AI and the Law

A recent exchange between Anthropic CEO Dario Amodei and investor Gavin Baker has highlighted the complexities surrounding artificial intelligence regulation. The debate centers on whether warnings about AI risks have contributed to a backlash against data centers in the United States.

Gavin Baker, an investor who has been vocal about his concerns regarding AI’s impact, argued that Amodei’s warnings have ‘lost the argument’ when it comes to AI regulation. He claimed that Amodei should focus on being a more positive advocate for the industry, given his position as CEO of one of the most influential companies in the field.

Baker is not alone in criticizing AI executives for their dire predictions about the technology’s future. Some argue that government crackdowns and public skepticism are natural responses to these warnings. However, Amodei has pushed back against this notion, stating that his messaging on AI risks has been balanced between cautionary notes and potential benefits.

In a series of posts, Amodei emphasized that he wrote his essay ‘Machines of Loving Grace’ because the industry was not doing enough to showcase AI’s transformative capabilities. He argued that ordinary people have a negative view of AI due to a lack of trust in companies, governments, and the tech industry as a whole.

According to Amodei, this crisis of trust has been decades in the making, with the current backlash being just one iteration of it. The CEO attributed the public’s skepticism to the fact that AI companies have not yet delivered on their promises to benefit society. He acknowledged that this is ‘totally on us’ and should be the focus of criticism rather than messaging or marketing.

Amodei also addressed concerns about regulation, arguing that Baker presented a false dichotomy between distributing AI widely without oversight and concentrating it in the hands of a few companies through regulation. The CEO emphasized that many people outside Silicon Valley view regulation as a means to constrain corporate power and benefit ordinary citizens.

In his posts, Amodei highlighted Anthropic’s policy proposals, which aim to disadvantage large frontier AI companies while benefiting smaller competitors. He stated that these proposals are designed to address the concentration of power in the industry and mitigate risks associated with advanced AI technologies.

Amodei acknowledged that open-weights models can help alleviate some concerns about AI’s impact on society but noted that they do not provide a sufficient solution. Instead, he advocated for clear ‘rules of the road’ that balance addressing AI-related risks with institutional constraints on large companies and room for smaller competitors to operate.

The debate between Amodei and Baker highlights the complexities surrounding AI regulation and the need for nuanced discussions about its potential benefits and drawbacks. As the industry continues to evolve, it is essential to address concerns about trust, power concentration, and risk mitigation in a comprehensive manner.

A new wave of policy ideas is emerging to address the challenges and opportunities presented by advanced artificial intelligence. OpenAI has announced a series of grants to support independent projects that aim to promote economic opportunity and societal resilience in the face of rapid AI advancements.

The 14 selected projects, led by organizations from around the world, will receive funding and API credits totaling $2 million. These initiatives span various themes, including the distribution of AI-driven productivity gains, access to AI ownership, and the development of new policy models for a rapidly changing economy.

According to OpenAI’s commitment outlined in their report ‘Industrial Policy for the Intelligence Age’ published in April 2026, these grants aim to support others in testing, challenging, and building on the ideas presented. The goal is to ensure that advanced AI benefits everyone, not just a select few.

The rapid advancement of AI capabilities has significant implications for how people learn, create, and participate in the economy. With ChatGPT reaching 1 billion users worldwide across various demographics, it’s clear that access to technology alone is only part of the equation. The choices societies make about deploying and distributing AI benefits will determine whether this technology serves the many or just a privileged few.

The policy response must be as ambitious as the technological change itself. This requires new approaches rather than adjustments to existing policies. In democratic societies, these decisions should be shaped through democratic institutions and public debate, with independent research and policy organizations playing an essential role in developing and testing new ideas.

Through these grants, researchers and practitioners will turn high-level concepts into concrete work, examining what could work, the potential costs, and how approaches can be implemented responsibly. Over 400 people and organizations responded to OpenAI’s call for proposals, with applicants identifying specific ideas that could meaningfully contribute to public understanding and policy development.

The selected projects span various countries, including the United States, European Union, Brazil, Singapore, and South Korea. They address two broad questions: how AI can broaden economic opportunity and how societies can build resilience as capabilities advance. Some will produce research and policy models, while others will develop prototypes, datasets, and frameworks that can be tested in practice.

For example, the American Enterprise Institute’s AEI-Urban Bipartisan Commission on Artificial Intelligence and the Future of the American Workforce aims to develop low-, moderate-, and high-disruption scenarios for AI’s effects on employment and skills. This will connect observable indicators of disruption to policy playbooks.

Another project, ‘Sharing the AI Dividend’ by Centre for European Policy Studies (CEPS), examines how AI-driven productivity gains are distributed across workers, firms, sectors, regions, and countries in Europe. The goal is to develop innovative policy principles for a renewed European social investment model and adaptive safety nets to ensure that AI-driven prosperity is broadly shared.

The projects will run for six months, with results reported in 2027. OpenAI’s commitment to supporting independent institutions around the world as they test new ideas reflects their recognition of the need for diverse perspectives and expertise in addressing the challenges of the Intelligence Age.

In ‘Industrial Policy for the Intelligence Age’, OpenAI argued that governments should be prepared to use a full policy toolbox, from research funding and workforce development to market-shaping tools and targeted regulation. However, no company or government has all the answers. These grants aim to widen the circle of people developing policies by supporting independent institutions as they test new ideas, build evidence, and help democratic societies decide how AI can expand opportunity and strengthen resilience.

The results from these projects will inform a broader public debate about the policies required for the Intelligence Age. By engaging with diverse stakeholders and fostering collaboration between researchers, policymakers, and practitioners, OpenAI hopes to contribute to a more comprehensive understanding of the challenges and opportunities presented by advanced AI.

A recent blog post from Anthropic aims to address concerns about its plan to watermark text generated by the chatbot Claude. The move is in compliance with the EU AI Act’s Transparency Code, which requires AI companies to use systems that make it possible to identify AI-generated content.

