Digital standards Archives | Page 3 of 394

Australian audit highlights governance gaps in public-sector AI

The Australian National Audit Office has found that IP Australia’s use of AI in the patent rights process is largely effective, while calling for stronger cybersecurity governance, monitoring and strategic oversight.

Auditor-General Report No. 43 of 2025–26 examined whether IP Australia has effective arrangements to support AI adoption in the patent rights process. IP Australia administers intellectual property rights, including patents, trade marks, design rights and plant breeders’ rights.

The agency deployed its first AI tool for patent examination in 2018 and now uses four AI tools in the process. The tools are designed to provide examiners with information to support better decisions, rather than to decide patent applications themselves.

The ANAO said IP Australia has been an early adopter of AI and has progressively improved its governance arrangements. The agency has introduced an AI governance policy, risk-scaled assessment mechanisms and clearer enterprise accountability roles.

However, the audit found that strategic oversight of AI implementation and related benefits is not yet fully established. It said IP Australia’s AI inventory, committee roles and use-case ownership remain works in progress.

Monitoring and reporting were assessed as only partly effective. The ANAO said benefits have been inconsistently defined and measured, making it harder to demonstrate the ongoing effectiveness of AI tools and manage emerging risks.

The ANAO made two recommendations, urging IP Australia to review cybersecurity governance controls for AI and establish clearer risk-based monitoring and reporting arrangements. IP Australia agreed to both recommendations.

The audit said public-sector agencies should regularly reassess AI governance frameworks as they move from experimentation to wider use.

Why does it matter?

The audit shows how AI is moving from experimentation into routine public-sector decision support. IP Australia’s experience points to the benefits of AI in improving efficiency and quality, but also shows that governance must evolve as tools become embedded in official processes. Cybersecurity, accountability, monitoring and measurable benefits are becoming central to responsible AI use in government.

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Spain calls for stronger AI rules in labour relations

Spain’s Second Vice President and Minister of Labour and Social Economy, Yolanda Díaz, has called for stronger regulation of AI and algorithmic decision-making in the workplace.

Speaking at the University of Oxford, Díaz said the debate should no longer focus on whether AI should be used, but on how to organise its deployment so that labour rights and fundamental rights are protected.

She argued that AI and algorithms already influence recruitment, hiring, performance evaluation, promotion, contract changes, dismissals and pension-related decisions. According to Díaz, stronger oversight is needed to ensure transparency and accountability where algorithmic management affects workers.

Spain’s Rider Law was presented as an early example of algorithmic transparency in labour relations, requiring digital labour platforms to disclose information about algorithms that affect working conditions and access to work.

Díaz also criticised proposals to deregulate AI, arguing that technological development should serve the public good rather than concentrate power among a small number of technology companies.

Her intervention comes as the EU rules for high-risk AI systems in areas including employment are set to apply later than initially expected. The European Commission says these rules will apply from 2 December 2027 under the new AI Omnibus enforcement timeline.

Díaz said governments should actively shape how AI is used in the workplace through regulation and public policy, rather than leaving the future of work to market forces alone.

Why does it matter?

AI is increasingly used to manage recruitment, performance assessment, scheduling, promotion and dismissal decisions. Spain’s position places algorithmic transparency and worker rights at the centre of the European AI debate, especially as the EU’s employment-related high-risk AI obligations are delayed. The intervention also shows how member states may move ahead with stricter national rules when they believe EU-level protections are too slow or insufficient.

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Türkiye steps into quantum race with strategic roadmap

Türkiye has published an updated quantum technology roadmap, setting out 85 priority technology topics across quantum computing, quantum sensing and quantum communication.

The roadmap was developed through the Quantum Focus Technology Network (OTAĞ), coordinated by the Presidency of the Republic of Türkiye, Secretariat of Defence Industries. The process involved 305 experts from 123 institutions and organisations, including civilian and military stakeholders.

The roadmap classifies the 85 proposed technology topics into 34 near-term and 51 long-term priorities. Technologies were assessed using an analytical prioritisation method that considered Türkiye’s needs, existing capabilities, infrastructure, and end user requirements.

The strategy focuses on building domestic capability in quantum computing, sensing and communication by strengthening research infrastructure, developing skilled human capital and expanding cooperation between universities, industry, research centres and public institutions.

