How to tell if your favourite new artist is AI-generated

A recent BBC report examines how listeners can determine whether AI-generated music AI actually from an artist or a song they love. With AI-generated music rising sharply on streaming platforms, specialists say fans may increasingly struggle to distinguish human artists from synthetic ones.

One early indicator is the absence of a tangible presence in the real world. The Velvet Sundown, a band that went viral last summer, had no live performances, few social media traces and unusually polished images, leading many to suspect they were AI-made.

They later described themselves as a synthetic project guided by humans but built with AI tools, leaving some fans feeling misled.

Experts interviewed by the BBC note that AI music often feels formulaic. Melodies may lack emotional tension or storytelling. Vocals can seem breathless or overly smooth, with slurred consonants or strange harmonies appearing in the background.

Lyrics tend to follow strict grammatical rules, unlike the ambiguous or poetic phrasing found in memorable human writing. Productivity can also be a giveaway: releasing several near-identical albums at once is a pattern seen in AI-generated acts.

Musicians such as Imogen Heap are experimenting with AI in clearer ways. Heap has built an AI voice model, ai.Mogen, who appears as a credited collaborator on her recent work. She argues that transparency is essential and compares metadata for AI usage to ingredients on food labels.

Industry shifts are underway: Deezer now tags some AI-generated tracks, and Spotify plans a metadata system that lets artists declare how AI contributed to a song.

The debate ultimately turns on whether listeners deserve complete transparency. If a track resonates emotionally, the origins may not matter. Many artists who protest against AI training on their music believe that fans deserve to make informed choices as synthetic music becomes more prevalent.

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India confronts rising deepfake abuse as AI tools spread

Deepfake abuse is accelerating across India as AI tools make it easy to fabricate convincing videos and images. Researchers warn that manipulated media now fuels fraud, political disinformation and targeted harassment. Public awareness often lags behind the pace of generative technology.

Recent cases involving Ranveer Singh and Aamir Khan showed how synthetic political endorsements can spread rapidly online. Investigators say cloned voices and fabricated footage circulated widely during election periods. Rights groups warn that such incidents undermine trust in media and public institutions.

Women face rising risks from non-consensual deepfakes used for harassment, blackmail and intimidation. Cases involving Rashmika Mandanna and Girija Oak intensified calls for stronger protections. Victims report significant emotional harm as edited images spread online.

Security analysts warn that deepfakes pose growing risks to privacy, dignity and personal safety. Users can watch for cues such as uneven lighting, distorted edges, or overly clean audio. Experts also advise limiting the sharing of media and using strong passwords and privacy controls.

Digital safety groups urge people to avoid engaging with manipulated content and to report suspected abuse promptly. Awareness and early detection remain critical as cases continue to rise. Policymakers are being encouraged to expand safeguards and invest in public education on emerging risks associated with AI.

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Creativity that AI cannot reshape

A landmark ruling in Munich has put renewed pressure on AI developers, following a German court’s finding that OpenAI is liable for reproducing copyrighted song lyrics in outputs generated by GPT-4 and GPT-4o. The judges rejected OpenAI’s argument that the system merely predicts text without storing training data, stressing the long-established EU principle of technological neutrality that, regardless of the medium, vinyl, MP3, or AI output, the unauthorised reproduction of protected works remains infringement.

Because the models produced lyrics nearly identical to the originals, the court concluded that they had memorised and therefore stored copyrighted content. The ruling dismantled OpenAI’s attempt to shift responsibility to users by claiming that any copying occurs only at the output stage.

Judges found this implausible, noting that simple prompts could not have ‘accidentally’ produced full, complex song verses without the model retaining them internally. Arguments around coincidence, probability, or so-called ‘hallucinations’ were dismissed, with the court highlighting that even partially altered lyrics remain protected if their creative structure survives.

As Anita Lamprecht explains in her blog, the judgement reinforces that AI systems are not neutral tools like tape recorders but active presenters of content shaped by their architecture and training data.

A deeper issue lies beneath the legal reasoning, the nature of creativity itself. The court inferred that highly original works, which are statistically unique, force AI systems into a kind of memorisation because such material cannot be reliably reproduced through generalisation alone.

That suggests that when models encounter high-entropy, creative texts during training, they must internalise them to mimic their structure, making infringement difficult to avoid. Even if this memorisation is a technical necessity, the judges stressed that it falls outside the EU’s text and data mining exemptions.

The case signals a turning point for AI regulation. It exposes contradictions between what companies claim in court and what their internal guidelines acknowledge. OpenAI’s own model specifications describe the output of lyrics as ‘reproduction’.

As Lamprecht notes, the ruling demonstrates that traditional legal principles remain resilient even as technology shifts from physical formats to vector space. It also hints at a future where regulation must reach inside AI systems themselves, requiring architectures that are legible to the law and laws that can be enforced directly within the models.

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Google launches Nano Banana Pro image model

Google has launched Nano Banana Pro, a new image generation and editing model built on Gemini 3 Pro. The upgrade expands Gemini’s visual capabilities inside the Gemini app, Google Ads, Google AI Studio, Vertex AI and Workspace tools.