Claude users have been debating this decision on Reddit and other platforms, with some expressing concern that watermarks could be seen as a ‘conspiracy against innocent Claude users.’ Others argue that having transparent information about AI-generated text is essential for maintaining trust in these tools.

Anthropic’s new post explains the watermarking concept by comparing it to making low-stakes choices. For example, when describing the weather, Claude might choose between ‘overcast’ and ‘grey’. In this case, the model can create a pattern that is undetectable to readers but detectable with a key.

The company emphasizes that watermarks do not impact the quality of Claude’s output. To a reader, a watermarked response should be indistinguishable from an unwatermarked one.

Anthropic will use the SynthID-Text approach developed by Google DeepMind in 2024 to implement its watermarking system. Additionally, it plans to release a watermark detection API for developers and researchers.

The company also clarifies that watermarking is distinct from AI detection approaches offered by companies like Pangram. These methods look for ‘tells’ in the writing, such as specific constructions or word choices, whereas watermarks are unique identifiers embedded within the text itself.

Some users have expressed concerns about whether it’s possible to rewrite or edit a watermarked text to remove the watermark completely. Anthropic acknowledges that this might be feasible with significant editing efforts but notes that ‘a complete rewrite where every word is replaced’ would likely eliminate the watermark entirely.

The company also addresses the issue of code, stating that it should have less of a watermark than other text because the model needs to create working code and has limited freedom in making choices. However, Anthropic suggests that watermarks can still be used in certain areas, such as comments within code, but with negligible effect on actual code produced.

Anthropic’s move is part of its compliance efforts under the EU AI Act’s Transparency Code. The company notes that other major model developers have signed this Code and will implement their own watermarks to ensure transparency in AI-generated content.

Claude users are facing an unexpected change in how their work is handled by the Anthropic model. Starting immediately, all media created with Claude will include invisible watermarks that identify it as AI-generated content. This move has sparked a heated debate among users who claim they cannot opt out of this new policy.

The decision to implement these watermarks comes after Anthropic announced its compliance with European Union regulations regarding transparency in AI-generated content. The ‘Code of Practice on Transparency of AI-Generated Content’ sets rules for marking and detecting AI-created media, including text, images, audio, and video. As part of this agreement, nearly 200 companies have signed up to comply, including Anthropic.

Claude users are particularly upset because they claim the watermarks will degrade their work or make it unusable in certain situations. For instance, if a user copies and pastes text generated by Claude into another document, the watermark may not be visible due to heavy editing. Similarly, metadata attached to images created with Claude could disappear if the file format changes.

The backlash against this policy has been swift on social media platforms like X and Reddit. Users have expressed their discontent, calling it ‘hugely problematic’ and an end to ‘the era of unprovable AI writing.’ Some users who rely on Claude for proofreading text they’ve written themselves are concerned that the watermark will reveal their use of AI tools.

A radio show host and blogger, Erick Erickson, posted a scathing review on X: ‘I had ditched Grammarly for Claude because it does a better job. But now my work will be watermarked as being generated by Claude.’ His comment highlights one of the main concerns users have – that their work is no longer entirely theirs.

The debate surrounding AI-generated content has also sparked discussions about who should receive credit for this type of work. Some argue that human users should get credit, not the machine itself. Others claim that acknowledging the AI’s role in creating the content is essential and fair. One Reddit user started a vigorous discussion by stating: ‘I gave the instructions, context, decisions, and countless refinements; Claude was just the tool.’

Anthropic has emphasized that its decision to implement watermarks aligns with EU regulations and aims to increase transparency around AI-generated media. However, users are still concerned about how this will affect their work and whether it’s a necessary step towards accountability.

The use of invisible watermarks is not new; Google has been watermarking its AI-generated images since 2023 and has expanded the practice to text, audio, and video. OpenAI also uses similar technology for image watermarking but has chosen not to release it due to concerns about false positives and circumvention.

It’s worth noting that this policy change affects all Claude models and products worldwide, including Claude Code and Claude Cowork. Users cannot opt out of the new policy, which will apply uniformly across Anthropic’s offerings.

Claude, the artificial intelligence model developed by Anthropic, will soon start watermarking its generated content. This move is in compliance with EU rules, specifically Article 50(2) of the EU AI Act, which requires transparency in AI-generated content. The company has signed the Code of Practice on Transparency of AI-Generated Content and outlined how it plans to implement these regulations.

In a support document, Anthropic explained that models launched in the European Union (EU) after August 2, 2026, will have watermarking capabilities at launch. This includes output from various Claude platforms such as the API, Code, Cowork, and Tag. The watermarks will be embedded in generated text files and include digitally signed provenance metadata for supported file types.

The watermarking feature is not limited to Europe; it will be applied globally wherever Claude is offered. However, Anthropic notes that some platforms or features might not support certain types of watermarks. This means users may still encounter AI-generated content without visible watermarks if they don’t know what to look for.

For text files, the watermark will be integrated into the generated text itself and travel with it when copied or pasted elsewhere. For images and other file formats, Anthropic plans to use the Coalition for Content Provenance and Authenticity (C2PA) open standard. Details on recognizing these watermarks are expected in forthcoming documentation.

Existing models launched before August 2, 2026, will also receive watermarking support at a later time. However, it’s worth noting that watermarking may not be foolproof. Heavily edited or translated text might not carry detectable watermarks, and metadata can be stripped through format conversion or other means.

Anthropic’s move follows similar commitments by AI companies like OpenAI, Google, and Meta. This development aims to increase transparency in AI-generated content and help users identify the origin of such material.

Anthropic, the company behind the popular AI model Claude, has announced that it will be watermarking text generated by its models. This move is in response to the European Union’s (EU) new regulations on artificial intelligence, which require companies to clearly identify AI-generated or edited content.

The EU’s Transparency Code, which took effect on August 2, mandates that AI companies mark their generated or edited content in a way that can be easily identified by other systems. To comply with this regulation, Anthropic will be applying watermarks to all text generated by its models, including Claude.

