EU proposal sparks alarm over weakened privacy rules

The Digital Omnibus has been released by the European Commission, prompting strong criticism from privacy advocates. Campaigners argue the reforms would weaken long-standing data protection standards and introduce sweeping changes without proper consultation.

Noyb founder Max Schrems claims the plan favours large technology firms by creating loopholes around personal data and lowering user safeguards. Critics say the proposals emerge despite limited political support from EU governments, civil society groups and several parliamentary factions.

The Omnibus is welcomed by industry which have called for simplification and changes to be made for quite a number of years. These changes should make carrying out business activities simpler for entities which do process vast amounts of data.

The Commission is also accused of rushing (errors can be found in the draft, including references to the GDPR) the process under political pressure, abandoning impact assessments and shifting priorities away from widely supported protections. View our analysis on the matter for a deep dive on the matter.

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Health sector AI growth in Europe raises safety concerns

Concerns are growing as European countries expand the use of AI in healthcare without establishing sufficient protections for patients or healthcare workers.

A new World Health Organisation report found significant disparities in how nations develop, regulate and fund AI tools.

Some countries are rapidly deploying chatbots, imaging systems and data-analysis tools, while others have barely started integrating AI into their health services. Only four nations across Europe and Central Asia currently have a national strategy dedicated to AI in health care.

WHO officials warn that weak safeguards could lead to biassed algorithms, medical errors and increased inequality in access to care.

The report urges governments to strengthen legal frameworks, train health workers in AI literacy and ensure these technologies are rigorously tested before reaching patients.

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Sundar Pichai warns users not to trust AI tools easily

Google CEO Sundar Pichai advises people not to unquestioningly trust AI tools, warning that current models remain prone to errors. He told the BBC that users should rely on a broader information ecosystem rather than treat AI as a single source of truth.

Pichai said generative systems can produce inaccuracies and stressed that people must learn what the tools are good at. The remarks follow criticism of Google’s own AI Overviews feature, which attracted attention for erratic and misleading responses during its rollout.

Experts say the risk grows when users depend on chatbots for health, science, or news. BBC research found major AI assistants misrepresented news stories in nearly half of the tests this year, underscoring concerns about factual reliability and the limits of current models.

Google is launching Gemini 3.0, which it claims offers stronger multimodal understanding and reasoning. The company says its new AI Mode in search marks a shift in how users interact with online information, as it seeks to defend market share against ChatGPT and other rivals.

Pichai says Google is increasing its investment in AI security and releasing tools to detect AI-generated images. He maintains that no single company should control such powerful technology and argues that the industry remains far from a scenario in which one firm dominates AI development.

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NVIDIA pushes forward with AI-ready data

Enterprises are facing growing pressure to prepare unstructured data for use in modern AI systems as organisations struggle to turn prototypes into production tools.

Around forty percent of AI projects advance beyond the pilot phase, largely due to limits in data quality and availability. Most organisational information now comes in unstructured form, ranging from emails to video files, which offers little coherence and places a heavy load on governance systems.

AI agents need secure, recent and reliable data instead of fragmented information scattered across multiple storage silos. Preparing such data demands extensive curation, metadata work, semantic chunking and the creation of vector embeddings.

Enterprises also struggle with the rising speed of data creation and the spread of duplicate copies, which increases both operational cost and security concerns.

An emerging approach by NVIDIA, known as the AI data platform, aims to address these challenges by embedding GPU acceleration directly into the data path. The platform prepares and indexes information in place, allowing enterprises to reduce data drift, strengthen governance and avoid unnecessary replication.

Any change to a source document is immediately reflected in the associated AI representations, improving accuracy and consistency for business applications.

NVIDIA is positioning its own AI Data Platform reference design as a next step for enterprise storage. The design combines RTX PRO 6000 Blackwell Server Edition GPUs, BlueField three DPUs and integrated AI processing pipelines.

Leading technology providers including Cisco, Dell Technologies, IBM, HPE, NetApp, Pure Storage and others have adopted the model as they prepare storage systems for broader use of generative AI in the enterprise sector.

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OpenAI and Intuit expand financial AI collaboration

Yesterday, OpenAI and Intuit announced a major strategic partnership aimed at reshaping how people manage their personal and business finances. The arrangement will allow Intuit apps to appear directly inside ChatGPT, enabling secure and personalised financial actions within a single environment.

An agreement that is worth more than one hundred million dollars and reinforces Intuit’s long-term push to strengthen its AI-driven expert platform.

Intuit will broaden its use of OpenAI’s most advanced models to support financial tasks across its products. Frontier models will help power AI agents that assist with tax preparation, cash flow forecasting, payroll management and wider financial planning.