Nano Banana Pro focuses on cleaner text rendering, richer world knowledge and tighter control over style and layout. Creators can produce infographics, diagrams and character consistent scenes, and refine lighting, camera angle or composition with detailed prompts.

The AI model supports higher resolution visuals, localised text in multiple languages and more accurate handling of complex scripts. Google highlights uses in marketing materials, business presentations and professional design workflows, as partners such as Adobe integrate the model into Firefly and Photoshop.

Users can try Nano Banana Pro through Gemini with usage limits, while paying customers and enterprises gain extended access. Google embeds watermarking and C2PA-style metadata to help identify AI-generated images, foregrounding safety and transparency around synthetic content.

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Creative industries seek rights protection amid AI surge

British novelists are raising concerns that AI could replace their work, with nearly half saying the technology could ‘entirely replace’ them. The MCTD survey of 332 authors found deep unease about the impact of generative tools trained on vast fiction datasets.

About 97% of novelists expressed intense negativity towards the idea of AI writing complete novels, while around 40% said their income from related work had already suffered. Many authors have reported that their work has been used to train large language models without their permission or payment.

While 80 % agreed AI offers societal benefits, authors called for better protections, including copyright reform and consent-based use of their work. MCTD Executive Director Prof. Gina Neff stressed that creative industries are not expendable in the AI race.

A UK government spokesperson said collaboration between the AI sector and creative industries is vital, with a focus on innovation and protection for creators. But writers say urgent action is needed to ensure their rights are upheld.

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New AI co-pilot uses CAD software to generate 3D designs

MIT engineers have developed a novel AI system able to use CAD software in a human-like way, controlling the interface with clicks, drags and menu commands to build 3D models from 2D sketches.

The team created a dataset called VideoCAD, comprising more than 41,000 real CAD session videos that explicitly show how users build shapes step-by-step, including mouse movement, keyboard commands and UI interactions.

By learning from this data, the AI agent can translate high-level design intents, such as ‘draw a line’ or ‘extrude a shape’, into specific UI actions like clicking a tool, dragging over a sketch region and executing the command.

When given a 2D drawing, the AI generates a complete 3D model by replicating the sequence of UI interactions a human designer would use. The researchers tested this on a variety of objects, from simple brackets to more complex architectural shapes.

The long-term vision is to build an AI-enabled CAD co-pilot. This tool not only automates repetitive modelling tasks but also works collaboratively with human designers to suggest next steps, speed up workflows or handle tedious operations.

The researchers argue this could significantly lower the barrier to entry for CAD use, making 3D design accessible to people without years of training.

From a digital economy and innovation policy perspective, this development is significant. It demonstrates how AI-driven UI agents are evolving, not just processing text or data, but also driving complex, creative software. That raises questions around intellectual property (who owns the design if the AI builds it?), productivity (will it replace or support designers?) and education (how will CAD teaching adapt?).

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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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Fight over state AI authority heats up in US Congress

US House Republicans are mounting a new effort to block individual states from regulating AI, reviving a proposal that the Senate overwhelmingly rejected just four months ago. Their push aligns with President Donald Trump’s call for a single federal AI standard, which he argues is necessary to avoid a ‘patchwork’ of state-level rules that he claims hinder economic growth and fuel what he described as ‘woke AI.’

House Majority Leader Steve Scalise is now attempting to insert the measure into the National Defence Authorisation Act, a must-pass annual defence spending bill expected to be finalised in the coming weeks. If successful, the move would place a moratorium on state-level AI regulation, effectively ending the states’ current role as the primary rule-setters on issues ranging from child safety and algorithmic fairness to workforce impacts.

The proposal faces significant resistance, including from within the Republican Party. Lawmakers who blocked the earlier attempt in July warned that stripping states of their authority could weaken protections in areas such as copyright, child safety, and political speech.

Critics, such as Senator Marsha Blackburn and Florida Governor Ron DeSantis, argue that the measure would amount to a handout to Big Tech and leave states unable to guard against the use of predatory or intrusive AI.

Congressional leaders hope to reach a deal before the Thanksgiving recess, but the ultimate fate of the measure remains uncertain. Any version of the moratorium would still need bipartisan support in the Senate, where most legislation requires 60 votes to advance.

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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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Cloudflare buys AI platform Replicate

Cloudflare has agreed to purchase Replicate, a platform simplifying the deployment and running of AI models. The technology aims to cut down on GPU hardware and infrastructure needs typically required for complex AI.

The acquisition will integrate Replicate’s extensive library of over 50,000 AI models into the Cloudflare platform. Developers can then access and deploy any AI model globally using just a single line of code for rapid implementation.

Matthew Prince, Cloudflare’s chief executive, stated the acquisition will make his company the ‘most seamless, all-in-one shop for AI development’. The move abstracts away infrastructure complexities so developers can focus only on delivering amazing products.

Replicate had previously raised $40m in venture funding from prominent investors in the US. Integrating Replicate’s community and models with Cloudflare’s global network will create a singular platform for building tomorrow’s next big AI applications.

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