All models released after August 2 will automatically include the watermarking technology, which will identify both computer-generated text and files as AI-created. For files, the company is using the C2PA open standard, a widely accepted method for verifying digital content’s authenticity.

The watermark will not only be present in new models but also extended to older ones, ensuring that all users are compliant with the EU regulations. Additionally, when users copy or paste text from an AI-generated source, the watermark will travel with it, persisting through some editing processes.

According to Anthropic’s support page, ‘the watermark is part of the text, so it will travel with the text when it’s copied and pasted elsewhere.’ However, it remains unclear how much editing users need to do to remove the watermark. We have reached out to Anthropic for clarification on this matter and will update our story accordingly.

Anthropic’s decision to implement watermarks is not unique; several other companies are also taking steps to comply with the EU regulations. Last week, AI music platform Suno announced that it would be marking tracks created on its platform after facing backlash from users and regulatory scrutiny. Newsletter service Substack has also partnered with Pangram to flag AI-generated content.

Other notable companies like Black Forest Labs, Google, Meta, Microsoft, OpenAI, and Synthesia have committed to adhering to the EU’s code, demonstrating a growing trend towards transparency in the AI industry.

A new tool from Anthropic is set to make it harder for people to pass off AI-generated content as their own. The company has announced that its Claude models will now embed an imperceptible watermark into text generated by the AI, making it easier to detect and investigate cases of plagiarism.

The watermark doesn’t change the meaning or readability of the original text but can be detected when copied and pasted. It may also persist through some editing processes, according to Anthropic. This move is part of the company’s efforts to increase transparency in line with the European Union AI Act.

A watermark is essentially a digital signature that proves ownership and authenticity of a piece of work. In this case, it will be embedded into text generated by Claude worldwide, including when accessed through cloud providers. Anthropic has also committed to providing third parties with tools to detect these watermarks.

The introduction of AI watermarking could have significant implications for the publishing industry, which has been grappling with concerns over AI-generated content. Last month, a book agent pulled support for a novel after allegations emerged that its author may have used AI to write it. The writer denied any involvement, but the incident highlights the need for greater transparency and accountability.

Anthropic’s move is not an isolated one - Google DeepMind has also been watermarking text generated by its Gemini app using SynthID technology since 2024. This development could give publishers, schools, and universities another tool to investigate cases of plagiarism and make it harder for people to pass off AI-generated writing as their own.

However, there are still potential loopholes in the system. Anthropic notes that heavy editing or paraphrasing can potentially remove the watermark, making it undetectable. Additionally, finding a watermark does not necessarily prove that Claude was the original author of the content, since even proofreading or translating with its AI can leave behind a mark.

The rollout marks a significant step towards greater transparency and accountability in the use of AI-generated content. As more companies begin to adopt similar measures, it will be interesting to see how this development impacts the publishing industry and beyond.

Athropic is making changes to its language model, Claude. The company’s adjustments are a response to new regulations from the European Union.

The push for transparency in AI-generated content comes from Article 50 of the EU AI Act. This article requires companies like Anthropic to be more open about their use of this technology. As part of complying with these regulations, Anthropic has signed up to the European Union’s Code of Practice covering AI-generated content.

Starting August 2, 2026, new Claude models will include watermarks at the model level. These watermarks appear in all generated text - regardless of how it’s accessed. This includes major platforms like AWS and Anthropic’s own cloud customers such as Google Cloud and Microsoft Foundry among others.

The watermarks are one aspect of a broader plan by Athropic to increase transparency around AI-generated content. The company is also working on a system for supported files that will include signed provenance metadata based on the C2PA standard.

This framework allows users to record information about digital content, enabling verification whether a file has been processed or altered in any way. For instance, it’s particularly important when verifying AI-generated images like those created using Claude for artistic purposes - which can be used for various applications including advertising and educational materials.

Anthropic cautions that text watermarks nor signed provenance metadata should not be considered definitive proof of authorship. The company notes its models can process original material from people, resulting in the output carrying a mark indicating it was processed by Claude even if not generated entirely by humans.

The technical challenges surrounding these signals are significant with text watermarks able to travel and file metadata potentially disappearing during format conversions or re-saving. Athropic is working on providing more detailed documentation as its marking systems mature.

For businesses that rely heavily on AI tools for data analysis, the addition of watermarks marks a crucial step towards greater transparency in AI-generated material - something that can make a big difference when assessing credibility. By providing machine-readable identity, Anthropic’s watermarks offer another way to verify whether content has been processed by an AI model.

Older models won’t get these new features right away but Athropic is working on adding marking capabilities during the transition period. This will ensure all users can benefit from increased transparency in generated content - something that could help platforms more easily identify when text was processed using Claude.

The changes may also impact how customers use AI-generated images which are used for various purposes including advertising or educational materials. By providing a way to verify whether an image was created with the model, businesses can have greater confidence in their content and avoid potential issues related to mislabeled material.

As new technologies emerge like AI tools that generate data analysis solutions - transparency becomes increasingly important. With watermarks and signed provenance metadata Anthropic is taking steps to address these concerns by providing a way for platforms and organizations more easily identify when a piece of text has been processed using its language model.

Artificial intelligence is rapidly advancing, but Alaska’s policy framework has failed to keep pace. While other states have made significant strides in regulating AI, the Last Frontier remains largely unprepared for its implications. This disparity becomes apparent when examining various aspects of AI governance, from chatbots and algorithmic bias to disinformation and deepfakes.

The use of companion chatbots is a prime example of where Alaska falls short. These digital assistants are increasingly prevalent in everyday life, often interacting with children and vulnerable individuals. However, unlike many other states, Alaska has no laws requiring these chatbots to disclose their non-human nature or take steps to prevent harm. This lack of regulation leaves users exposed to potential risks.

House Bill 47, which passed this June as part of an omnibus crime bill, marked a narrow step forward for AI governance in Alaska. The legislation criminalized the creation and distribution of AI-generated child sexual abuse material and deepfake harassment. While this is a positive development, it represents only a small fraction of the comprehensive framework needed to address AI’s complexities.