Intuit will also continue using ChatGPT Enterprise internally so employees can work with greater speed and accuracy.

The partnership is expected to help consumers make more informed financial choices instead of relying on fragmented tools. Users will be able to explore suitable credit offers, receive clearer tax answers, estimate refunds and connect with tax specialists.

Businesses will gain tailored insights based on real time data that can improve cash flow, automate customer follow ups and support more effective outreach through email marketing.

Leaders from both companies argue that the collaboration will give people and firms a meaningful financial advantage. They say greater personalisation, deeper data analysis and more effortless decision making will support stronger household finances and more resilient small enterprises.

The deal expands the growing community of OpenAI enterprise customers and strengthens Intuit’s position in global financial technology.

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Google enters a new frontier with Gemini 3

A new phase of its AI strategy has begun for Google with the release of Gemini 3, which arrives as the company’s most advanced model to date.

The new system prioritises deeper reasoning and more subtle multimodal understanding, enabling users to approach difficult ideas with greater clarity instead of relying on repetitive prompting. It marks a major step for Google’s long-term project to integrate stronger intelligence into products used by billions.

Gemini 3 Pro is already available in preview across the Gemini app, AI Mode in Search, AI Studio, Vertex AI and Google’s new development platform known as Antigravity.

A model that performs at the top of major benchmarks in reasoning, mathematics, tool use and multimodal comprehension, offering substantial improvements compared with Gemini 2.5 Pro.

Deep Think mode extends the model’s capabilities even further, reaching new records on demanding academic and AGI-oriented tests, although Google is delaying wider release until additional safety checks conclude.

Users can rely on Gemini 3 to learn complex topics, analyse handwritten material, decode long academic texts or translate lengthy videos into interactive guides instead of navigating separate tools.

Developers benefit from richer interactive interfaces, more autonomous coding agents and the ability to plan tasks over longer horizons.

Google Antigravity enhances this shift by giving agents direct control of the development environment, allowing them to plan, write and validate code independently while remaining under human supervision.

Google emphasises that Gemini 3 is its most extensively evaluated model, supported by independent audits and strengthened protections against manipulation. The system forms the foundation for Google’s next era of agentic, personalised AI and will soon expand with additional models in the Gemini 3 series.

The company expects the new generation to reshape how people learn, build and organise daily tasks instead of depending on fragmented digital services.

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TikTok launches new tools to manage AI-generated content

TikTok has announced new tools to help users shape and understand AI-generated content (AIGC) in their feeds. A new ‘Manage Topics’ control will let users adjust how much AI content appears in their For You feeds alongside keyword filters and the ‘not interested’ option.

The aim is to personalise content rather than remove it entirely.

To strengthen transparency, TikTok is testing ‘invisible watermarking’ for AI-generated content created with TikTok tools or uploaded using C2PA Content Credentials. Combined with creator labels and AI detection, these watermarks help track and identify content even if edited or re-uploaded.

The platform has launched a $2 million AI literacy fund to support global experts in creating educational content on responsible AI. TikTok collaborates with industry partners and non-profits like Partnership on AI to promote transparency, research, and best practices.

Investments in AI extend beyond moderation and labeling. TikTok is developing innovative features such as Smart Split and AI Outline to enhance creativity and discovery, while using AI to protect user safety and improve the well-being of its trust and safety teams.

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Poll manipulation by AI threatens democratic accuracy, according to a new study

Public opinion surveys face a growing threat as AI becomes capable of producing highly convincing fake responses. New research from Dartmouth shows that AI-generated answers can pass every quality check, imitate real human behaviour and alter poll predictions without leaving evidence.

In several major polls conducted before the 2024 US election, inserting only a few dozen synthetic responses would have reversed expected outcomes.

The study reveals how easily malicious actors could influence democratic processes. AI models can operate in multiple languages yet deliver flawless English answers, allowing foreign groups to bypass detection.

An autonomous synthetic respondent that was created for the study passed nearly all attention tests, avoided errors in logic puzzles and adjusted its tone to match assigned demographic profiles instead of exposing its artificial nature.

The potential consequences extend far beyond electoral polling. Many scientific disciplines rely heavily on survey data to track public health risks, measure consumer behaviour or study mental wellbeing.

If AI-generated answers infiltrate such datasets, the reliability of thousands of studies could be compromised, weakening evidence used to shape policy and guide academic research.

Financial incentives further raise the risk. Human participants earn modest fees, while AI can produce survey responses at almost no cost. Existing detection methods failed to identify the synthetic respondent at any stage.

