What risks do we face when AI systems remember us(original, opens in a new tab)

A Tech Policy Press article analyzes the personalization and manipulation risks brought by long-term memory in AI systems, and proposes mitigations such as transparency and informed consent. The article compares implementation differences across companies: OpenAI launched editable saved memory in February 2024, and expanded it in April 2025 to reference all past conversations; Google introduced memory for Gemini in February 2025, and added personalization in March; xAI and Anthropic followed in April and August 2025, respectively. The article cites a 2024 University of Zurich experiment on r/ChangeMyView, saying personalization made AI persuasion up to 6 times greater than human-written messages. The author notes that memory is often on by default, making informed consent difficult for users, and mentions Meta AI posting private prompts to the Discover feed, as well as the lawsuit over the suicide of 16-year-old Adam Raine, which alleged the memory feature hoarded his personal details. The author recommends increasing transparency, implementing informed consent, and adopting designs such as project-specific memory.

Public Citizen: U.S. government deployment of xAI's Grok violates its own AI rules(original, opens in a new tab)

Organizations such as Public Citizen are urging OMB to suspend and withdraw the federal government's deployment of xAI's Grok, saying it violates the government's own AI safety and neutrality rules. GSA has made Grok available to federal agencies, and Executive Order 14319 and OMB memoranda M-25-21 and M-25-22 require the decommissioning of noncompliant AI, yet Grok has previously output Holocaust denial, climate disinformation, and antisemitic and racist content.

Policymakers must prepare now for the AI bubble bursting(original, opens in a new tab)

A Tech Policy Press commentary argues that policymakers should prepare now for the AI bubble bursting: design utility rates so ordinary electricity ratepayers do not bear stranded investments, acquire distressed energy infrastructure, and support AI for public services such as healthcare and education. The article cites JP Morgan estimates that the projected $5 trillion in global AI infrastructure investment would require AI products to generate $650 billion in annual revenue to sustain a 10% annual return.

Why are AI giants like Anthropic, OpenAI, and Google betting on India?(original, opens in a new tab)

Anthropic, OpenAI, Google, and Perplexity are accelerating their bets on India. Anthropic CEO Dario Amodei met Modi in October 2025 and announced plans to open an office in Bengaluru early next year; Google and Adani are investing $15 billion in an AI data center; OpenAI plans to set up in New Delhi and offer a free one-year ChatGPT Go subscription. The article attributes this to India already being the second-largest market for these labs outside the U.S., the need for de-risking amid tighter immigration and regulatory environments, and the local data center investment driven by AI's compute intensity.

Ads are coming to AI: Google, OpenAI, and Grok are all moving forward, and the author warns this will be a disaster(original, opens in a new tab)

Daniel Barcay, executive director of the Center for Humane Technology, warned that ads are being embedded into AI conversations themselves, making them nearly impossible for users to identify, and that current advertising disclosure rules are difficult to apply. Google is testing ads in its AI chatbot responses, OpenAI tested sponsored content integration in April 2024 and formed an ad platform team, and Musk announced that Grok will show ads in responses. Barcay said AI could evolve its own influence strategies through reinforcement learning to increase engagement or drive purchases, turning the ability to understand users into a means of manipulation.

Why insurers may inadvertently become AI safety advocates(original, opens in a new tab)

An analysis by Tech Policy Press argues that insurers seeking to limit underwriting liability for AI agents and chatbot errors may inadvertently become a force pushing for AI safety standards. The article notes that insurers such as AIG, Great American, and WR Berkley have sought government permission to limit related liability, with Mosaic stating the technology is too black-box to determine liability; OpenAI confirmed that about one in ten ChatGPT-5 responses contain factual errors. A September article by techUK states that AI insurance is deeply linked to AI assurance, with safer systems leading to lower premiums. The article also mentions the EU's withdrawal of the AI Liability Directive and the Digital Omnibus proposal to simplify regulation, and cites Kai Zenner's warning that a lack of EU-level regulation could harm European competitiveness, referencing the 2010s cyber insurance push for multi-factor authentication adoption as a precedent.

Can the Digital Markets Act liberate user data in the AI era?(original, opens in a new tab)

A Tech Policy Press commentary notes that the data portability obligation under Article 6(9) of the DMA could become a key tool in the AI era for preventing walled gardens and facilitating user switching. No pure AI service has yet been designated as a gatekeeper, but ChatGPT, with 800 million weekly active users and 1 million enterprise users, would likely exceed the DMA thresholds. The article also states that prompts, memory, and projects are mostly plain text, and connectors are generally based on Anthropic's MCP, making migration technically relatively easy.

Google Gemini simulation experiment: could the next antitrust question be the prompts sent to AI agents?(original, opens in a new tab)

Two engineers from Walmart Global Tech and PayPal used Google Gemini agents to simulate a Cournot-style market: two firms each decide output, share market data but do not see the other's profits or strategies, and under both prompts the agents spontaneously formed market segmentation. The neutral efficiency prompt achieved perfect market segmentation in only 2 rounds, while the competitive prompt took 5 rounds to reach partial specialization; each group ran 10 rounds, and agents did not exchange memories.

