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IAPP Global Summit session examines AI, privacy, and the courts with US federal judges

US District Court for the District of Columbia Chief Judge James Boasberg and US District Court for the District of Massachusetts Judge Allison Burroughs discussed AI, privacy, and the courts during the IAPP Global Summit 2026 in Washington, D.C.

The IAPP report said Burroughs pointed to the gap between older legal protections and newer technologies, including debates over how surveillance rules apply to cell-tower data. Burroughs said existing laws and constitutional protections are ‘not keeping up, never have kept up and never will keep up’ with the speed of innovation.

Burroughs commented: ‘The gap is getting bigger for two reasons. One is that there’s so much more data stored electronically that if you even search for someone’s laptop, you’re going to get more data now than you used to get, and the other one is that there is so much more technology, there are just so many ways of gaining access to data.’

Another part of the IAPP report stated that Boasberg referred to a case in which lawyers submitted filings containing hallucinatory information generated through AI use. According to the report, he required that side to pay attorney’s fees to the other side as a sanction after discovering that AI had been used in the briefs.

Boasberg noted at the IAPP session: ‘I’m sure lawyers using AI is happening a lot more on the state level, and some judges are referring lawyers to state bars (for possible discipline), but there have been federal judges whose opinions included hallucinatory (citations) and that was obviously embarrassing for them.’ He added: ‘The question is how can it help without compromising privacy issues, sealed cases; there’s just a whole lot that we have to figure out, but I think judges are trying to learn how we can use this constructively.’

Burroughs also remarked at the IAPP event that judges want disclosure when lawyers use AI in filings. She said: ‘We want lawyers to tell us when they’ve used AI. They can use it, but they have to disclose it.’ She added: ‘They can use AI, they can’t use AI, they must disclose when they’re using it, they have to certify that they do citation checks to make sure they don’t have hallucinatory citations — it’s hard to think of what these rules would be going forward today.’

IAPP reported the remarks from the summit discussion. At the IAPP Global Summit, the discussion focused on how AI is affecting legal filings, surveillance questions, and court practice.

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Student AI rights framework unveiled

A newly released ‘Student AI Bill of Rights’ in the US outlines a proposed framework to protect learners as AI tools become increasingly widespread in education. The initiative aims to establish clear standards for fairness, transparency and accountability.

The document highlights the need for students to be informed when AI systems are used in teaching, assessment or administration. It also stresses that students should retain control over their personal data and academic work.

Another central principle is accountability, with students given the right to question and appeal decisions made or influenced by AI systems. The framework also calls for safeguards to prevent bias and ensure equal access to educational opportunities.

While not legally binding, the proposal is designed to guide higher education institutions in developing responsible AI policies. It reflects growing efforts to define ethical standards for AI use in education in the US.

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UK Research and Innovation review calls for reform at The Alan Turing Institute

An independent review by UK Research and Innovation has assessed the performance of The Alan Turing Institute. The evaluation examined whether the institute meets expectations as a national centre for AI and data science.

Findings recognise scientific excellence, strong partnerships and valuable contributions within the UK research system. However, the review identifies the need for a clearer strategic purpose and stronger delivery.

The panel concludes that alignment with national priorities and value for money is not yet satisfactory. Recommendations include improved governance, clearer prioritisation and renewed external scientific scrutiny.

Additional proposals call for stronger stakeholder engagement and a defined mission focused on resilience, security and defence. A framework for value for money is also expected to be agreed with the Engineering and Physical Sciences Research Council.

UK Research and Innovation will work with the institute’s leadership and partners to implement the changes. A development plan is expected by September 2026, with further assessment to follow.

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CNN develops agent infrastructure for AI media trading

CNN is developing an internal agent infrastructure as part of a plan to begin AI-driven media trading by early 2027. The company aims to complete protocol scoping by the end of the second quarter before moving into testing phases later in the year.

Testing will focus on how properties are interpreted by large language models and how buyers allocate budgets to agent-based systems. Executives say the timeline may change as the technology and market conditions continue to evolve.

The initiative combines in-house development with external technology partners, while aligning with industry frameworks to ensure compatibility. CNN is also working with standards bodies to ensure agent communication produces accurate outcomes for buyers.

Agentic protocols enable systems to exchange information, negotiate pricing, and manage tasks autonomously between buyers and sellers. The company is prioritising consistent communication to support efficient and reliable transactions.