The researcher urges survey companies to adopt new verification systems that confirm the human identity of participants, arguing that stronger safeguards are essential to protect democratic accountability and the wider research ecosystem.

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The future of the EU data protection under the Omnibus Package

Introduction and background information

The Commission claims that the Omnibus Package aims to simplify certain European Union legislation to strengthen the Union’s long-term competitiveness. A total of six omnibus packages have been announced in total.

The latest (no. 4) targets small mid-caps and digitalisation. Package no. 4 covers data legislation, cookies and tracking technologies (i.e. the General Data Protection Regulation (GDPR) and ePrivacy Directive (ePD)), as well as cybersecurity incident reporting and adjustments to the Artificial Intelligence Act (AIA).

That ‘simplification’ is part of a broader agenda to appease business, industry and governments who argue that the EU has too much red tape. In her September 2025 speech to German economic and business associations, Ursula von der Leyen sided with industry and stated that simplification is ‘the only way to remain competitive’.

As for why these particular laws were selected, the rationale is unclear. One stated motivation for including the GDPR is its mention in Mario Draghi’s 2024 report on ‘The Future of European Competitiveness’.

Draghi, the former President of the European Central Bank, focused on innovation in advanced technologies, decarbonisation and competitiveness, as well as security. Yet, the report does not outline any concrete way in which the GDPR allegedly reduces competitiveness or requires revision.

The GDPR appears only twice in the report. First, as a brief reference to regulatory fragmentation affecting the reuse of sensitive health data across Member States (MS).

Second, in the concluding remarks, it is claimed that ‘the GDPR in particular has been implemented with a large degree of fragmentation which undermines the EU’s digital goals’. There is, however, no explanation of this ‘large fragmentation’, no supporting evidence, and no dedicated section on the GDPR as its first mention being buried in the R&I (research and innovation) context.

It is therefore unclear what legal or analytical basis the Commission relies on to justify including the GDPR in this simplification exercise.

The current debate

There are two main sides to this Omnibus, which are the privacy forward and the competitive/SME side. The two need not be mutually exclusive, but civil society warns that ‘simplification’ risks eroding privacy protection. Privacy advocates across civil society expressed strong concern and opposition to simplification in their responses to the European Commission’s recent call for evidence.

Industry positions vary in tone and ambition. For example, CrowdStrike calls for greater legal certainty under the Cybersecurity Act, such as making recital 55 binding rather than merely guiding and introducing a one-stop-shop mechanism for incident reporting.

Meta, by contrast, urges the Commission to go beyond ‘easing administrative burdens’, calling for a pause in AI Act enforcement and a sweeping reform of the EU data protection law. On the civil society side, Access Now argues that fundamental rights protections are at stake.

It warns that any reduction in consent prompts could allow tracking technologies to operate without users ever being given a real opportunity to refuse. A more balanced, yet cautious line can be found in the EDPB and EDPS joint opinion regarding easing records of processing activities for SMEs.

Similar to the industry, they support reducing administrative burdens, but with the caveat that amendments should not compromise the protection of fundamental rights, echoing key concerns of civil society.

Regarding Member State support, Estonia, France, Austria and Slovenia are firmly against any reopening of the GDPR. By contrast, the Czech Republic, Finland and Poland propose targeted amendments while Germany proposes a more systematic reopening of the GDPR.

Individual Members of the European Parliament have also come out in favour of reopening, notably Aura Salla, a Finnish centre-right MEP who previously headed Meta’s Brussels lobbying office.

Therefore, given the varied opinions, it cannot be said what the final version of the Omnibus would look like. Yet, a leaked draft document of the GDPR’s potential modifications suggests otherwise. Upon examination, it cannot be disputed that the views from less privacy-friendly entities have served as a strong guiding path.

Leaked draft document main changes

The leaked draft introduces several core changes.

Those changes include a new definition of personal and sensitive data, the use of legitimate interest (LI) for AI processing, an intertwining of the ePrivacy Directive (ePD) and GDPR, data breach reforms, a centralised data protection impact assessment (DPIA) whitelist/blacklist, and access rights being conditional on motive for use.

A new definition of personal data

The draft redefines personal data so that ‘information is not personal data for everyone merely because another entity can identify that natural person’. That directly contradicts established EU case law, which holds that if an entity can, with reasonable means, identify a natural person, then the information is personal data, regardless of who else can identify that person.

A new definition of sensitive data

Under current rules, inferred information can be sensitive personal data. If a political opinion is inferred from browsing history, that inference is protected.

