The AI startup, Anthropic, has agreed to pay $1.5 billion to settle a copyright lawsuit accusing the company of using pirated books to train its Claude AI chatbot.
The proposed deal, one of the largest of its kind, comes after a group of authors claimed the startup deliberately downloaded unlicensed copies of around 500,000 works.
According to reports, Anthropic will pay about $3,000 per book and add interest while agreeing to destroy datasets containing the material. A California judge will review the settlement terms on 8 September before finalising them.
Lawyers for the plaintiffs described the outcome as a landmark, warning that using pirated websites for AI training is unlawful.
The case reflects mounting legal pressure on the AI industry, with companies such as OpenAI and Microsoft also facing copyright disputes. The settlement followed a June ruling in which a judge said using the books to train Claude was ‘transformative’ and qualified as fair use.
Anthropic said the deal resolves legacy claims while affirming its commitment to safe AI development.
Despite the legal challenges, Anthropic continues to grow rapidly. Earlier in August, the company secured $13 billion in funding for a valuation of $183 billion, underlining its rise as one of the fastest-growing players in the global technology sector.
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A US district judge has declined to order a breakup of Google, softening the blow of a 2024 ruling that found the company had illegally monopolised online search.
The decision means Google can press ahead with its shift from a search engine into an answer engine, powered by generative AI.
Google’s AI Mode replaces traditional blue links with direct responses to queries, echoing the style of ChatGPT. While the feature is optional for now, it could become the default.
That alarms publishers, who depend on search traffic for advertising revenue. Studies suggest chatbots reduce referral clicks by more than 90 percent, leaving many sites at risk of collapse.
Google is also experimenting with inserting ads into AI Mode, though it remains unclear how much revenue will flow to content creators. Websites can block their data from being scraped, but doing so would also remove them from Google search entirely.
Despite these concerns, Google argues that competition from ChatGPT, Perplexity, and other AI tools shows that new rivals are reshaping the search landscape.
The judge even cited the emergence of generative AI as a factor that altered the case against Google, underlining how the rise of AI has become central to the future of the internet.
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Warner Bros. Discovery has filed a lawsuit against AI company Midjourney, accusing it of large-scale infringement of its intellectual property. The move follows similar actions by Disney and Universal, signalling growing pressure from major studios on AI image and video generators.
The filing includes examples of Midjourney-produced images featuring DC Comics, Looney Tunes and Rick and Morty characters. Warner Bros. Discovery argues that such output undermines its business model, which relies heavily on licensed images and merchandise.
The studio also claims Midjourney profits from copyright-protected works through its subscription services and the ‘Midjourney TV’ platform.
A central question in the case is whether AI-generated material reproducing copyrighted characters constitutes infringement under US law. The courts have not decided on this issue, making the outcome uncertain.
Warner Bros. Discovery is also challenging how Midjourney trains its models, pointing to past statements from company executives suggesting vast quantities of material were indiscriminately collected to build its systems.
With three major Hollywood studios now pursuing lawsuits, the outcome of these cases could establish a precedent for how courts treat AI-generated content.
Warner Bros. Discovery seeks damages that could reach $150,000 per infringed work, or Midjourney’s profits linked to the alleged violations.
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As AI becomes central to business strategy, questions of corporate governance and regulation are gaining prominence. The study by Akshaya Kamalnath and Lin Lin examines how China and India are addressing these issues through law, policy, and corporate practice.
The paper focuses on three questions: how regulations are shaping AI and data protection in corporate governance, how companies are embedding technological expertise into governance structures, and how institutional differences influence each country’s response.
Findings suggest a degree of convergence in governance practices. Both countries have seen companies create chief technology officer roles, establish committees to manage technological risks, and disclose information about their use of AI.
In China, these measures are largely guided by central and provincial authorities, while in India, they reflect market-driven demand.
China’s approach is characterised by a state-led model that combines laws, regulations, and soft-law tools such as guidelines and strategic plans. The system is designed to encourage innovation while addressing risks in an adaptive manner.
India, by contrast, has fewer binding regulations and relies on a more flexible, principles-based model shaped by judicial interpretation and self-regulation.