Early efforts are centred on learning and experimentation, even without immediate revenue generation. Initial use cases are expected to focus on performance-driven campaigns before expanding into broader advertising activities.

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GEANT Security Days 2026 to address AI, internet resilience, and cyber resilience

GEANT Security Days 2026 will take place in Utrecht, the Netherlands, bringing together security professionals, network experts, incident responders, and chief information security officers from the research and education community.

The opening plenary includes a keynote by Frank Rieger, Chief Technical Officer of a supplier of secure communication systems, on ‘The bumpy road ahead – IT security challenges of the next years.’ According to the programme, his talk will address agentic LLMs, attention economics, and how automation, control of networked systems, endpoints, and software are becoming increasingly important as change accelerates.

A second keynote in the opening plenary of GEANT Security Days is scheduled with Valerie Aurora of the Amsterdam Internet Resiliency Club. The programme says her session, ‘Start your own Internet Resiliency Club,’ will look at how communities can prepare for temporary loss of internet connectivity caused by accidents, natural disasters, or armed conflict, and how to build local internet resiliency clubs using LoRa radios, mesh networking, and community management.

Another keynote is listed from Nancy Beers of Sanne Cyber and Happy Game Changers. Her session, ‘Play More Today. Secure Tomorrow,’ is described as a discussion of play and playfulness as tools for learning, innovation, and security practice, drawing on interactive games and team-based approaches.

Topics listed in the GEANT Security Days programme include security operations centres, AI in incident response, AI more broadly, cloud security, community engagement, cyber resilience, the human factor, an unconference or storytelling session, squeezed budgets and stretched teams, and practical security.

The event page says these sessions will address issues such as anomaly detection and prediction, malicious uses of generative AI, trust in third-party services, compliance in multi-cloud and hybrid environments, continuity planning, phishing and credential reuse, and operational pressures on security teams.

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MIT study finds steady AI growth reshapes work

A new study from the Massachusetts Institute of Technology (MIT) Computer Science and Artificial Intelligence Laboratory finds that AI is reshaping work through steady, broad-based improvements rather than sudden technological jumps.

Researchers describe this pattern as a ‘rising tide,’ in which capability gains emerge across many tasks simultaneously.

The analysis draws on more than 17,000 worker evaluations covering over 3,000 text-based tasks from US labour classifications. Findings show limited evidence of abrupt ‘crashing wave’ breakthroughs in which AI suddenly masters specific job areas.

Instead, performance improves consistently across tasks of varying complexity and duration. Researchers report that current AI systems can already complete roughly half to three-quarters of text-related tasks at a minimally sufficient standard without human intervention.

Projections suggest that, if current trends continue, success rates could reach around 80 to 95 percent by 2029, although higher-quality performance may take longer to achieve.

Workplace change is unfolding gradually, with employees shifting towards oversight roles focused on directing, reviewing, and validating AI outputs.

Despite a slower structural transition than abrupt disruption scenarios, researchers warn that cumulative improvements could still drive significant labour market effects as adoption expands.

AI-driven change is likely to unfold across a wide range of tasks, allowing adaptation by workers and organisations while still signalling longer-term shifts in skills, workflows, and labour markets.

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AI improves structured and coherent legal systems for better regulation

A study from Sultan Qaboos University shows how AI can be used to map hidden structural relationships within legal systems, offering new ways to understand how laws interact and evolve.

Published in The Journal of Engineering Research, the research applies natural language processing and network analysis to Oman’s 2023 Labour Law.

The analysis reveals that legal provisions operate as an interconnected system rather than isolated rules. Certain articles emerge as highly influential ‘hubs’, with Article 147 identified as a central node whose modification could generate cascading effects across multiple parts of the legislation.

These interdependencies are visualised through network mapping techniques that highlight structural relationships not easily detected through traditional review.

To construct this model, researchers developed a four-stage methodology combining Arabic-language NLP tools with industrial engineering approaches. Legal texts were mapped using terminology and cross-referencing patterns, with outputs validated by Omani legislative experts to ensure accuracy and relevance.

The study highlights links between labour law and broader regulatory domains, including commercial regulation, social protection, occupational health, and immigration policy.

The findings underline AI’s potential in the regulatory sector to improve coherence, reveal interdependencies, and support scalable, more consistent legal frameworks across jurisdictions.

