Future of work Archives | Digital Watch Observatory

EU lawmakers move forward on AI Act changes

Members of the European Parliament have reached a preliminary political agreement on amendments to the EU Artificial Intelligence Act. The compromise will be reviewed by parliamentary committees before a scheduled vote in Brussels.

Lawmakers in the EU agreed to extend compliance deadlines for some high risk AI systems. The changes aim to give companies and regulators more time to prepare technical standards and enforcement frameworks.

The proposed amendments also include a ban on AI systems that create non consensual explicit deepfakes. Officials in the EU say the measure aims to strengthen consumer protection and improve online safety for children.

Industry groups in the EU have raised concerns about compliance burdens linked to the revised rules. Policymakers in the EU continue negotiations as the legislation moves toward committee approval.

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Civil society urges stronger EU digital fairness rules

More than 200 civil society organisations have urged the European Commission to deliver strong consumer protections through the upcoming Digital Fairness Act. Advocacy groups in the EU say the proposal must address risks created by modern online platforms.

Campaigners argue that many existing EU consumer laws were designed decades ago and no longer reflect the realities of the digital market. The coalition warned policymakers in the EU not to treat regulatory simplification as a path toward deregulation.

Advocates are pushing for binding rules targeting deceptive design practices and addictive digital features. Survey responses across the EU show broad public support for stronger protections against dark patterns and unfair personalisation.

The European Commission is expected to present the Digital Fairness Act later this year. Officials in the EU are also considering expanding enforcement powers to strengthen consumer safeguards online.

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EU charts roadmap for tokenised financial markets

The European Central Bank (ECB) has unveiled Appia, a strategic roadmap for developing Europe’s tokenised financial ecosystem anchored in central bank money. The initiative aims to guide the shift from traditional finance to tokenised markets while ensuring stability and interoperability.

A key component of Appia is Pontes, the Eurosystem’s distributed ledger technology (DLT) settlement solution. Pontes, set for Q3 2026 pilots, will enable central bank money transactions and connect DLT infrastructures with the Eurosystem’s TARGET2, T2S, and TIPS services.

The ECB has opened a public consultation inviting feedback and proposals from both public and private sector stakeholders. Respondents’ input will help refine the roadmap and shape the long-term blueprint for Europe’s tokenised financial system.

Appia also complements ongoing efforts on the digital €, with payment service provider selection planned for 2026 and a 12-month pilot trial in the second half of 2027.

The initiative highlights the ECB’s commitment to integrating emerging technologies while preserving financial stability.

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AI-powered Copilot Health platform introduced by Microsoft

Microsoft has introduced Copilot Health, a new feature that uses AI to help users interpret personal health data and prepare for medical consultations.

The tool will operate as a separate and secure environment within Microsoft’s Copilot ecosystem, allowing users to combine health records, wearable data, and medical history into a single profile. The system then uses AI to analyse patterns and generate personalised insights intended to support conversations with healthcare professionals.

Microsoft said the feature aims to help people better understand existing medical information rather than replace clinical care. Users can review trends such as sleep patterns, activity levels, and vital signs gathered from wearable devices, alongside test results and visit summaries from healthcare providers.

Copilot Health can integrate data from more than 50 wearable devices, including systems connected through platforms such as Apple Health, Fitbit, and Oura. The platform can also access health records from over 50,000 US hospitals and provider organisations through HealthEx, as well as laboratory test results from Function.

According to Microsoft, the system builds on ongoing research into medical AI systems, including work on the Microsoft AI Diagnostic Orchestrator (MAI-DxO). The company said future publications will explore how such systems could assist in analysing complex medical cases.

Privacy and security are central elements of the design. Microsoft stated that Copilot Health data and conversations are stored separately from standard Copilot interactions and protected through encryption and access controls. The company also noted that health information used in the service will not be used to train AI models.

