Tag: Copyright

Tech News : Copywriting Danish People Against Deepfakes

Posted on by Paul Stradling

The Danish government is planning a major legal shift to let people claim copyright over their own body, facial features, and voice, in what it says is the first European attempt to systematically tackle the threat posed by deepfakes.

A Legal Response to a Rapidly Growing Threat

Deepfakes, which are highly realistic synthetic media generated using artificial intelligence (AI), have become one of the most pressing digital threats of the past five years. By mimicking a person’s appearance, voice, and movements, these AI-generated videos, images or audio clips can convincingly impersonate individuals without their consent. Initially used for novelty and satire, they’re increasingly tied to malicious uses including fraud, harassment, and disinformation.

Massive Rise

According to a 2024 report from cybersecurity firm Sumsub, the number of detected deepfake videos worldwide rose by over a massive 700 per cent in a single year, with Europe seeing the sharpest spike. Consequently, the European Union’s law enforcement agency, Europol, has warned that deepfakes are “a significant threat to democracy and trust in institutions,” particularly around elections and public figures. However, individuals are also at risk, e.g. from revenge porn to financial scams where a cloned voice is used to impersonate a relative or company executive.

While many countries are beginning to introduce narrow legislation to deal with specific uses of deepfakes, Denmark is now attempting something broader.

What Denmark Is Proposing

Under the new proposals announced by Denmark’s Ministry of Culture in late June 2025, citizens would be granted copyright over their physical appearance, voice, and other personal traits. The hope is that this would allow them to demand the removal of AI-generated content that imitates them without permission (regardless of context) and seek compensation where harm has occurred.

Treated As A Creative Work

One important aspect of this new legal approach is that it would not rely on proving defamation or reputational damage, as is often required under existing European law. Instead, it would actually treat a person’s likeness as a creative work, similar to how a photograph or piece of music is protected. The law would apply to both private individuals and public figures, including artists and performers.

Culture Minister Jakob Engel-Schmidt described the legislation as a “bold step to protect personal identity in the age of AI,” noting that current legal protections lag behind technical capabilities. “Human beings can be run through the digital copy machine and misused for all sorts of purposes,” he said in a statement. “We are not willing to accept that.”

Timing, Process and Political Backing

The proposed changes will be submitted for public consultation before the Danish parliament breaks for summer recess, with formal legislation expected to be introduced in the autumn. Given the political climate, it’s highly likely to pass. For example, around 90 per cent of MPs reportedly support the reform, following widespread concern about the use of AI-generated content in political misinformation and online abuse.

Would Be A European First

The law would make Denmark the first European country to explicitly codify individual ownership of biometric traits for the purpose of combatting generative AI misuse. It is expected to take effect in early 2026 if passed.

What It Means in Practice

If enacted, the law would essentially give Danes the legal right to request takedowns of deepfake content from online platforms if it replicates their image, voice or body in a “realistic, digitally generated imitation.” The rule would apply whether or not the content was created with malicious intent.

Platforms that fail to comply with takedown requests could face “severe fines,” according to Engel-Schmidt. There’s also potential for EU-level action if enforcement proves challenging, particularly during Denmark’s upcoming EU presidency in 2026, when it plans to raise the issue with member states.

Includes Key Exceptions

Crucially, the proposal includes exceptions for parody and satire, which are protected under free expression rules. These carve-outs are intended to ensure that political cartoonists, satirical shows, and legitimate artistic works aren’t caught by the law.

Performances Too

The reform would also extend to artists’ performances. For example, musicians would have legal grounds to object if their voice or performance style is cloned by AI without consent, which has been a growing concern in the music industry as AI-generated songs imitate the voices of famous performers.

Why Businesses and Platforms Should Take Note

For technology companies, particularly those that operate online platforms or generate AI models, Denmark’s proposal could have far-reaching consequences.