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OpenAI presents policy proposals addressing AI’s economic and labour impacts

Policy proposals advanced by OpenAI outline a vision of economic restructuring in response to the growing influence of AI.

Framed within an emerging ‘intelligence age‘, the approach reflects concerns that AI-driven productivity gains may concentrate wealth while undermining traditional labour-based economic models.

The proposals, therefore, attempt to reconcile market-led innovation with mechanisms aimed at broader distribution of economic benefits.

A central element involves shifting taxation away from labour towards capital, reflecting expectations that automation will reduce reliance on human work.

Instruments such as robot taxes and public wealth funds are presented as potential tools to redistribute gains generated by AI systems.

Such proposals by OpenAI indicate a policy direction where states may need to redefine fiscal structures to sustain social protection systems traditionally funded through employment-based taxation.

Labour market adaptation forms another key pillar, with suggestions including shorter working weeks, portable benefits, and increased corporate contributions to social welfare.

However, reliance on employer-linked mechanisms raises questions about coverage gaps, particularly for individuals displaced by automation. The proposals highlight ongoing tensions between corporate-led welfare models and the need for more comprehensive public safety nets.

Alongside economic measures, the framework addresses governance challenges linked to advanced AI systems, including systemic risks and misuse.

OpenAI’s proposals also recommend that oversight bodies, risk containment strategies, and infrastructure expansion reflect an effort to balance innovation with control.

Treating AI as a utility further signals a shift towards recognising digital infrastructure as a public good, though implementation will depend on political consensus and regulatory capacity.

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South Korea-France partnership reshapes AI and technology cooperation strategy

The recent state visit between South Korea and France signals a deepening of bilateral cooperation that extends beyond diplomacy into long-term technological and cultural alignment.

Agreements endorsed by President Lee Jae-myung and President Emmanuel Macron reflect a coordinated effort to strengthen shared capabilities in emerging sectors, while reinforcing institutional ties across research, education, and industry.

A central policy dimension lies in the expansion of cooperation in AI, semiconductors, and quantum technologies, areas increasingly tied to economic security and global competitiveness.

Partnerships between institutions such as KAIST and CNRS highlight a shift towards structured research integration, enabling joint innovation and knowledge transfer.

Such collaboration between South Korea and France is positioned not as an isolated scientific exchange, but as part of broader strategies to secure technological sovereignty and resilient supply chains.

Cultural and educational initiatives complement these ambitions by supporting long-term people-to-people engagement and workforce development. Expanded exchanges in creative industries and language education aim to cultivate talent pipelines that can operate across both economies.

Rather than symbolic diplomacy, these measures serve as enabling mechanisms for sustained cooperation in high-value sectors where human capital remains critical.

From a policy perspective, the agreements illustrate how economies are increasingly forming strategic partnerships to navigate global technological competition.

Instead of relying solely on domestic capacity, coordinated international frameworks are being used to manage innovation risks, diversify supply dependencies, and strengthen regulatory alignment.

The outcome will depend on implementation, yet the direction suggests a model of cooperation that blends economic, technological, and societal priorities.

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Anthropic scales AI compute to meet rising global demand

AI company Anthropic has announced a major expansion of its compute infrastructure through a new partnership with Google and Broadcom, securing multiple gigawatts of next-generation TPU capacity expected to come online from 2027.

The increased compute supply is intended to support its frontier Claude models and meet rapidly growing global demand.

The company said the expansion reflects a continued strategy of scaling infrastructure to match accelerating customer growth. Demand for Claude has increased sharply in 2026, with revenue run-rate surpassing $30 billion and the number of high-spending business customers doubling in a short period.

Most new computing capacity will be based in the United States, aligning with broader investment plans in domestic AI infrastructure. The partnership builds on collaborations with Google Cloud and Broadcom, alongside continued use of multiple hardware platforms to improve performance and resilience.

Anthropic stated that diversifying compute across different providers helps optimise workloads and maintain reliability for enterprise users. Claude remains available across major cloud platforms, supporting its position in a competitive and rapidly scaling AI market.

The expansion reflects how rapidly growing demand for advanced AI systems is driving large-scale investment in underlying compute infrastructure, with potential implications for capacity, reliability, and the global distribution of AI development resources over time.

It also suggests how access to computing resources is becoming a key factor shaping competitiveness and innovation across the AI ecosystem.

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