Priority steps include postgraduate programmes in quantum engineering and hardware technologies, researcher exchange and internship schemes, international research partnerships and critical infrastructure such as nanofabrication, cryogenic testing, precision measurement laboratories and sensor packaging.

The roadmap forms part of Türkiye’s wider effort to build a coordinated quantum ecosystem and improve its international competitiveness in a field with implications for cybersecurity, secure communications, advanced sensing and future computing.

Why does it matter?

Quantum technologies could reshape encryption, secure communications, sensing, navigation and high-performance computing. Türkiye’s roadmap is important because it turns quantum capability-building into a structured national programme with defence and strategic-technology relevance. By aligning universities, public institutions, industry and research centres around shared priorities, Türkiye is trying to reduce dependence on foreign technologies and position itself earlier in a field where global leadership is still being contested.

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Moldova tightens rules on AI in university theses

Moldova has approved a national framework regulation on academic integrity in higher education, introducing common rules on plagiarism, unauthorised use of AI and other forms of academic fraud.

The regulation, approved by the government and developed by the Ministry of Education and Research, sets a single framework that all higher education institutions in Moldova will be required to implement.

Under the new rules, students will have to declare whether they used AI in their academic work and explain how they used it. The ministry said the framework is intended to increase transparency and strengthen responsibility in the use of digital tools.

Acceptable AI use may include support functions such as proofreading, formatting or organising material, while core academic work, including analysis, interpretation and conclusions, must remain the student’s own intellectual contribution.

The regulation also classifies academic integrity violations by severity, with sanctions ranging from rewriting assignments to suspension or expulsion. Academic staff and supervisors may also face disciplinary measures if they fail to enforce integrity rules.

The framework forms part of Moldova’s wider effort to strengthen trust in higher education, including the planned use of a national anti-plagiarism system for bachelor’s and master’s theses.

Why does it matter?

Moldova’s rules show how universities are moving from informal guidance on generative AI towards enforceable academic integrity frameworks. Requiring students to disclose AI use can help distinguish between acceptable assistance and improper authorship, while preserving the value of independent analysis and critical thinking. The approach also reflects a wider education-policy challenge: institutions need to adapt assessment and integrity systems without banning useful digital tools entirely.

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Google proposes a balanced approach to AI governance in the US

Google has published a policy paper proposing a two-track approach to AI governance in the United States, separating oversight of frontier AI models from rules for widely deployed AI applications.

The paper argues that AI policy should avoid what Google describes as a false choice between over-regulation and no regulation. Instead, the company calls for a pragmatic, evidence-based framework that treats the most advanced AI systems differently from everyday AI tools such as chatbots.

For frontier AI, Google proposes the creation of a Frontier AI Regulatory Organisation, or FARO. The industry-funded body would operate under federal oversight and develop standards for safety, security, incident reporting and transparency.

Google says FARO could set scientific benchmarks for frontier capabilities, particularly in areas such as cybersecurity and chemical, biological, radiological and nuclear risks. It could also oversee independent audits and require frontier AI companies to publish and follow safety frameworks before releasing highly capable models.

For widely deployed AI applications, Google argues that the federal government should rely mainly on existing legal frameworks, with targeted updates where needed. The paper says policy should focus on real-world harms and outputs rather than micromanaging AI development.

The company identifies several priority areas, including workforce preparedness, child safety, information integrity, copyright, privacy and energy infrastructure for data centres.

Google supports measures such as AI interaction guidelines for children, disclosures that chatbots are not sentient, rules for self-harm-related queries, watermarking and provenance standards for generative AI, privacy-enhancing technologies and workforce reskilling.

The paper presents the model as a way to address national security and consumer protection risks while preserving US leadership in AI development.

Why does it matter?

Google’s paper is a significant industry intervention in the US AI policy debate. Its two-track model reflects a broader governance trend: frontier AI is increasingly being treated as a national security and safety issue, while everyday AI applications are being handled through consumer protection, child safety, privacy, copyright and labour policy. The proposal could influence federal discussions, but it also reflects Google’s own regulatory preferences, including industry-funded oversight, confidential audit reports and reliance on existing law for many AI applications.

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EU signs Pax Silica Declaration on AI supply chains

The European Commission has signed the Pax Silica Declaration on behalf of the EU, joining an international initiative focused on AI security and resilient silicon supply chains.