Development of the system involves Microsoft’s internal clinical team and an external advisory group of more than 230 physicians from 24 countries. The company said Copilot Health has also achieved ISO/IEC 42001 certification, a standard focused on the governance of AI management systems.

The feature is being introduced through a phased rollout, beginning with a waitlist for early users who will help shape the service as it develops.

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Generative AI in precision oncology faces a trust and safety challenge

A narrative review published in the Journal of Hematology & Oncology examined how generative AI tools could support oncologists in precision cancer care.

In this increasingly data-intensive field, clinicians must cross-reference genomic sequencing results, patient records, imaging findings, and a rapidly expanding body of biomedical literature to inform their decisions.

Researchers found promising results for AI-assisted clinical trial matching and diagnostic report drafting, but also highlighted significant risks that make unsupervised deployment dangerous.

On the positive side, the AI tool TrialGPT demonstrated 87.3% agreement with expert assessments when matching patients to clinical trials, while reducing processing time by an average of 42.6%.

Meanwhile, the vision-language model Flamingo-CXR matched or exceeded the performance of board-certified radiologists in 94% of chest X-ray cases with no clinically relevant findings.

Researchers cautioned, however, that clinically significant errors appeared in 24.8% of evaluated imaging reports, whether AI- or human-generated, underscoring the need for combined oversight.

The review’s authors advocate for ‘Human-in-the-Loop’ workflows, in which human experts review all AI outputs before clinical implementation, and for Retrieval-Augmented Generation techniques that force AI systems to draw on current medical guidelines rather than relying solely on their base training data.

The key conclusion is that AI should function as an assistant to oncologists, not as an autonomous decision maker.

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EU platform law expands data access rights

European regulators are examining how the Digital Markets Act interacts with the General Data Protection Regulation across major digital platforms. The EU rules apply to designated gatekeepers that operate core platform services used by millions of users.

Policy specialists in the EU say the Digital Markets Act complements GDPR protections by strengthening user control over personal data. The framework also supports rights related to data access, portability and transparency for both consumers and business users.

The regulatory overlap affects areas including consent requirements, third-party software installation and interoperability between services. Authorities are also coordinating enforcement between competition and data protection regulators.

Analysts say the combined application of both laws could reshape the responsibilities of major technology platforms. Policymakers aim to increase user choice while reinforcing safeguards for the integrity and confidentiality of personal data in the GDPR.

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AI agents face growing prompt injection risks

AI developers are working on new defences against prompt-injection attacks that aim to manipulate AI agents. Security specialists warn that attackers are increasingly using social engineering techniques to influence AI systems that interact with online content.

Researchers say AI agents that browse the web or handle user tasks face growing risks from hidden instructions embedded in emails or websites. Experts in the US note that attackers often attempt to trick AI into revealing sensitive information.

Engineers are responding by designing systems that limit the impact of manipulation attempts. Developers in the US say AI tools must include safeguards preventing sensitive data from being transmitted without user approval.

Security teams are also introducing technologies that detect risky actions and prompt users for confirmation. Specialists argue that strong system design and user oversight will remain essential as AI agents gain more autonomy.

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MIT researchers outline future of AI and physical sciences

AI and the mathematical and physical sciences are entering a new phase of collaboration that could accelerate technological progress and scientific discovery. Researchers increasingly see the relationship as a two-way exchange rather than a one-sided use of AI tools.

A 2025 MIT workshop brought together experts from astronomy, chemistry, materials science, mathematics and physics to examine the future of this collaboration.

Discussions resulted in a white paper published in Machine Learning: Science and Technology, outlining strategies for research institutions and funding bodies.

Participants agreed that stronger computing infrastructure, shared data resources and cross-disciplinary research methods are essential for progress. Scientists also improve AI by analysing neural networks, identifying principles and developing new algorithms.

Researchers highlighted the growing importance of so-called ‘centaur scientists’- specialists trained in both AI and traditional scientific disciplines. Universities, including MIT, are expanding interdisciplinary programmes and research initiatives to train experts who can work across AI and scientific fields.