In practical terms, businesses hosting user-generated content, such as social media platforms, image generators, or AI voice apps, may soon be legally obligated to implement mechanisms for recognising and responding to takedown requests based on biometric misuse. This could involve new detection systems, moderation processes, and audit trails to demonstrate compliance.

It also raises questions around liability. Under current EU law, platforms benefit from limited liability for illegal content they host, provided they act promptly when notified. Denmark’s new copyright-based approach might test the limits of that framework, especially if it leads to conflicts over enforcement or definitions of consent.

For creative industries, including advertising, film, and gaming, the law could restrict the use of AI tools trained on real individuals without licensing agreements. While this may increase costs and licensing complexity, supporters argue it could also encourage more ethical use of synthetic media.

From a business reputation standpoint, being seen to respect biometric rights could become a key trust signal for users and customers. A 2023 survey by the European Commission found that 79 per cent of EU citizens want stronger legal safeguards on the use of AI-generated likenesses.

How Other Countries Are Approaching the Issue

Globally, it seems, few countries have gone as far as Denmark is proposing, but some are moving in the same direction.

For example, in the United States, several states have passed deepfake-specific laws, mostly focused on election interference and non-consensual pornography. California, Texas, and New York, for instance, have made it illegal to create or distribute deepfakes that impersonate political candidates within 30 to 60 days of an election. However, there is no federal law yet, and a new budget proposal being debated in Congress could strip states of their authority to regulate AI for 10 years.

In China, deepfake creators must label synthetic media clearly and obtain consent from the people being replicated. Failure to comply can result in heavy fines. South Korea is also considering similar legislation, particularly to address deepfake abuse in online pornography, which has become a major social issue there.

Within Europe, the EU’s AI Act (adopted in 2024) includes provisions requiring deepfakes to be labelled as such, but it does not go as far as granting individuals copyright over their features. That’s why Denmark’s move is seen as a potential model for broader reforms.

What Challenges Remain?

Despite strong domestic support, Denmark’s proposal is not without critics. For example, some legal scholars have raised questions about how biometric copyright would be enforced across borders, especially on platforms based outside the EU. Others argue that tying personal identity to copyright, a system traditionally designed to protect creative works, may lead to unintended legal consequences.

There are also practical concerns, e.g. identifying a deepfake is not always straightforward, and takedown systems are often slow or ineffective. If enforcement relies heavily on users flagging violations, the burden may fall disproportionately on individuals without the resources or knowledge to pursue their rights.

For now, however, Denmark appears determined to lead the way by betting that stronger individual protections are the only way to restore trust in a digital landscape where seeing is no longer believing.

What Does This Mean For Your Business?

If Denmark succeeds in passing this reform, it could change how personal identity is treated under copyright law, not just nationally, but across Europe. By legally enshrining the right to control one’s own voice, face, and likeness, the country is effectively trying to redraw the boundary between creative freedom and personal protection in the age of synthetic media. For individuals, this could offer an unprecedented tool to fight back against misuse, without needing to prove reputational harm or navigate complex defamation law.

For UK businesses, particularly those in tech, media, and advertising, Denmark’s approach may offer a glimpse of what’s to come. If other EU countries follow suit, companies that operate across borders could face new compliance demands, from biometric consent processes to proactive takedown mechanisms. At the same time, businesses that adopt strong safeguards now, such as consent-driven AI use policies, may gain a competitive advantage by building trust with customers and clients. For those in the creative sector, for example, the move could also help clarify the grey area around training AI models on real human traits, especially in performance-heavy fields like music, voiceover, or influencer marketing.

However, enforcement remains a key challenge. For example, without international alignment, cross-border takedowns could prove difficult, and smaller platforms may struggle to implement the necessary safeguards. There’s also a risk that applying copyright principles to human identity could lead to unintended consequences, particularly if courts are left to interpret the balance between personal rights and creative expression.