Algorithmic bias is another area where Alaska lags behind. When software makes decisions about loan approvals, job interviews, or benefits applications, fairness and transparency are crucial. Yet, unlike many other states, Alaska has no requirements for explainability, audibility, or disclosure in these processes. This absence of regulation leaves individuals vulnerable to discriminatory outcomes.

Disinformation is also a pressing concern in the age of AI-generated deepfakes. With roughly 30 states having passed election-related deepfake disclosure laws ahead of this year’s midterms, Alaska stands out as an exception. The state has yet to establish meaningful safeguards against AI-generated nonconsensual intimate imagery or fabricated videos and images.

A previous attempt to address these issues was House Concurrent Resolution 3, which aimed to create a task force studying AI in Alaska and recommending policies for its use in government, education, and everyday life. Although this effort stalled, the need for comprehensive governance has only grown more pressing.

Rather than abandoning HCR 3’s goals, proponents are advocating for a new approach: establishing research capacity at the University of Alaska Fairbanks. This proposal would create a graduate-level program incorporating computer science, public policy, philosophy, and ethics to study AI and data centers in an integrated manner. By examining these two areas together, researchers can better understand their interdependencies and develop more effective policies.

The relationship between AI and data centers is crucial for policymakers. As AI use grows, so does the demand for data centers – which, in turn, fuels further AI development. This feedback loop highlights the need to address both issues simultaneously. Any Alaska framework that takes AI seriously must consider its infrastructure requirements, including electricity draw on grids, water usage, and community effects.

The ultra-rich tech giants are largely driving AI policy without input from state governments or local communities. If Alaskans want a say in this process, they should contact their legislators to revive HCR 3’s task force with real teeth and support the University of Alaska Fairbanks proposal for research capacity. By doing so, Alaska can avoid being the last state at the table when it comes to AI governance.

A new regulation in the European Union is set to change how chatbots and other AI systems interact with people. As of today, any system that talks directly to individuals within the EU must inform them they are dealing with a machine. This requirement applies not just to newly developed systems but also those already live, marking a significant shift for companies operating in this space.

The regulation, which comes into effect on August 2, 2026, is part of the AI Act and focuses specifically on Article 50. According to the European Commission’s guidance, providers of chatbots and other interactive systems must ensure users are aware they are interacting with an artificial intelligence system from the outset. This includes clear labeling and transparency measures.

Four key areas are covered by this regulation: providers, deployers, generative systems, and labelling requirements. Providers of systems that interact directly with people must design them to inform users about AI involvement. Generative systems, which produce synthetic content such as audio or images, must be marked in a machine-readable format so it can be detected as AI-generated.

Deployers also have responsibilities under this regulation. They are required to notify individuals when emotion recognition or biometric categorization systems are being used and clearly label deepfakes and AI-generated text published for public interest purposes. This includes content generated before the August 2026 deadline, although retroactive labelling is not mandatory.

One of the key aspects of this regulation is its application to existing systems already in production. It’s not a rule that only applies to new developments but rather one that requires companies to adapt their current systems to meet these new requirements. The Commission has provided guidance on how to implement these changes, including a voluntary Code of Practice on transparency of AI-generated content.

The regulation also makes it clear that providers established outside the EU are in scope if their system’s output is used within the EU. This means companies operating globally must ensure compliance with this regulation even if they’re based elsewhere. The Commission has specified that fines can reach up to €15 million or 3% of total worldwide turnover, with proportionality available for SMEs and small mid-caps.

There are two exceptions to this rule: where it’s obvious a person is dealing with AI, and when content has had human review or editorial control. The Commission emphasizes the importance of transparency in these cases, stating that superficial checks do not count as sufficient human oversight.

The regulation also applies to consumer products such as customer-service bots and AI writing tools. Dating apps have been using AI features for over a year, and subscription platforms often employ chatbots to answer paid subscriber messages. This places certain corners of the internet squarely within Article 50’s scope.

For companies operating in this space, implementing these changes will be crucial. The Commission has given providers four months to adapt their systems before the December deadline closes the gap for existing systems. Watermarking synthetic text robustly remains an unsolved problem compared to watermarking images.

The recent surge in the use of artificial intelligence (AI) to create synthetic media has prompted regulators at both federal and state levels to consider new approaches to enhance transparency and protect consumers. While efforts are underway at the federal level, California is taking a proactive stance by enacting comprehensive laws aimed at addressing the risks associated with AI-generated images, video, and audio.

The law targets transparency around AI-generated content, requiring providers of generative artificial intelligence (GenAI) systems to make visible and machine-readable disclosures as well as publicly accessible detection tools. Service providers offering users GenAI functionalities for creating or altering images, video, and audio should carefully assess the new compliance obligations and implementation timeline.

California’s initial wave of requirements became operative on August 2, marking a significant milestone in the state’s efforts to regulate AI-generated content. The law applies to GenAI services that have more than one million monthly visitors or users and are publicly accessible in California.

The act imposes rigorous disclosure and detection requirements on GenAI service providers operating in the state. Covered providers must implement both latent disclosures and a manifest disclosure option for AI-generated images, video, and audio, as well as make available a free public AI detection tool.

Latent Disclosure: Providers must embed a unique identifier that provides information about the name and version of the GenAI system used to create or alter content. This disclosure must be durable, consistent with widely accepted industry standards, and compatible with the service provider’s AI detection tool.

Manifest Disclosure Option: Covered providers must offer users the option to include a manifest disclosure in any image, video, or audio content created or altered by their GenAI system. The manifest disclosure must clearly identify the content as being AI-generated and be permanent or difficult to remove, if technically feasible.

AI Detection Tool: Providers must make available at no cost a publicly accessible tool that permits users to determine whether certain content was created or altered by its GenAI system. This tool must allow for content upload, URL submission, and application programming interface support, while ensuring the collection of user personal information is narrowly defined and not retained longer than necessary.