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Leading tech companies deepen AI competition with new capabilities

AI competition among leading AI developers intensified in early 2026 as major companies expanded their models, platforms, and partnerships. Companies including Google, OpenAI, Anthropic, and xAI are introducing new capabilities and integrating AI systems into broader ecosystems.

Google has continued to expand its Gemini model family with updates to Gemini 3.1 Pro and 3.1 Flash, designed to support complex tasks across applications. The company is also integrating Gemini into services such as Docs, Sheets, Slides, and Drive, allowing users to generate documents and analyse data across multiple Google services.

Gemini has also been embedded into the Chrome browser and integrated with Samsung’s Galaxy devices, expanding its distribution across consumer platforms as AI competition among major developers accelerates.

Anthropic has focused on advancing the Claude model family while positioning the system for enterprise and professional use. Recent updates include Claude Sonnet 4.6, which introduces improvements in reasoning and coding capabilities alongside an expanded context window currently in beta. The company has also launched a limited preview of the Claude Marketplace, allowing organisations to use third-party tools built on Claude through partnerships with several software companies.

OpenAI has continued to update ChatGPT with the release of the GPT-5 series, including GPT-5.2 and GPT-5.4. The newer models combine reasoning, coding, and agent-based workflows, while also introducing computer-use capabilities that allow the system to interact with applications directly.

OpenAI has also introduced additional services, including ChatGPT Health and integrations designed to assist with spreadsheet modelling and data analysis, further intensifying AI competition across enterprise and consumer tools.

Meanwhile, xAI has expanded development of its Grok models while increasing computing infrastructure. The company has reported growth in Grok usage through integration with the X platform and other applications. Recent announcements include upgrades to Grok’s voice and multimodal capabilities, as well as continued training of future models.

Across the industry, developers are increasingly positioning their systems not only as conversational assistants but also as tools integrated into enterprise workflows, creative production, and software development. New releases in 2026 reflect a broader shift toward multimodal systems, agent-based capabilities, and deeper integration with existing digital platforms, highlighting how AI competition is shaping the next phase of AI development.

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ChatGPT dynamic visual explanations introduce interactive learning tools

OpenAI has introduced a new ChatGPT feature called dynamic visual explanations, allowing users to interact with mathematical and scientific concepts through real-time visuals.

Instead of relying solely on text explanations or static diagrams, the feature enables users to manipulate formulas and variables and immediately see how those changes affect results. For example, when exploring the Pythagorean theorem, users can adjust the triangle’s sides and see the hypotenuse update instantly.

To use the tool, users can ask ChatGPT questions such as ‘What is a lens equation?’ or ‘How can I find the area of a circle?’ The chatbot responds with both a written explanation and an interactive visual module that users can manipulate directly.

The feature currently supports more than 70 topics in mathematics and science. The topics include binomial squares, Charles’ law, compound interest, Coulomb’s law, exponential decay, Hooke’s law, kinetic energy, linear equations, and Ohm’s law.

OpenAI says it plans to expand the range of topics over time. The feature is already available to all logged-in ChatGPT users. The launch marks a shift in how ChatGPT supports learning. Instead of simply providing answers, the tool now encourages users to explore underlying concepts by experimenting with interactive models.

AI tools have become increasingly common in education, although their role remains widely debated. Some educators worry that students may become overly dependent on AI tools, while others see them as valuable learning aids.

According to OpenAI, more than 140 million people use ChatGPT every week to help with subjects such as mathematics and science, which many learners find challenging. Other technology companies are also experimenting with similar tools. Google’s Gemini introduced interactive diagrams and visual explanations last year.

The new feature joins several other ChatGPT learning tools, including study mode, which guides users through problems step by step, and QuizGPT, which allows users to create flashcards and test themselves before exams.

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