Even so, Denmark’s proposed law appears to reflect a broader global reckoning with the risks of generative AI. It signals that governments are no longer willing to let platforms set the terms of engagement when it comes to biometric misuse. With deepfakes set to become more sophisticated and widespread, that signal may be just as important as the legal details that follow.

Tech News : Musicians Unite in Silence, Protesting AI Copyright Reforms

Posted on by Paul Stradling

Over 1,000 musicians have released a silent album, Is This What We Want?, in protest against UK copyright law changes that would allow AI companies to use copyrighted material without creators’ permission.

A Symbolic Protest

The album, comprising 12 tracks of ambient studio sounds, symbolises the artists’ concerns about the potential erosion of their rights and livelihoods in the face of advancing AI technologies.

Released on 25 February 2025, Is This What We Want? features contributions from a diverse array of artists, including luminaries such as Kate Bush, Damon Albarn, Annie Lennox, and Hans Zimmer. The album’s tracks are recordings of empty studios and performance spaces, capturing subtle ambient noises but devoid of musical content. The deliberate absence of music is designed to be a representation of the artists’ fears that their creative voices may be silenced if the proposed copyright reforms are enacted.

Also, the track titles on the ‘silent’ album collectively spell out the message: “The British Government Must Not Legalise Music Theft To Benefit AI Companies.” This is intended to highlight the unified stance of the artists against the legislative changes they believe could undermine their control over their own work.

Proposed Copyright Reforms

The impetus for this silent protest stems from the UK government’s proposal to amend copyright laws to facilitate AI development. For example, the suggested changes would allow AI companies to use copyrighted material for training models without obtaining prior consent from creators, provided the content is lawfully accessible. Creators would have the option to “opt out,” but many argue that this system places an unreasonable burden on individual artists to protect their work.

Exploitation?

Critics contend that such reforms to copyright laws could lead to widespread exploitation of creative content, effectively enabling AI firms to appropriate artists’ work without fair compensation. This concern is particularly acute in the music industry, where AI technologies are increasingly capable of generating compositions that closely mimic human-created music.

A United Front of Artists

The protest album brings together a coalition of well-known artists from various genres and backgrounds. In addition to the aforementioned contributors, the project also includes co-writing credits from hundreds more, such as Billy Ocean, The Clash, Mystery Jets, Yusuf / Cat Stevens, Riz Ahmed, Tori Amos, and Imogen Heap. This extensive participation reflects a broad consensus within the creative community about the potential threats posed by the proposed copyright changes.

Composer Max Richter, known for his contemporary classical works, has been quoted as saying that the plans not only impact musicians but also “impoverish creators” across the board, from writers to visual artists and beyond. This sentiment may resonate with many who fear that the reforms could set a precedent affecting all creative industries.

The Timing of the Release

The album’s release coincided with the closing of a public consultation on the proposed legal changes, aiming to draw attention to the potential impact on livelihoods and the UK music industry. By launching the album at this critical juncture, the artists sought to influence public opinion and encourage policymakers to reconsider the ramifications of the proposed reforms.

Reception and Impact

The silent album has garnered significant media attention and sparked public discourse on the intersection of AI and intellectual property rights. While some have praised the initiative as a powerful statement against the commodification of creative works, others question its efficacy in effecting legislative change.

All Profits To Charity

Financially, the album is directing all profits to the charity ‘Help Musicians’, supporting artists who may be adversely affected by the evolving landscape of the music industry. This charitable aspect adds a layer of altruism to the protest, highlighting the community’s commitment to safeguarding the welfare of its members.

Future Implications for Artists and the Music Industry

The protest movement and album raise critical questions about the future relationship between AI technologies and creative industries. The artists hope that their collective action will prompt the government to implement more robust protections for creators, ensuring that they retain control over how their work is used in AI training.

However, the feasibility of such protections remains uncertain. For example, the vast scale of data required to train AI models makes it challenging to monitor and control the use of individual works. Also, the global nature of the internet means that content accessible in one jurisdiction can be utilised elsewhere, complicating enforcement efforts.