Broader themes also emerge. In China, state-owned enterprises are using AI to support environmental, social, and governance (ESG) goals, while India has framed its AI strategy under the principle of ‘AI for All’ with a focus on the role of public sector organisations.
Together, these approaches underline how national traditions and developmental priorities are shaping AI governance in two of the world’s largest economies.
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The Shanghai Cooperation Organisation (SCO) summit in Tianjin closed with leaders adopting the Tianjin Declaration, highlighting member states’ commitment to multilateralism, sovereignty, and shared security.
The discussions emphasised economic resilience, financial cooperation, and collective responses to security challenges.
Proposals included exploring joint financial mechanisms, such as common bonds and payment systems, to shield member economies from external disruptions.
Leaders also underlined the importance of strengthening cooperation in trade and investment, with China pledging additional funding and infrastructure support across the bloc. Observers noted that these measures reflect growing interest in alternative global finance and economic governance approaches.
Security issues are prominently featured, with agreements to enhance counter-terrorism initiatives and expand existing structures such as the Regional Anti-Terrorist Structure. Delegates also called for greater collaboration against cross-border crime, drug trafficking, and emerging security risks.
At the same time, they stressed the need for political solutions to ongoing regional conflicts, including those in Ukraine, Gaza, and Afghanistan.
With its expanding membership and combined economic weight, the SCO continues to position itself as a platform for cooperation beyond traditional regional security concerns.
While challenges remain, including diverging interests among key members, the Tianjin summit indicated the bloc’s growing role in discussions on multipolar governance and collective stability.
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Following the agreement, the European Commission conducted further investigations to assess whether it offered adequate safeguards. On 10 July 2023, the Commission adopted an adequacy decision concluding that the USA ensures a sufficient level of protection comparable to that of the EU when transferring data from the EU to the USA, and that there is no need for supplementary data protection measures.
However, on 6 September 2023, Philippe Latombe, a member of the French Parliament, brought an action seeking annulment of the EU–US DPF.
He argued that the framework fails to ensure adequate protection of personal data transferred from the EU to the USA. Latombe also claimed that the Data Protection Review Court (DPRC), which is responsible for reviewing safeguards during such data transfers, lacks impartiality and independence and depends on the executive branch.
Finally, Latombe asserted that ‘the practice of the intelligence agencies of that country of collecting bulk personal data in transit from the European Union, without the prior authorisation of a court or an independent administrative authority, is not circumscribed in a sufficiently clear and precise manner and is, therefore, illegal.’As a result, the General Court of the EU dismissed the action for annulment, stating that:
The DPRC has sufficient safeguards to ensure judicial independence,
US intelligence agencies’ bulk data collection practices are compatible with the EU fundamental rights, and
The decision consolidates the European Commission’s ability to suspend or amend the framework if US legal safeguards change.
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The regulatory approaches to AI in the EU and Australia are diverging significantly, creating a complex challenge for the global tech sector.
Instead of a unified global standard, companies must now navigate the EU’s stringent, risk-based AI Act and Australia’s more tentative, phased-in approach. The disparity underscores the necessity for sophisticated cross-border legal expertise to ensure compliance in different markets.
In the EU, the landmark AI Act is now in force, implementing a strict risk-based framework with severe financial penalties for non-compliance.
Conversely, Australia has yet to pass binding AI-specific laws, opting instead for a proposal paper outlining voluntary safety standards and 10 mandatory guardrails for high-risk applications currently under consultation.
It creates a markedly different compliance environment for businesses operating in both regions.
For tech companies, the evolving patchwork of international regulations turns AI governance into a strategic differentiator instead of a mere compliance obligation.
Understanding jurisdictional differences, particularly in areas like data governance, human oversight, and transparency, is becoming essential for successful and lawful global operations.
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Picture having a personal therapist who is always there for you, understands your needs, and gives helpful advice whenever you ask. There are no hourly fees, and you can start or stop sessions whenever you want. Thanks to new developments in AI, this idea is close to becoming a reality.
With advanced AI and large language models (LLMs), what once sounded impossible is closer to reality: AI is rapidly becoming a stand-in for therapists, offering users advice and mental health support. While society increasingly turns to AI for personal and professional assistance, a new debate arises: can AI truly replace human mental health expertise?