The law also requires providers to collect feedback from users to continually improve detection tools and their efficacy. Providers that license their GenAI systems to third parties must contractually require the licensee to maintain the system’s latent disclosure capability and revoke any noncompliant licenses within 96 hours of discovery.

California enacted CAITA in 2024, initially slated for January 1, 2026, but amended in 2025 to delay its operation until August 2, 2026. The law excludes products or services that are exclusively non-user-generated video game, television, streaming, movie, or interactive experiences.

The first set of CAITA requirements targets companies creating, coding, or producing GenAI systems with more than one million monthly users that are publicly accessible in California. By its own terms, the act does not apply to AI-generated textual content.

Additional requirements for GenAI system hosting platforms, large online platforms, and manufacturers of devices will be rolled out in 2027 and 2028. Noncompliance carries significant civil penalties, enforceable by state authorities, but there is no private right of action.

The law does not create a private right of action; instead, enforcement authority is vested in the attorney general and other state actors who may bring civil actions seeking penalties of $5,000 per violation against any covered provider. State authorities can also seek injunctive relief and recover attorney fees and costs.

CAITA represents a substantial shift in legal requirements for large-scale GenAI providers operating in California, mandating clear disclosures and robust provenance measures for AI-generated content. It sets a new bar for AI transparency compliance and will have significant operational, technical, and contractual impacts on affected businesses throughout the AI ecosystem.

A new law requiring embedded data on AI-generated images has taken effect in California, marking a significant step towards making it easier to identify such content. The legislation, which was passed in 2024, is part of a coordinated effort with the European Union’s AI Act and aims to combat election misinformation, scams, and abusive deepfakes by giving users better tools to distinguish authentic from fabricated media.

The law requires generative AI companies to embed ‘provenance’ data into their images, videos, and audio files. This information includes details such as whether the content was made using AI, which system was used, and the date it was created. The embedded data can then be verified using content authentication tools like those developed by Coalition for Content Provenance and Authenticity.

State Senator Josh Becker of Menlo Park played a key role in developing this legislation with EU lawmakers. He explained that while AI has its benefits, there is a growing concern about the misuse of AI-generated content. ‘While AI has some benefits, we’ve seen AI content used for election misinformation, for scams and abusive deepfakes,’ he said.

The California law’s next phases will roll out over the coming years. Starting January 1, large social media platforms operating in California must provide users with a way to view embedded provenance information attached to AI-generated content. Then, from 2028 onwards, phones and cameras manufactured in California will be required to capture and store this data when creating new content.

Becker acknowledged that technology is advancing faster than regulation and emphasized the need for lawmakers to move more quickly on future AI policy. He also highlighted California’s unique position as a hub for Silicon Valley and the world’s fourth-largest economy, which gives it influence well beyond its borders.

The partnership between California and the European Union marks an important step in establishing a common international framework for regulating AI-generated content. Many leaders within the AI industry have acknowledged the need for guardrails to prevent misuse of this technology. Becker emphasized that his state has both the opportunity and responsibility to regulate this industry, given its significant presence.

The new law won’t eliminate skepticism online but aims to provide users with better tools to make informed decisions about the content they consume. As part of this effort, California lawmakers worked closely with EU officials while developing the legislation so both measures could take effect simultaneously.

OpenAI has responded to Apple’s lawsuit, accusing the tech giant of mishandling its claims and making false accusations against former employees. The company argues that Apple’s actions do not live up to its reputation for attention to detail.

In February, Apple claimed it had contacted OpenAI about concerns over access to confidential information after a former employee left the company. However, in a recent filing, Apple admitted that outside lawyers emailed the wrong person due to confusion between two Asian last names. This mistake was only brought to light when OpenAI pointed out the error.

Apple also initially claimed it had discussed its allegations with OpenAI’s General Counsel, but later conceded this never happened. What is more concerning is that Apple failed to raise these specific claims during their initial conversation and instead told OpenAI they were ‘resolving any issues’. This lack of transparency has left many wondering what really went on behind the scenes.

The lawsuit accuses Chang Liu, a former employee who left Apple in January 2026, of accessing confidential information. However, emails between Liu and his former colleagues reveal that he was asked to help locate files and information for their work at Apple after leaving the company. This raises questions about how Apple manages system access when employees depart.

Apple’s accusations against Tang Tan, another former employee who served the company for over 24 years, are also under scrutiny. OpenAI argues that Tan has consistently maintained he does not want or need any confidential information from other companies. The company claims it would have been happy to work with Apple to resolve these issues if they had raised them before filing the lawsuit.

OpenAI’s response highlights a series of missteps by Apple, including making vague accusations against former employees and attempting to change its narrative after being called out on its mistakes. The company argues that Apple’s request for a preliminary injunction is based on false information and unnecessary since OpenAI does not possess any trade secrets from the tech giant.

The emails between Apple’s outside counsel, Gabriel Gross, and OpenAI’s General Counsel, Che Chang, reveal a series of miscommunications and errors. Gross initially claimed to have spoken with Chang over the phone but later admitted this was an error due to confusion between two Asian last names. The specific claims in Apple’s lawsuit were never raised during their initial conversation.

A closer look at these emails shows that Gross inadvertently sent a message intended for another former employee, Wang, instead of Che Chang. This mistake led to further confusion and miscommunication between the parties involved. OpenAI argues that this sequence of events raises serious questions about Apple’s handling of its claims and its treatment of former employees.

The emails also reveal that Gross apologized for the confusion caused by his mistake and claimed they were ‘resolving any issues’. However, it is clear from the subsequent exchange that these specific allegations in the lawsuit were never raised during their initial conversation. This lack of transparency has left OpenAI wondering what really went on behind the scenes.

OpenAI’s response to Apple’s lawsuit highlights a series of missteps by the tech giant and raises questions about its handling of former employees’ access to confidential information. The company argues that it would have been happy to work with Apple to resolve these issues if they had raised them before filing the lawsuit. However, instead of addressing the concerns directly, Apple chose to pursue a lawsuit based on false information.

