systems, and curated datasets.

Scenario-based evaluation mechanisms indicate an effort to tailor oversight to specific use cases, recognising that AI risks vary significantly across sectors. Instead of relying solely on static compliance rules, the framework promotes adaptive governance aligned with technological complexity.

Ultimately, the outcome is a governance model that seeks to maintain technological competitiveness while addressing societal risks, contributing to wider global debates on how states can regulate AI systems without constraining their development.

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Penguin Random House sues OpenAI for copyright infringement over ‘Coconut the Little Dragon’ series in Germany

Penguin Random House has filed a lawsuit against OpenAI, alleging that its chatbot, ChatGPT, infringed copyright by imitating content from the ‘Coconut the Little Dragon’ series by German author Ingo Siegner. Filed in a Munich court, the complaint targets OpenAI’s European subsidiary, citing the chatbot’s creation of text, a book cover, and a promotional blurb as evidence of unauthorised ‘memorisation’ of Siegner’s work.

This issue highlights the challenge of distinguishing between algorithmic learning and direct copying, as AI models like OpenAI’s large language model (LLM) can retain extensive portions of their training data and reproduce them, raising legal and ethical dilemmas.

Penguin Random House insists that protecting human creativity is central to its mission. Carina Mathern, a representative, stressed the importance of safeguarding intellectual property, even as the company acknowledges the potential benefits of AI.

That reflects a broader industry tension between embracing technological innovation and protecting authors’ rights. The lawsuit’s implications could set a precedent affecting how AI-generated content is treated under intellectual property laws, posing significant questions for the publishing and creative industries.

The case against OpenAI is not isolated. A Munich court previously ruled against the company for using lyrics from popular musicians without permission, underscoring ongoing legal challenges around AI-generated content in Germany.

Bertelsmann, the parent company of Penguin Random House, had a prior agreement with OpenAI but did not allow access to its media archives, illustrating the complexities of AI collaboration while safeguarding proprietary content. OpenAI responded by stating that they are reviewing the allegations, reiterating their respect for creators and maintaining dialogue with publishers worldwide.

Why does it matter?

The resolution of this lawsuit could mark a pivotal moment in defining AI’s role in creative industries, shaping future regulations and enforcement strategies for AI-driven content creation and its impact on intellectual property rights globally.

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Will AI turn novel-writing into a collaborative process

The article argues that a novel’s value cannot be judged solely by the quality of its prose, because many readers respond to other elements such as premise, ideas and character. It points to Amazon reviews of ‘Shy Girl’, which holds a four-out-of-five-star rating based on hundreds of reviews, with many praising its hook despite awareness of ‘the controversy’ around it. One reviewer writes, ‘The premise sucked me in.’

The broader point is that plenty of novels are poorly written yet still succeed, because fiction, like music, is forgiving: a song may have an irresistible beat even with a predictable melody, and a book can move readers through suspense, beauty, realism, fantasy, or a protagonist they recognise in themselves.

From that premise, the piece asks whether fiction’s ‘layers’ (premise, plot, style and voice) must all come from a single person. It notes that collaborative creation is already normal in many fields, even if audiences rarely state their expectations explicitly: readers tend to assume a Booker Prize-winning novel is written entirely by the named author, while journalism is understood to be shaped by both writers and editors, and television and film are widely accepted as writers’ room and revision-heavy processes.

The article uses James Patterson as an example of industrial-scale collaboration in publishing, describing how he supplies collaborators with outlines and treatments and oversees many projects at once, an approach likened to a ‘novel factory’ that some argue distances him from ‘literary fiction’, yet may be the only practical way to sustain a decades-long series.

The author suggests AI will make such factories easier to create, citing a New York Times report on ‘Coral Hart’, a pseudonymous romance writer who uses AI to generate drafts in about 45 minutes, then revises them before self-publishing hundreds of books under dozens of names. Although not a bestseller, she reportedly earns ‘six figures’ and teaches others to do the same.

This points to a future in which authors act more like showrunners supervising AI-powered writers’ rooms, while raising a central risk: readers may not know who, or what, produced what they are reading, especially if AI use is not consistently disclosed despite platforms such as Amazon asking for it.

The piece ends by questioning whether AI necessarily implies high-volume, depersonalised production. Using a personal analogy from music-making, the author notes that technology can enable rapid output, but can also serve a more artistic purpose: helping a creator overcome technical limits and ‘realise a vision’.

Why does it matter?

The underlying argument is not that AI guarantees either shallow churn or genuine creativity, but that the most consequential issues may lie in intent, authorial expectations, and honest disclosure to readers.

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Digital Services Act agreement links European Commission and EUIPO on online IP enforcement

The European Commission and the European Union Intellectual Property Office (EUIPO) have signed a five-year agreement under which the latter will provide technical support and intellectual property expertise for work under the Digital Services Act. The cooperation focuses on online infringements of intellectual property rights, in particular the sale of counterfeit goods and the distribution of pirated content.

The EUIPO will support the oversight of the European Commission’s Very Large Online Platforms and Very Large Online Search Engines. That work will include analysing internal reports submitted by those services on how they address online intellectual property infringement.

An agreement with the European Commission includes training for national authorities that enforce the Digital Services Act. It also supports the European Board for Digital Services by contributing to discussions in its working groups on intellectual property.

The EUIPO will also help build expertise among judicial authorities, intellectual property right holders, and smaller online intermediaries, and contribute to a shared collection of best practices and tools.

However, this agreement is linked to the Digital Services Act framework, under which online intermediaries are required to provide notice-and-action mechanisms for illegal content, and Very Large Online Platforms and Very Large Online Search Engines are subject to additional risk-assessment and mitigation obligations.

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