All this means that artists may need to explore alternative strategies to protect their interests, such as developing new licensing frameworks that accommodate AI’s unique requirements or leveraging technology to track and manage the use of their work. Collaboration between creators, policymakers, and tech companies is also likely to be essential to establish fair and effective solutions.

Engage With the Creative Community

The controversy surrounding the proposed copyright reforms highlights the need for a balanced approach that considers the interests of all stakeholders. While fostering AI innovation is crucial for economic growth and technological advancement, it should not come at the expense of creators’ rights and livelihoods.

For large tech companies, the debate highlights the importance of engaging with the creative community to develop ethical practices that respect intellectual property. Failure to do so could lead to reputational damage and potential legal challenges.

Policymakers face the complex task of crafting legislation that supports technological progress while safeguarding the rights of creators. This requires nuanced understanding and collaboration across sectors to ensure that the benefits of AI are realised without undermining the foundations of creative industries.

What Does This Mean For Your Business?

The silent protest led by musicians highlights the deep concerns within the creative community about the potential consequences of AI-driven copyright reforms. It seems that their fears are not unfounded since AI has already demonstrated its ability to replicate and remix artistic works with increasing sophistication, thereby raising urgent questions about ownership, consent, and fair compensation. The proposed changes to UK copyright law, which would allow AI firms to use creative material without prior permission, actually represent a seismic shift in how intellectual property is protected.

At the heart of this debate lies the challenge of balancing technological progress with the rights of those who create the content AI systems rely on. Advocates for reform argue that relaxing copyright restrictions will accelerate innovation and unlock new possibilities in music and the arts. However, for many artists, this approach risks devaluing human creativity and diminishing their ability to control how their work is used. The ‘opt-out’ model, while positioned as a safeguard, places the burden on individuals rather than the companies seeking to benefit from their labour.

The collective action taken by musicians through Is This What We Want? has already been a success in terms of drawing public and media attention to the issue, demonstrating the strength of opposition to the proposed changes. While it remains to be seen whether this protest will actually influence policy decisions, it has undoubtedly reinforced the argument that AI should not be granted unrestricted access to creative works without proper safeguards.

With AI pretty much being a genie that’s out of the bottle and racing ahead of regulation, many believe that a truly constructive path forward will require cooperation between artists, policymakers, and technology companies to establish fair regulations that protect creative industries while allowing AI to develop in an ethical and sustainable manner. Licensing frameworks, transparency in data usage, and technological solutions for tracking content could all form part of a more equitable system. If AI is to be integrated into the creative world, it must be done in a way that respects the fundamental rights of those who give it the material to learn from.

Featured Article : New Certification For Copyright Compliant AI

Posted on by Paul Stradling

Following many legal challenges to AI companies about copyrighted content being scraped and used to train their AI models (without consent or payment), a new certification for copyright-compliant AI has been launched.

The Issue 

As highlighted in the recent case of the New York Times suing OpenAI over the alleged training of its AI on New York Times articles without permission for free (with the likelihood of a ‘fair use’ claim in defence), how AI companies train their models is now a big issue.

The organisation ‘Fairly Trained’ says that its new Licensed Model certification is intended to highlight this difference between AI companies who scrape data (and claim fair usage) and AI companies who license it, thereby getting permission and pay for training data (i.e. they choose to do so for ethical and legal reasons). As Fairly Trained’s CEO, Ed Newton-Rex says: “You’ve got a bunch of people who want to use licenced models and you’ve got a bunch of people who are providing those. I didn’t see any way of being able to tell them apart” 

Fairly Trained says it hopes its certification will “reinforce the principle that rights-holder consent is needed for generative AI training.” 

Fairly Trained – The Certification Initiative

The non-profit ‘Fairly Trained’ initiative has introduced a Licensed Model (L) certification for AI providers that can be obtained by (awarded to) any generative AI model that doesn’t use any copyrighted work without a licence.