The emails between Chang Liu and his former colleagues reveal that he was asked to help locate files and information for their work at Apple after leaving the company. This raises questions about how Apple manages system access when employees depart. OpenAI argues that this is a common issue with Apple caused by failing to properly manage system access when people leave.

The lawsuit against Tang Tan accuses him of trying to get and use trade secrets from Apple. However, OpenAI points out that Tan has consistently maintained he does not want or need any confidential information from other companies. The company argues that this is a clear example of Apple’s attempt to shift the blame onto former employees rather than taking responsibility for its own mistakes.

OpenAI wishes it had been given the opportunity to work with Apple to resolve these issues before the lawsuit was filed. Instead, they are left to respond to Apple’s accusations and defend themselves against what OpenAI sees as baseless claims.

The White House has finalized its framework for reviewing advanced artificial intelligence models. According to an administration official, the blueprint outlines how the federal government will work with leading AI developers before and after their most sophisticated models are deployed.

A meeting is scheduled on Tuesday between industry leaders and officials from the Office of the National Cyber Director, where a draft of the framework will be reviewed. Representatives from Anthropic, Google, Meta, and OpenAI have been invited to attend, along with other top AI companies.

The development comes as part of the Trump administration’s efforts to address potential safety and national security risks associated with advanced AI technology. The White House has opted for a light-touch regulatory approach, but critics argue that this may not be sufficient to mitigate the risks involved.

A June 2nd executive order outlined the voluntary framework, which was completed by its deadline of August 1st. However, it remains unclear whether the framework will be publicly released or remain confidential within industry circles.

The White House has been working closely with leading AI companies over the past few weeks to refine the contours of the framework. Google, OpenAI, and Anthropic jointly reviewed a draft in late July and submitted edits before its completion.

Despite the lack of clarity on public release, discussions are underway between the White House and industry leaders about next steps. The voluntary nature of the order raises questions about how companies not briefed by the White House will be able to opt-in if it is not released more widely.

The deadline for completing the framework was set 60 days after the executive order was signed, as stipulated in the order itself.

A US District Judge has denied, in part, a motion to dismiss from web scraper SerpApi, which is accused of conspiring with Perplexity AI to illegally scrape copyrighted Reddit content. The decision came on Friday and marks the latest development in a complex case that involves Google search results and copyright law.

The judge’s opinion suggests that at this early stage, Reddit has made a plausible argument that there was indeed a conspiracy between SerpApi and Perplexity AI. According to the ruling, SerpApi provided a product designed to circumvent Google access controls, while Perplexity AI paid for it.

This decision is significant because it shows that Reddit’s claims have some merit, even if they are still in their early stages. The company will now need to prove three key points: first, that SerpApi and Perplexity AI conspired to access copyrighted content; second, that this content was protected by a technological measure controlling access; and third, that the defendants circumvented that technology.

Interestingly, Google had previously faced a similar lawsuit from Reddit, which also involved allegations of copyright infringement. However, in that case, the court dismissed the action because it found that Google had not proven that rights holders like Reddit had authorized the search engine to prevent scraping of protected content.

The outcome is likely to be disappointing for web scrapers like SerpApi, who claim that both Google and Reddit are trying to ‘use the DMCA to wall off the open Internet by retroactively claiming control over content they didn’t author and don’t own.’

Google has stated its intention to amend its complaint in response to this decision. Meanwhile, SerpApi remains committed to defending itself against these allegations.

The European Union has taken a significant step towards establishing a comprehensive framework for artificial intelligence (AI) with the introduction of the AI Act. This landmark legislation aims to address the risks associated with AI and position Europe as a leader in the global AI landscape.

The AI Act, Regulation (EU) 2024/1689 laying down harmonised rules on artificial intelligence, is the first-ever comprehensive legal framework on AI worldwide. Its primary objective is to foster trustworthy AI in Europe by setting out clear guidelines for developers and deployers of AI systems.

To achieve this goal, the AI Act introduces a risk-based approach that categorizes AI systems into four levels of risk: unacceptable, high, transparency, and minimal or no risk. This framework allows authorities to focus on the most critical areas while minimizing unnecessary regulatory burdens.

The AI Act sets out specific rules for each level of risk. For instance, unacceptable-risk AI systems are banned outright, with nine practices prohibited under the legislation. These include harmful manipulation and deception, social scoring, and untargeted scraping of internet or CCTV material to create facial recognition databases.

High-risk AI use cases pose serious risks to health, safety, or fundamental rights. Examples include AI safety components in critical infrastructure, such as transport systems, where failure could put lives at risk. Other high-risk areas include education institutions, employment management, and access to essential services like credit scoring.

The AI Act also introduces transparency obligations for providers of generative AI models. This includes ensuring that humans are informed when interacting with chatbots or other AI-generated content. Additionally, AI-generated images, audio, and text must be clearly labelled as such.

Minimal-risk AI systems, which include applications like video games and spam filters, are not subject to the same level of regulation under the AI Act. However, providers of high-risk AI systems will need to adhere to strict obligations before placing their products on the market.

These obligations include conducting thorough risk assessments, ensuring high-quality datasets, logging activity for traceability, providing detailed documentation, and implementing human oversight measures. Transparency is also crucial, with clear information provided to deployers and users about the system’s purpose and functionality.

The AI Act has a phased implementation timeline, with some provisions taking effect earlier than others. For instance, prohibited practices and AI literacy obligations entered into application on 2 February 2025, while governance rules and GPAI model obligations became applicable on 2 August 2025.

Going forward, the European Commission’s AI Office will play a key role in implementing and enforcing the AI Act. The office has already published guidelines to support compliance with transparency rules for generative AI models. Additionally, the Code of Practice on marking and labelling of AI-generated content is under preparation and expected to be published in 2026.

The AI Omnibus package, adopted in November 2025, aims to simplify the implementation of the AI Act by clarifying certain provisions and introducing new rules for high-risk AI systems. This includes a clear timeline for applying rules governing these systems, with some areas subject to stricter regulations from December 2027 onwards.