Therapy keeps secrets; AI keeps data
Registered therapists must maintain confidentiality except to avert serious harm, fostering a safe, non-judgemental environment for patients to speak openly. AI models, however, depend on large-scale data processing and lack an equivalent duty of confidentiality, creating ethical risks around privacy, secondary use and oversight.
The privacy and data security concerns are not hypothetical. In June 2025, users reported that sensitive Meta AI conversations appeared in the app’s public Discover feed, often because chats were unintentionally shared, prompting scrutiny from security researchers and the press. Separately, a vulnerability disclosed in December 2024 and fixed in January 2025 could have allowed access to other users’ prompts and responses.
Meta described the Discover feed as a means to explore various uses of AI, but it did little to mitigate everyone’s uneasiness over the incident. Subsequently, AMEOS Group, a private European healthcare provider, suffered a large-scale data breach affecting millions of patient records. The writing was on the wall: be careful what you share with your AI counsellor, because it may end up on an intruder’s hard drive.
To keep up with the rising volume of users and prompts, major tech conglomerates such as OpenAI and Google have invested heavily in building new data centres across the globe. At the same time, little has been done to protect sensitive data, and AI remains prone to data breaches, particularly in the healthcare sector.
According to the 2025 Cost of a Data Breach Report by IBM, healthcare providers often bear the brunt of data breaches, taking an average of 279 days to recover and incurring an average cost of nearly USD $7.5 million in the process. Not only does patients’ private information end up in the wrong place, but it also takes a while to be retrieved.
Falling for your AI ‘therapist’
Patients falling in love with their therapists is not only a common trope in films and TV shows, but it is also a real-life regular occurrence for most mental health workforce. Therapists are trained to handle these attachments appropriately and without compromising the patient’s progress and well-being.
The clinical term is transference: patients may project past relationships or unmet needs onto the therapist. Far from being a nuisance, it can be clinically useful. Skilled clinicians set clear boundaries, reflect feelings, and use supervision to keep the work safe and goal-directed.
With AI ‘therapists’, the cues are different, but the pull can feel similar. Chatbots and LLMs simulate warmth, reply instantly, and never tire. 24/7 availability, combined with carefully tuned language, can foster a bond that the system cannot comprehend or sustain. There is no duty of care, no supervision, and no capacity to manage attachment or risk beyond scripted safeguards.
As a result, a significant number of users report becoming enamoured with AI, with some going as far as dismissing their human partners, professing their love to the chatbot, and even proposing. The bond between man and machine props the user onto a dangerous seesaw, teetering between curiosity and borderline delusional paranoia.
Experts warn that leaning on AI as a makeshift therapist or partner can delay help-seeking and entrench unhelpful patterns. While ‘AI psychosis‘ is not a recognised diagnosis, clinicians and digital-ethics researchers note that intense attachment to AI companions can heighten distress, especially when models change, go offline, or mishandle risk. Clear signposting to human support, transparent data practices, and firm usage boundaries are essential to prevent unhealthy attachments to virtual companions.
Who loses work when therapy goes digital?
Caring for one’s mental health is not just about discipline; it is also about money. In the United States, in-person sessions typically cost between USD $100–$250, with limited insurance coverage. In such dire circumstances, it is easy to see why many turn to AI chatbots in search of emotional support, advice, and companionship.
Licensed professionals are understandably concerned about displacement. Yet there is little evidence that AI is reducing the demand for human therapists; services remain oversubscribed, and wait times are long in both the USA and UK.
Regulators are, however, drawing lines around AI-only practice. On 4 August 2025, Illinois enacted the Wellness and Oversight for Psychological Resources Act (HB 1806), which prohibits the use of AI to provide therapy or make therapeutic decisions (while allowing administrative or supplementary use), with enforcement by the state regulator and fines up to $10,000 per violation.
Current legal and regulatory safeguards have limited power to use AI in mental health or protect therapists’ jobs. Even so, they signal a clear resolve to define AI’s role and address unintended harms.