Who? 

Fairly Trained says the certification can go to “any company, organisation, or product that makes generative AI models or services available” and meets certain criteria.

The Criteria  

The main criteria for the certification includes:

– The data used for the model(s) must be explicitly provided to the model developer for the purposes of being used as training data, or available under an open license appropriate to the use-case, or in the public domain globally, or fully owned by the model developer.

– There must be a “robust process for conducting due diligence into the training data,” including checks into the rights position of the training data provider.

– There must also be a robust process for keeping records of the training data that was used for each model training.

The Price 

In addition to meeting the criteria, AI companies will also have to pay for their certification. The price is based on an organisation’s annual revenue and ranges from $150 submission fee and $500 annual certification fee for an organisation with a $100k annual revenue to a $500 submission fee and $6,000 annual certification fee for an organisation with a $10M annual revenue.

What If The Company Changes Its Training Data Practices? 

If an organisation acquires the certification and then changes its data practices afterwards (i.e. it no longer meets the criteria), Fairly Trained says it is up to that organisation to inform Fairly Trained of the change, which suggests that there’s no pro-active checking in place. Fairly Trained does, however, say it reserves the right to withdraw certification without reimbursement if “new information comes to light” that shows an organisation no longer meets the criteria.

None Would Meet The Criteria For Text 

Although Fairly Trained accepts that its certification scheme is not an end to the debate over what creator consent should look like, the scheme does appear to have one significant flaw at the moment.

As Fairly Trained’s CEO, Ed Newton-Rex has acknowledged, it’s unlikely that any of the major text generation models could currently get certified because they have been trained upon a large amount of copyrighted work, i.e. even ChatGPT is unlikely to meet the criteria.

The AI companies argue, however, that they have had little choice but to do so because copyright protection seems to cover so many different things including blog and forum posts, photos, code, government documents, and more.

Alternative? 

Mr Newton-Rex has been reported as saying he’s hopeful that there will be models (in future) that are trained on a small amount of data and end up being licensed, and that there may also be other alternatives. Examples of some ways AI models could be trained without using copyrighted material (but probably not without consent) include:

– Using open datasets that are explicitly marked for free use, modification, and distribution. These can include government datasets, datasets released by academic institutions, or datasets available through platforms like Kaggle (provided their licenses permit such use).

– Using works that have entered the public domain, meaning copyright no longer applies. This includes many classic literary works, historical documents, and artworks. Generating synthetic data using algorithms. This could include text, images, and other media. Generative models can create new, original images based on certain parameters or styles (but could arguably still allow copyrighted styles to creep in).

– Using crowdsourcing and user contribution, i.e. contributions from users under an open license.

– Using data from sources that have been released under Creative Commons or other licenses that allow for reuse, sometimes with certain conditions (like attribution or non-commercial use).

– Partnering / collaboratiing with artists, musicians, and other creators to generate original content specifically for training the AI. This can also involve contractual agreements where the rights for AI training are clearly defined.

– Using web scraping but with strict filters to only collect data from pages that explicitly indicate the content is freely available or licensed for reuse.

Collaboration and Agreements 

Alternatively, AI companies could choose to partner with artists, musicians, and other creators to generate original content (using contractual agreements) specifically for training the AI. Also, they could choose to Enter into agreements with organisations or individuals to use private or proprietary data, ensuring that the terms of use permit AI training.

What Does This Mean For Your Business? 

It’s possible to see both sides of the argument to a degree. For example, so many things are copyrighted and AI companies such as OpenAI with ChatGPT wouldn’t have been able to create and get a reasonable generative AI chatbot out there if it had to get consent from everyone for everything and pay for all the licenses needed.

On the other hand, it’s understandable that creatives such as artists or journalistic sources such as the New York Times are angry that their output may have been used for free (with no permission) to train an LLM and thereby create the source of its value that it may then charge users for. Although the idea of providing a way to differentiate between AI companies that had paid and acquired permission (i.e. acted ethically for their training content sounds like a fair idea), the fact that the LLMs from the main AI companies (including ChatGPT) may not even meet the criteria does make it sound a little self-defeating and potentially not that useful for the time being.