In conclusion, the AI Act represents a significant step towards establishing trust in AI across Europe. By setting out comprehensive guidelines for developers and deployers of AI systems, this legislation aims to promote innovation while safeguarding fundamental rights and public trust.

A new law in California is putting the spotlight on artificial intelligence (AI) transparency, particularly when it comes to synthetic media. The state’s AI Transparency Act has taken effect, and companies that fail to comply face significant fines. According to the law, any provider of generative AI tools must offer a free public tool for assessing whether an image, video, or audio clip was created or altered by their system. This includes placing a latent disclosure in those files and giving users the option of a visible, manifest disclosure.

The threshold for this requirement is set at more than 1 million monthly visitors or users for a publicly accessible generative AI system in California. If a company’s tool meets these criteria, they must ensure that their synthetic media carries a clear indication of its origin. This can be achieved through watermarking or other methods that provide machine-readable signals around the content.

The law is part of an effort to combat deepfakes and other forms of AI-generated synthetic media that can deceive users. The California Legislature’s bill text emphasizes the importance of transparency in this area, stating that a blog post about safety will not suffice as compliance. Companies must implement working disclosure machinery that allows users to assess whether an image or video was created by their system.

The penalty for non-compliance is steep. Covered providers can face a civil penalty of $5,000 per violation, collected by the California Attorney General, a city attorney, or a county counsel. Each day in violation counts as a separate offense, making it expensive to ignore this requirement. The law’s authors are clear that they expect companies to take proactive steps towards transparency.

The original operative date for this law was January 1, 2026, but it has been amended by AB 853 to August 2, 2026. This change coincides with the European Commission’s implementation of Article 50 of the EU AI Act on the same day. The overlap is significant because companies like OpenAI and Google now face similar requirements in both California and Europe.

Both regimes prioritize provenance and watermarking over relying on users to guess what looks real. In California, latent disclosure must be detectable by the provider’s own tool and consistent with widely accepted industry standards such as C2PA (Coalition for Content Provenance and Authenticity). This standard is backed by major companies like Adobe and Microsoft.

Google recently demonstrated its compliance efforts when it pulled a new AI image-editing feature from Google Earth less than 24 hours after launch. The feature allowed users to transform real-world places in Google Earth, which can create synthetic media that carries borrowed authority from the map beneath it. A fake image over a real coordinate can deceive even the most discerning viewer.

AI researcher Henk van Ess used this feature to create convincing images of refugee camps along the US-Mexico border and a nuclear plant in Iran. Google told users that these images included SynthID watermarking, which could be checked through Gemini or Lens. However, as The Verge reported, Digital Digging was able to fool Hive’s AI detector with an AI-altered Google Earth video.

This incident highlights the challenges of implementing effective disclosure mechanisms. A watermark that disappears when a file leaves a demo environment is not transparency – it’s a weak receipt. Companies must ensure that their systems can survive the messy path from creation to screenshot, upload, compression, reposting, and detection.

The next wave of compliance will hit large online platforms with more than 2 million monthly California users on January 1, 2027. These platforms, including public-facing social media, file-sharing services, mass-messaging products, and search engines, must detect provenance data that follows widely adopted specifications from an established standards-setting body.

The distinction between model makers and platform providers is crucial here. The former can mark a file with metadata, but the latter decides what users see when files move through feeds or search results. If a platform buries a provenance signal in its interface, readers are still left guessing.

Compliance has been uneven so far. OpenAI has published a California training data summary under AB 2013, and Assessed Intelligence reported that OpenAI, Anthropic, and Google posted their disclosures by the January 1, 2026 deadline. However, xAI is notable for suing California Attorney General Rob Bonta over AB 2013 in federal court.

This regulation marks a significant shift towards transparency in AI-generated synthetic media. It acknowledges that users cannot eyeball these files at scale and instead asks companies to implement robust disclosure mechanisms. The law’s authors are clear: if your product makes media that can pass as real, California is now asking whether you can prove what your product made.

A new EU regulation is about to tackle fake content online, particularly AI-generated images and audio. Starting from this Sunday, companies must label their generated content as such – text, images, video, and audio designed to look authentic. This move aims to protect consumers by making it clear when they interact with chatbots or view manipulated media.

The regulation applies to new AI systems on the EU market from August 2nd. Existing ones have an additional four months to comply, a deadline that’s part of the EU’s landmark AI Act. The act establishes a framework for trustworthy AI development and deployment – transparency is key to preserving democracy and authenticity online according to Sergey Lagodinsky.

The rules require companies to visibly mark synthetic text, images, video, and audio as AI-generated, including digital watermarks showing their artificial origins. Texts on public interest must be labelled if there’s no human editorial oversight. Companies are encouraged but not required to label pre-existing content – a grey area that may spark debate.

Failure to comply could result in fines of up to €15 million or 3% of a company’s worldwide turnover, a hefty price for ignoring transparency rules. The EU executive has created black-and-white labels anyone can use; companies can design their own if they prefer. Pre-existing content remains exempt from this requirement – but the regulation only applies to new AI systems.

The tech industry welcomes making deepfakes visible but fears broad interpretation and overwhelming users with banners and labels. Boniface de Champris, CCIA Europe’s AI policy lead, thinks confusion will arise – manipulated images in adverts are similar to deceptive political speech. This raises questions about the balance between regulation and commercial activity.

This change won’t be noticeable on social media platforms that already label most AI content. Instead, it’ll hit industries where AI is used at scale but its presence goes unnoticed: advertising, film, and publishing. De Champris believes this will put pressure on commercial activities across the board – forcing a shift in how businesses operate.

Some tech companies have implemented policies to inform users about AI-generated content before these regulations came into effect. For example, TikTok requires creators to label realistic AI images, audio, and video; they’ve even helped label over 3 billion pieces of content so far. Google’s tool SynthID lets users check if an image is AI-generated – a useful resource for identifying manipulated media.