Pax Silica is a US-led initiative that aims to strengthen cooperation among allies and trusted partners across the AI supply chain, from critical minerals and energy inputs to semiconductor manufacturing, AI infrastructure and logistics.

The Commission said secure access to silicon and related technologies is becoming increasingly important as AI reshapes economies, security and industrial competitiveness.

The declaration commits signatories to closer cooperation on trusted technology ecosystems and more resilient supply chains. It also aims to reduce strategic dependencies and improve coordination on the materials, infrastructure and manufacturing capacity needed for AI development.

The EU’s signature follows the adoption of the European Technological Sovereignty Package, which includes Chips Act 2.0 and measures to strengthen Europe’s capacity in semiconductors, AI, cloud and open-source technologies.

The Commission said participation in Pax Silica could support European businesses, strengthen international partnerships and contribute to Europe’s broader technological sovereignty objectives.

Why does it matter?

AI development depends on far more than models and software. Advanced chips, critical minerals, energy, manufacturing capacity, cloud infrastructure and logistics are becoming strategic layers of the AI economy. By joining Pax Silica, the EU is linking AI competitiveness and security to semiconductor supply-chain resilience and cooperation with trusted partners. The move also shows how digital sovereignty is increasingly pursued through both domestic capacity-building and selective international alignment.

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New MIT development reduces energy use in AI systems

Researchers from MIT and Microsoft have developed a system called Murakkab to improve the speed and energy efficiency of agentic AI workflows.

Agentic workflows combine multiple AI models and external tools to complete complex, multi-step tasks, such as analysing video or generating code. MIT said these systems are becoming more important for cloud providers, but their fragmented design can waste computation, energy and money.

Murakkab allows developers to describe an AI application in high-level terms rather than manually specifying every model, tool, hardware choice and execution step. The system then identifies suitable models and tools, decides which components should run sequentially or in parallel, and selects hardware resources for cloud deployment.

The system can adjust configurations during execution based on user priorities such as accuracy, speed, latency and cost. It also gives cloud providers more visibility into workflows, allowing them to allocate computing resources more efficiently across multiple tasks.

In tests of video-question-answering and code-generation workflows, Murakkab met user requirements while using about 35% of the computational resources required by other methods. It also consumed about 27% as much energy and cost less than 25% as much as the comparison approaches.

In one case, the system reduced energy consumption by more than an order of magnitude with only about a 2% drop in accuracy. The researchers plan to expand Murakkab to more complex workflows and larger computing clusters.

Why does it matter?

Agentic AI systems are becoming more complex and resource-intensive, especially as cloud providers deploy workflows that combine many models, tools and hardware configurations. Murakkab points to a shift from optimising individual models to optimising the whole AI workflow and its cloud deployment. That matters because energy use, compute costs, and data centre capacity are becoming central constraints on AI growth.

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TEQSA backs GenAI learning reform in Australia

Australia’s Tertiary Education Quality and Standards Agency has published a paper on how higher education institutions can assure quality learning in a future shaped by generative AI.

The paper, ‘Assuring quality learning in a GenAI-integrated future: The role of adaptive capabilities’, argues that universities need to rethink how they define, assess and evidence student learning as generative AI becomes embedded in education.

The authors say generative AI and automated decision-making systems challenge traditional approaches to academic integrity and assessment. Rather than focusing only on securing final submissions, institutions should clarify what students need to learn in AI-integrated environments and how that learning can be demonstrated.

The paper identifies adaptive capabilities as central to graduate learning. These include digital literacy, distributed cognition, hybrid metacognition and life-long learning, grounded in disciplinary knowledge and supported by student agency and regulation.

The authors warn that narrow AI literacy may not be enough, as operational skills linked to current tools can quickly become outdated. Adaptive capabilities can help students evaluate new technologies, use AI ethically and continue learning as systems evolve.

The paper also highlights risks linked to generative AI, including overreliance on AI-generated explanations, reduced effortful learning and excessive cognitive offloading. It says higher education should preserve practices that support deeper learning, such as retrieval practice, spaced revision and generating answers before receiving explanations.

Assessment reform is a major theme. The paper calls for greater attention to evidence of learning processes rather than only to final products. Possible approaches include portfolios, learning journey documentation, reflective tasks, trace data and structured self-assessments.