Also, some would say that relying upon companies to admit when they may have changed their AI training practices and potentially lose the certification they’ve paid for (when Fairly Trained isn’t checking anyway) may also sound as though this may not work. All that said, there are other possible alternatives (as mentioned above) that could require consent and organisations working together that could result in useful, trained LLMs without copyright headaches.

Although the Fairly Trained scheme sounds reasonable, Fairly Trained admits that it’s not a definitive answer to the problem. It’s probably more likely that the outcomes of the many lawsuits will help shape how AI companies act as regards training their LLMs in the near future.

Featured Article : NY Times Sues OpenAI And Microsoft Over Alleged Copyright

Posted on by Paul Stradling

It’s been reported that The New York Times has sued OpenAI and Microsoft, alleging that they used millions of its articles without permission to help train chatbots.

The First 

It’s understood that the New York Times (NYT) is the first major US media organisation to sue ChatGPT’s creator OpenAI, plus tech giant Microsoft (which is also an OpenAI investor and creator of Copilot), over copyright issues associated with its works.

Main Allegations 

The crux of the NYT’s argument appears to be that the use of its work to create GenAI tools should come with permission and an agreement that reflects the fair value of the work. Also, it’s important in this case to note that the NYT relies on digital subscriptions rather than physical newspaper subscriptions, of which it now has 9 million+ subscribers (the relevance of which will be clear below).

With this in mind, in addition to the main allegation of training AI on its articles without permission (for free), other main allegations made by the NYT about OpenAI and Microsoft in relation to the lawsuit include :

– OpenAI and Microsoft may be trying to get a “free-ride on The Times’s massive investment in its journalism” by using it to provide another way to deliver information to readers, i.e. a way around its payment wall. For example, the NYT alleges that OpenAI and Microsoft chatbots gave users near-verbatim excerpts of its articles. The NYT’s legal team have given examples of these, such as restaurant critic Pete Wells’ 2012 review of Guy Fieri’s (of Diners, Drive-Ins, and Dives fame) “Guy’s American Kitchen & Bar”. The NYT argues that this threatens its high-quality journalism by reducing readers’ perceived need to visit its website, thereby reducing its web traffic, and potentially reducing its revenue from advertising and from the digital subscriptions that now make up most of its readership.

– Misinformation from OpenAI’s (and Microsoft’s) chatbots, in the form of errors and so-called ‘AI hallucinations’ make it harder for readers to tell fact from fiction, including when their technology falsely attributes information to the newspaper. The NYT’s legal team cite examples of where this may be the case, such as ChatGPT once falsely attributing two recommendations for office chairs to its Wirecutter product review website.

“Fair Use” And Transformative 

In their defence, Open AI and Microsoft appear likely to be relying mainly on the arguments that the training of AI on NYT’s content amounts to “fair use” and the outputs of the chatbots are “transformative.”

For example, under US law, “fair use” is a doctrine that allows limited use of copyrighted material without permission or payment, especially for purposes like criticism, comment, news reporting, teaching, scholarship, or research. Determining whether a specific use qualifies as fair use, however, will involve considering factors like the purpose and character of the usage. For example, the use must be “transformative”, i.e. adding something new or altering the original work in a significant way (often for a different purpose). OpenAI and Microsoft may therefore argue that training their AI products could potentially be seen as transformative as the AI uses the newspaper content in a way that is different from the original purpose of news reporting or commentary. However, the NYT has already stated that: “There is nothing ‘transformative’ about using The Times’s content without payment to create products that substitute for The Times and steal audiences away from it”. Any evidence of verbatim outputs may also damage the ‘transformative’ argument for OpenAI and Microsoft.