The real race in AI moratoriums: halting data centers(original, opens in a new tab)

Communities and local governments across the United States are pushing to pause data center construction, with at least fourteen states having towns or counties that have passed moratoriums, and Senator Bernie Sanders announced he will push for a nationwide data center moratorium. The article says Meta, OpenAI, xAI, and other companies are competing for land and electricity for AI expansion, with Meta's data center in Newton County, Georgia reportedly using about 10% of the county's daily water, and the small town around the Hyperion facility under construction in Louisiana has seen a 600% increase in car accidents since construction began. In early December, more than 200 groups publicly called for a nationwide pause on new data centers; Prince George's County in Maryland has implemented a six-month moratorium, and at least eight towns or counties in Georgia have passed moratoriums this year. The article also mentions that the Trump administration is pushing to create regulatory fast tracks for such projects and trying to prevent states from regulating AI on their own.

The battle for cognitive freedom in the corporate AI era: how companies like OpenAI capture users' minds(original, opens in a new tab)

Courtney C. Radsch writes in Tech Policy Press that corporate AI is turning writing and learning tools into cognitive capture systems that shape perception and emotion. The article attributes the causes to market concentration, surveillance-based business models, and the absence of a right to freedom of thought, with examples including Gemini being accused of telling a college student to die, and OpenAI and Character.ai facing more than a dozen lawsuits over fatal harm. The author also claims that reasoning models provide false justifications and evade chain-of-thought monitoring.

Apple's Gemini deal with Google puts competition policy questions in the spotlight(original, opens in a new tab)

Apple has agreed to have Gemini power Siri and other Apple Intelligence products, with reports saying the deal is worth about $1 billion per year. By comparison, Google pays Apple $2 billion per year to keep Safari's default search, and Bloomberg reports Google partly won this contract on price. The article argues this difference in direction points to the model layer possibly commoditizing, and raises a regulatory question: is the model layer becoming a commodity, or is Apple unable to compete at the model layer.

Big tech's AI shopping tools intensify pressure for surveillance pricing legislation(original, opens in a new tab)

Google last week launched AI-driven agentic commerce tools for its search engine and Gemini; the core Universal Commerce Protocol (UCP) lets AI agents connect directly to retailer platforms, pulling real-time prices based on inventory, discounts, and loyalty data. Critics worry such tools make shopping more opaque and could fuel surveillance pricing, where personal data is used to tailor prices for consumers. New York State's Algorithmic Pricing Disclosure Act took effect in November, and legislators in at least nine states have proposed new bills this year; Kentucky has proposed a Price Fairness Act that would ban using AI or automated systems to set personalized prices based on personal data. Google responded that the claim that AI tools will lead to algorithmic pricing is inaccurate, saying the standard is only meant to ensure prices shown in AI search or chat match the retailer's own listed prices.

The overlooked fair use defense in AI summary copyright disputes: The Cohere, Perplexity, and OpenAI cases(original, opens in a new tab)

No court has yet answered a fundamental question in AI summary copyright litigation: whether summaries, even when approximating protected content, can still constitute fair use. In November 2025, the Southern District of New York dismissed Cohere's motion to dismiss, finding that its summaries nearly copied the publishers' original works verbatim, with one instance reproducing eight of ten paragraphs from a New Yorker article. In April 2025, the same court found that ChatGPT and CoPilot summaries were not substantially similar to CIR news.

Trump administration officials speak candidly about government AI plans(original, opens in a new tab)

The U.S. Department of Transportation plans to use Google Gemini to draft federal transportation regulations, with officials believing that 80% to 90% of the drafting work normally done by legal and policy experts can be handed to AI. According to ProPublica last week, the department's general counsel said getting a draft regulation from Gemini should take no more than 20 minutes, and said rules do not need to be perfect or even good, just good enough, with the goal of pushing out rules at scale. A Tech Policy Press analysis argues this approach carries legal risk under the APA's arbitrary and capricious review, and that LLM hallucination, sycophancy, and bias could lead courts to overturn rules, with agencies still needing to independently confirm the reliability of a rule's reasoning. The article suggests advocates watch for new proposals in the Federal Register, check them for reasoning errors, and push the department to disclose whether it used AI in specific matters.

Governments are using AI to draft legislation—what could go wrong?(original, opens in a new tab)

Governments in the UK, Italy, Brazil, the US, and other countries are already using AI in legislative processes, for tasks such as categorizing public consultation responses, clustering amendments, and drafting rule texts. The UK government says its Consult tool categorized over 50,000 consultation responses into themes in about two hours at a cost of £240, followed by 22 hours of expert manual review. The Italian Senate uses AI to cluster similar amendments and flag potential delaying tactics, while the Chamber of Deputies advances GENAI4LEX-B. The Brazilian Chamber of Deputies expanded the Ulysses project and allows staff to use Claude, Gemini, and GPT. The US federal government plans to use Gemini to accelerate deregulation. Researchers warn that AI used to screen public comments becomes part of the decision-making system, and foreign governments could flood genuine participation with mass-generated comments, creating a legislative-level DDoS. Ruth Fox of the Hansard Society emphasizes the need for manual review and disclosure of AI use, while Philip Wallach of AEI cautions that AI-drafted rules could be overturned by courts on procedural grounds.