The draft would narrow this by limiting sensitive data to information that ‘directly reveals’ special categories (political views, health, religion, sexual orientation, race/ethnicity, trade union membership). That would remove protection from data derived through profiling and inference.

Detected patterns, such as visits to a health clinic or political website, would no longer be treated as sensitive, and only explicit statements similar to ‘I support the EPP’ or ‘I am Muslim’ would remain covered.

Intertwining article 5(3) ePD and the GDPR

Article 5(3) ePD is effectively copied into the GDPR as a new Article 88a. Article 88a would allow the processing of personal data ‘on or from’ terminal equipment where necessary for transmission, service provision, creating aggregated information (e.g. statistics), or for security purposes, alongside the existing legal bases in Articles 6(1) and 9(2) of the GDPR.

That generates confusion about how these legal bases interact, especially when combined with AI processing under LI. Would this mean that personal data ‘on or from’ a terminal equipment may be allowed if it is done by AI?

The scope is widened. The original ePD covered ‘storing of information, or gaining access to information already stored, in the terminal equipment’. The draft instead regulates any processing of personal data ‘on or from’ terminal equipment. That significantly expands the ePD’s reach and would force controllers to reassess and potentially adapt a broad range of existing operations.

LI for AI personal data processing

A new Article 88c GDPR, ‘Processing in the context of the development and operation of AI’, would allow controllers to rely on LI to process personal data for AI processing. That move would largely sideline data subject control. Businesses could train AI systems on individuals’ images, voices or creations without obtaining consent.

A centralised data breach portal, deadline extension and change in threshold reporting

The draft introduces three main changes to data breach reporting.

  • Extending the notification deadline from 72 to 96 hours, giving privacy teams more time to investigate and report.
  • A single EU-level reporting portal, simplifying reporting for organisations active in multiple MS.
  • Raising the notification threshold when the rights and freedoms of data subjects are at ‘risk’ to ‘high risk’.

The first two changes are industry-friendly measures designed to streamline operations. The third is more contentious. While industry welcomes fewer reporting obligations, civil society warns that a ‘high-risk’ threshold could leave many incidents unreported. Taken together, these reforms simplify obligations, albeit at the potential cost of reducing transparency.

Centralised processing activity (PA) list requiring a DPIA

This is another welcome change as it would clarify which PAs would automatically require a DPIA and which would not. The list would be updated every 3 years.

What should be noted here is that some controllers may not see their PA on this list and assume or argue that a DPIA is not required. Therefore, the language on this should make it clear that it is not a closed list.

Access requests denials

Currently, a data subject may request a copy of their data regardless of the motive. Under the draft, if a data subject exploits the right of access by using that material against the controller, the controller may charge or refuse the request.

That is problematic for the protection of rights as it impacts informational self-determination and weakens an important enforcement tool for individuals.

For more information, an in depth analysis by noyb has been carried out which can be accessed here.

The Commission’s updated version

On 19 November, the European Commission is expected to present its official simplification package. This section will be updated once the final text is published.

Final remarks

Simplification in itself is a good idea, and businesses need to have enough freedom to operate without being suffocated with red tape. However, changing a cornerstone of data protection law to such an extent that it threatens fundamental rights protections is just cause for concern.

Alarms have already been raised after the previous Omnibus package on green due diligence obligations was scrapped. We may now be witnessing a similar rollback, this time targeting digital rights.

As a result, all eyes are on 19 November, a date that could reshape not only the EU privacy standards but also global data protection norms.

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AI search tools put to the test in UK study

AI tools are shaping online searches, but testing reveals notable risks in relying on them. ChatGPT, Google Gemini, Microsoft Copilot, Meta AI, and Perplexity were tested on 40 questions in finance, law, health, and consumer rights.

Results show errors, incomplete advice, and ethical oversights remain widespread despite AI’s popularity.

More than half of UK adults now use AI for online searches, with frequent users showing higher trust in the responses. Around one in ten regularly seeks legal advice from AI, while others use it for financial or medical guidance.

Experts warn that overconfidence in AI recommendations could lead to costly mistakes, particularly when rules differ across regions in the UK.

Perplexity outperformed other tools in accuracy and reliability, while ChatGPT ranked near the bottom. Google’s AI overview (AIO) often delivers better results for legal and health queries, while its Gemini chatbot scores higher on finance and consumer questions.

Users are encouraged to verify sources, as many AI outputs cite vague or outdated references and occasionally promote questionable services.

Despite flaws, AI remains a valuable tool for basic research, summarising information quickly and highlighting key points. Experts advise using multiple AI tools and consulting professionals for complex financial, legal, or medical matters.

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