Complicated 

Although these sound like relatively clear arguments either way, there are several factors that add to the complication of this case. These include:

– The fact that OpenAI altered its products following copyright issues, thereby making it difficult to decide whether its outputs are currently enough to find liability.

– Many possible questions about the journalistic, financial, and legal implications of generative AI for news organisations.

– Broader ethical and practical dilemmas facing media companies in the age of AI.

What Is It Going To Cost? 

Given reports that talks between all three companies to avert the lawsuit have failed to resolve the matter, what the NYT wants is:

Damages of an as yet undisclosed sum, which some say could be in the $billions (given that OpenAI is valued at $80 billion and Microsoft has invested $13 billion in a for-profit subsidiary).

For OpenAI and Microsoft to destroy the chatbot models and training sets that incorporate the NYT’s material.

Many Other Examples

AI companies like OpenAI are now facing many legal challenges of a similar nature, e.g. the scraping/automatic collection of online content/data by AI without compensation, and for other related reasons. For example:

– A class action lawsuit filed in the Northern District of California accuses OpenAI and Microsoft of scraping personal data from internet users, alleging violations of privacy, intellectual property, and anti-hacking laws. The plaintiffs claim that this practice violates the Computer Fraud and Abuse Act (CFAA).

– Google has been accused in a class-action lawsuit of misusing large amounts of personal information and copyrighted material to train its AI systems. This case raises issues about the boundaries of data use and copyright infringement in the context of AI training.

– A Stability AI, Midjourney, and DeviantArt class action claims that these companies used copyrighted images to train their AI systems without permission. The key issue in this lawsuit is likely to be whether the training of AI models with copyrighted content, particularly visual art, constitutes copyright infringement. The challenge lies in proving infringement, as the generated art may not directly resemble the training images. The involvement of Large-scale Artificial Intelligence Open Network (LAION) in compiling images used for training adds another layer of complexity to the case.

– Back in February 2023, Getty Images sued Stability AI alleging that it had copied 12 million images to train its AI model without permission or compensation.

The Actors and Writers Strike 

The recent strike by Hollywood actors and writers is another example of how fears about AI, consent, and copyright, plus the possible effects of AI on eroding the value of people’s work and jeopardising their income are now of real concern. For example, the strike was primarily focused on concerns regarding the use of AI in the entertainment industry. Writers, represented by the Writers Guild of America, were worried about AI being used to write or complete scripts, potentially affecting their jobs and pay. Actors, under SAG-AFTRA, protested against proposals to use AI to scan and use their likenesses indefinitely without ongoing consent or compensation.

Disputes like this, and the many lawsuits against AI companies highlight the urgent need for clear policies and regulations on AI’s use, and the fear that AI’s advance is fast outstripping the ability for laws to keep up.

What Does This Mean For Your Business? 

We’re still very much at the beginning of a fast-evolving generative AI revolution. As such, lawsuits against AI companies like Google, Meta, Microsoft, and OpenAI are now challenging the legal limits of gathering training material for AI models from public databases. These types of cases are likely to help to shape the legal framework around what is permissible in the realm of data-scraping for AI purposes going forward.

The NYT/OpenAI/Microsoft lawsuit and other examples, therefore, demonstrate the evolving legal landscape as courts now try to grapple with the implications of AI technology on copyright, privacy, and data use laws, and its complexities. Each case will contribute to defining the boundaries and acceptable practices in the use of online content for AI training purposes, and it will be very interesting to see whether arguments like “fair use” are enough to stand up to the pressure from multiple companies and industries. It will also be interesting to see what penalties (if things go the wrong way for OpenAI and others) will be deemed suitable, both in terms of possible compensation and/or the destruction of whole models and training sets.

For businesses (who are now able to create their own specialised, tailored chatbots), these major lawsuits should serve as a warning to be very careful in the training of their chatbots and to think carefully about any legal implications, and to focus on creating chatbots that are not just effective but are also likely to be compliant.