TEQSA says the paper is not prescriptive and does not form part of its formal guidance notes. Instead, it is intended to support institutional thinking about how quality assurance may need to change as generative AI becomes a normal part of higher education.

Why does it matter?

Generative AI is weakening the reliability of product-based assessment, especially when final essays, reports, or problem solutions are produced or heavily shaped by AI tools. TEQSA’s focus on adaptive capabilities points towards a different quality assurance model: one that values student judgement, process evidence, ethical AI use and deep disciplinary understanding. That matters for universities because they will increasingly need to prove not only that students produced work, but that they learned, reasoned and exercised agency while using AI.

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China pledges continued role in global AI governance

Chinese Premier Li Qiang has said China will continue to participate in global governance on AI responsibly and constructively.

Li made the remarks during the opening plenary of the 17th Annual Meeting of the New Champions, also known as Summer Davos, in Dalian.

According to the Chinese government’s account of the speech, Li said China would work with other parties to strengthen institutional frameworks and rules, improve regulatory effectiveness and address potential AI risks.

He said AI has significantly improved innovation efficiency, but warned that risks linked to technological loss of control and ethical failures are becoming more pronounced.

Li said governance needs to keep pace with AI development, warning that the consequences could be severe if regulatory systems fail to keep to with the pace of technological change.

The remarks underline China’s continued effort to position itself as a participant in international AI governance debates, while also linking AI regulation to broader questions of innovation, economic development and global cooperation.

Why does it matter?

Li’s remarks show that AI governance remains part of China’s wider diplomatic and economic positioning. As frontier AI advances, governments are treating safety, ethics and regulatory coordination as strategic issues alongside competition over models, compute and industrial capacity. The speech does not introduce a new Chinese AI policy, but it reinforces Beijing’s message that global AI governance should involve international coordination rather than being shaped only by a few countries or companies.

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EU drops browser-based cookie consent proposal from Digital Omnibus

The European Commission had proposed replacing cookie banners with an automated browser-based privacy signal as part of its ‘Digital Omnibus’ package, a move that would have allowed devices to communicate users’ tracking preferences directly to websites. The plan, outlined in Article 88b of the GDPR, was intended to cut red tape and reduce the burden on consumers navigating consent requests across the web.

According to digital rights organisation noyb, cookie banners were not created by data protection law but emerged as a mechanism for the online advertising industry to obtain users’ consent for data sharing with third parties. Studies suggest only 3 to 10 per cent of users actually wish to be tracked, yet so-called dark patterns, such as hidden ‘no’ buttons and pre-ticked boxes, allow the industry to achieve consent rates of up to 90 per cent. Across more than 450 million EU citizens, this results in billions of unnecessary clicks each year.

According to noyb, a lobbying document submitted by Google argued that removing cookie banners would effectively halt all online advertising, citing figures that the European Commission has since described as highly exaggerated. The Commission had made clear that consent would still be possible on a per-website and per-purpose basis, meaning users could grant access to specific outlets while withholding it from others. Google’s paper also claimed that media outlets would be harmed, despite the fact that they are explicitly exempt from the proposed provision.

According to noyb, the lobbying campaign appears to have influenced the legislative process. In the Council’s position paper of 18 June 2026, Article 88b was removed entirely from the Digital Omnibus. Noyb added that Germany, France, and Poland were among the member states supporting the article’s removal following lobbying by the online advertising industry.

The outcome is particularly striking given that many of the same member states have long called on the EU to simplify regulation and cut red tape. noyb, the European digital rights organisation, has described the result as a victory for lobbying over public interest, noting that the majority of EU citizens have consistently expressed frustration with cookie banners.

The European Parliament has not yet taken a position on Article 88b, and negotiations between the Parliament and the Council are ongoing. Noyb has urged the European Parliament to support reinstating Article 88b during the next stage of negotiations.

Why does it matter?

The debate highlights the growing tension between digital simplification efforts, privacy protection and the economic interests of the online advertising ecosystem. Browser-based privacy signals have long been discussed as a way to reduce repetitive consent requests while preserving users’ ability to decide when and how their personal data may be used.

The proposal’s removal also illustrates the influence that industry stakeholders can have during the EU legislative process. Whether Article 88b is reinstated during negotiations with the European Parliament could shape the future of online consent management in Europe, affecting digital advertising, user experience and the practical implementation of data protection rules.

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