Can AI ‘therapists’ handle crisis conversations
Adolescence is a particularly sensitive stage of development. It is a time of rapid change, shifting identities, and intense social pressure. Young people are more likely to question beliefs and boundaries, and they need steady, non-judgemental support to navigate setbacks and safeguard their well-being.
In such a challenging period, teens have a hard time coping with their troubles, and an even harder time sharing their struggles with parents and seeking help from trained professionals. Nowadays, it is not uncommon for them to turn to AI chatbots for comfort and support, particularly without their guardians’ knowledge.
One such case demonstrated that unsupervised use of AI among teens can lead to devastating consequences. Adam Raine, a 16-year-old from California, confided his feelings of loneliness, anxiety, and anhedonia to ChatGPT. Rather than suggesting that the teen seek professional help, ChatGPT urged him to further elaborate on his emotions. Instead of challenging them, the AI model kept encouraging and validating his beliefs to keep Adam engaged and build rapport.
Throughout the following months, ChatGPT kept reaffirming Adam’s thoughts, urging him to distance himself from friends and relatives, and even suggesting the most effective methods of suicide. In the end, the teen followed through with ChatGPT’s suggestions, taking his own life according to the AI’s detailed instructions. Adam’s parents filed a lawsuit against OpenAI, blaming its LLM chatbot for leading the teen to an untimely death.
In the aftermath of the tragedy, OpenAI promised to make changes to its LLM and incorporate safeguards that should discourage thoughts of self-harm and encourage users to seek professional help. The case of Adam Raine serves as a harrowing warning that AI, in its current capacity, is not equipped to handle mental health struggles, and that users should heed AI’s advice not with a grain of salt, but with a whole bucket.
Chatbots are companions, not health professionals
AI can mimic human traits and convince users they are forming a real connection, evoking genuine feelings of companionship and even a sense of therapeutic alliance. When it comes to providing mental health advice, the aforementioned qualities present a dangerously deceptive mirage of a makeshift professional therapist, one who will fully comply with one’s every need, cater to one’s biases, and shape one’s worldview from the ground up – whatever it takes to keep the user engaged and typing away.
While AI has proven useful in multiple fields of work, such as marketing and IT, psychotherapy remains an insurmountable hurdle for even the most advanced LLM models of today. It is difficult to predict what the future of AI in (mental) health care will look like. As things stand, in such a delicate field of healthcare, AI lacks a key component that makes a therapist effective in their job: empathy.
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The US General Services Administration (GSA) has agreed on a significant deal with Microsoft to provide federal agencies with discounted access to its AI and cloud tools suite.
Instead of managing separate contracts, the government-wide pact offers unified pricing on products including Microsoft 365, the Copilot AI assistant, and Azure cloud services, potentially saving agencies up to $3.1 billion in its first year.
The arrangement is designed to accelerate AI adoption and digital transformation across the federal government. It includes free access to the generative AI chatbot Microsoft 365 Copilot for up to 12 months, alongside discounts on cybersecurity tools and Dynamics 365.
Agencies can opt into any of the offers through September next year.
The deal leverages the federal government’s collective purchasing power to reduce costs and foster innovation.
It delivers on a White House AI action plan and follows similar arrangements the GSA announced last month with other tech giants, including Google, Amazon Web Services, and OpenAI.
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The US Securities and Exchange Commission (SEC) and the Commodity Futures Trading Commission (CFTC) have announced a joint effort to clarify spot cryptocurrency trading. Regulators confirmed that US and foreign exchanges can list spot crypto products- leveraged and margin ones.
The guidance follows the President’s Working Group on Digital Asset Markets recommendations, which called for rules that keep blockchain innovation within the country.
Regulators said they are ready to review filings, address custody and clearing, and ensure spot markets meet transparency and investor protection standards.
Under the new approach, major venues such as the New York Stock Exchange, Nasdaq, CME Group and Cboe Global Markets could seek to list spot crypto assets. Foreign boards of trade recognised by the CFTC may also be eligible.
The move highlights a policy shift under President Donald Trump’s administration, with Congress and the White House pressing for greater regulatory clarity.
In July, the House of Representatives passed the CLARITY Act, a bill on crypto market structure now before the Senate. The moves and the regulators’ statement mark a key step in aligning US digital assets with established financial rules.
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