Google claims to have put invisible digital watermarks on more than 100 billion images and nearly 60,000 years’ worth of audio. The company signed the voluntary code of practice with Meta, along with over 180 other organizations, to help companies comply with EU’s AI transparency rules – a sign of good intent from regulators.

Meta launched policies in 2024 to identify AI-generated photo-realistic images and has been working on industry-wide technical standards for identifying AI audio and video. The company announced its intention to join the EU code of practice this week, with vice-president Markus Reinisch stating they must avoid overwhelming users while adding regulatory complexity – a delicate balance.

Lagodinsky believes the industry can find a way to implement these regulations without burdening commercial activity. He respects the tech industry but notes that companies often complain about new rules only to adapt once implemented – a pattern of behavior he hopes will change this time around.

The transparency rules are part of broader enforcement of the AI Act starting from August 2nd. Henna Virkkunen, commission’s lead official on tech policy, described AI as an extraordinary technology with benefits and risks creating new problems at scale. Europe anticipated this development and established a clear framework for trustworthy AI – giving innovators freedom to innovate while protecting public interest.

Europe aims to find balance between regulation and innovation by establishing legal certainty – addressing both potential risks and opportunities presented by AI-generated content. By requiring companies to label their generated content, regulators send a signal about what’s acceptable in terms of transparency.

This regulation will have little impact on users’ personal content as it only applies to new AI systems on the EU market. Companies must comply from August 2nd; existing ones have an additional four months to adapt – providing some flexibility for businesses to adjust their operations.

The exemption for ‘evidently artistic’, satirical, or fictional works is key in maintaining creative freedom while ensuring accountability. This approach allows companies to innovate and push boundaries without ignoring transparency rules.

The upcoming ruling in the Pentagon’s case against Anthropic will mark a major milestone in what promises to be a drawn-out legal battle. The dispute centers on the government’s attempt to use Anthropic’s AI model, Claude, for sensitive military and intelligence applications without restrictions.

Athropic has insisted that two areas remain off-limits: mass surveillance of Americans and fully autonomous weapons. This stance has led to a standoff between the company and the Defense Department, which designated Anthropic a national security risk earlier this year. As a result, the company sued the government, sparking a lengthy legal battle.

US District Judge Rita Lin signaled her growing unease with the government’s case during Thursday’s hearing. ‘I don’t see additional evidence from the government justifying what it did,’ she said within the first five minutes of opening the hearing. This statement suggests that Lin is not convinced by the government’s arguments, and may even be leaning towards a favorable ruling for Anthropic.

Lin also questioned whether Anthropic could alter its model after delivery or flip a kill switch. Both parties have asked her to grant summary judgment in their favor, but she has yet to make a decision. The judge is not expected to rule from the bench and will instead issue a written decision at an unspecified date.

The case against Anthropic has been ongoing since early this year, with Lin previously calling the administration’s treatment of the company ‘troubling’. She later temporarily blocked the Defense Department’s ban, finding that Anthropic had shown a likelihood of success on the merits and would suffer irreparable harm without an injunction. This development has given the company hope that it may ultimately prevail.

The hearing marks another critical juncture in what is expected to be a lengthy legal battle between the government and Anthropic over its designation as a supply-chain risk. The outcome will have significant implications for AI companies like Anthropic, which are simultaneously helping shape the government’s AI safety rules.

A Wake County teenager has been charged with a 10th felony offense related to the alleged creation of sexually explicit images using artificial intelligence. The juvenile, who was previously accused of nine Class E felony charges, now faces an additional charge of sexual exploitation of a minor in connection with AI-generated images of underage girls.

The new charge involves a victim whose parent spoke anonymously with WRAL last week, expressing frustration that prosecutors had not initially filed a charge involving the manipulated images of her daughter. The Knightdale Police Department has since confirmed that this victim will be added to the investigation, accounting for the 10th and latest charge in their ongoing case.

The parents of several local girls have come forward, alleging that their daughters were victims connected to the juvenile investigation. These mothers claim that their daughters learned over the summer that non-explicit photos taken from various sources, including social media, had been altered using AI to depict them in a sexually explicit manner. The exact number of potential victims remains unclear at this time.

The Knightdale Police Department has stated that they will not release any additional information or provide further comment on the case due to its ongoing nature and the involvement of juvenile victims and offenders. In accordance with North Carolina law, no details regarding the identities of those involved or other specifics of the investigation can be disclosed at this time.

The Knightdale Police Department remains committed to protecting children, thoroughly investigating crimes, and holding offenders accountable under the law. This commitment is reflected in their statement: ‘The Knightdale Police Department remains committed to protecting children…’

North Carolina’s sexual exploitation laws were updated in 2024 to include language prohibiting the use of artificial intelligence as a means of producing pornographic material. Specifically, this update addresses pictures, drawings, video recordings, films, or other visual representations created using technological means such as algorithms or AI.

The teen boy at the center of the Knightdale Police investigation is charged with second-degree sexual exploitation of a minor, which is defined in state law as anyone who records, photographs, films, develops, or duplicates material containing a visual representation of a minor engaged in sexual activity. This includes distributing, transporting, exhibiting, receiving, selling, purchasing, exchanging, or soliciting such material.

Parents who have spoken to WRAL on the condition of anonymity expressed concern that content considered sexually explicit by the general public may not be viewed as such under North Carolina’s laws. Joseph Hyde, an assistant professor at the University of North Carolina’s School of Government, confirmed this interpretation: ‘Display does not constitute sexual activity unless the display is of the genitals or pubic area…’

In particular, Hyde noted that displaying female breasts alone would not meet the criteria for sexual exploitation under state statutes. This nuance has sparked debate among parents and experts regarding the scope of North Carolina’s laws in addressing AI-generated explicit images.

The case highlights concerns about the use of artificial intelligence assistants to create sexually explicit content involving minors. As technology continues to evolve, law enforcement agencies must adapt their strategies for investigating crimes related to AI-generated images.