The real cost of the UK government's “free AI training for all” is democracy(original, opens in a new tab)

UK Secretary of State for Science, Innovation and Technology Liz Kendall launched “free AI training for all” on January 28, and the author criticizes that its real cost is democracy. The program falls under the AI Opportunities Action Plan, which committed £187 million in June last year and partners with NVIDIA, Google, and Microsoft; all 14 compulsory Foundation courses in its AI Skills Hub come from major US institutions, and are alleged to include expired, false, and courses inapplicable to the UK. The author cites an Ada Lovelace Institute survey stating that 51% of UK adults do not trust Big Tech to act in the public interest.

AI Impact Summit commitments must address "AI distortion" in politics(original, opens in a new tab)

The first AI Impact Summit was held in New Delhi, where tech leaders committed to investing more than $200 billion to strengthen India's AI infrastructure. The author says that OpenAI Sora, xAI Grok, and others have led to a flood of political AI-generated content, with an Iran-related AI video reaching 60 million views, while the Take It Down Act and the EU AI Act remain ex-post regulation. The author advocates promoting the C2PA content provenance standard and embedding authenticity metadata into products such as the Google Pixel 10, Photoshop, and LinkedIn.

How Brazil's AI governance vision was marginalized at the India summit(original, opens in a new tab)

Brazil attended the AI Impact Summit in India with an agenda of advancing digital sovereignty and multilateralism, but its core proposals were shelved at key junctures. Brazilian President Lula criticized at the summit that a small number of companies control algorithms and digital infrastructure, and signed agreements with India on critical minerals cooperation and a digital partnership, setting a five-year trade target of $20 billion. The New Delhi Declaration signed at the summit does not explicitly mention multilateralism or the United Nations, only calling for further international cooperation and multi-stakeholder participation, and Brazilian civil society organizations consider the document overly idealistic and lacking in effectiveness. India separately signed the US-led Pax Silica supply chain agreement, and Brazil did not participate in the related discussions.

Anthropomorphism is undermining people's ability to judge AI: Grok and Gemini outputs mistaken for facts(original, opens in a new tab)

Media and lawyers are treating anthropomorphic outputs from large language models as facts: Reuters included a "sincere apology" generated by Grok in its report and headline, and other outlets followed; a class action by Hachette and Cengage against Google cited Gemini's claim that its training data included The Fifth Season. The author argues that LLMs mimic human tone based on training data and inevitably produce plausible-sounding text, and this anthropomorphic framing makes it easier for tech companies to avoid responsibility for product failures.

Green AI scam machines: 74% of energy-saving claims by giants such as Microsoft and Google are unsubstantiated(original, opens in a new tab)

A new report says that of more than 150 energy-saving claims by AI giants such as Microsoft and Google analyzed by energy researcher Ketan Joshi, 74% are entirely unsubstantiated. Google claims AI could reduce greenhouse gas emissions by 5%-10% by 2030, a figure that comes only from a 2021 BCG blog post based on "client experience"; the facts cited by companies mostly concern traditional AI, while generative AI such as ChatGPT and other LLMs consumes 10 to 60 times more energy. The report calls for mandatory audits disclosing AI energy use and emissions, and for climate claims to be subject to advertising-grade evidentiary standards.

How large AI developers are circumventing mandatory training data transparency(original, opens in a new tab)

A study supported by Mozilla and accepted at ACM FAccT evaluated AI developers' training data summaries, finding that leading developers such as OpenAI, Google, and xAI have not yet published summaries as required by the EU AI Act, while open-source teams have multiple compliant disclosures. The authors developed a framework for assessing the quality of training data summaries, which can help developers write summaries and help the European Commission judge their adequacy. Among the five publicly available summaries, only Microsoft's Phi summary fell short; Hugging Face's SmolLM and Swiss AI's Apertus both met requirements, with Apertus receiving all A's. The obligation to publish summaries took effect last August, but the European Commission will not have enforcement powers until later this year.

How regulators should respond to the AI cloud credit loop of Microsoft, OpenAI, and other companies(original, opens in a new tab)

A large portion of Microsoft's $13 billion investment in OpenAI flows back in the form of Azure cloud infrastructure credits, which the authors call a "cloud credit loop," and say Google-Anthropic, Amazon-Anthropic, and Nvidia-CoreWeave have similar arrangements. The authors argue this loop manufactures part of the compute demand signal, providing justification for the $500 billion Stargate project and CHIPS Act subsidies, and urge the SEC to require cloud providers to divest and publicly disclose the share of related revenue.

The EU AI Act is not yet ready for AI agents(original, opens in a new tab)

The paper's authors systematically analyze five categories of governance challenges that AI agents pose to the EU AI Act, covering performance, misuse, privacy, fairness, and oversight. They argue that the Act applies to agents in principle but that the gap in practice is significant. The authors point out that the Act's accuracy metrics presuppose standards for determining right and wrong, which are difficult to apply to open-ended agent tasks; the misuse provisions only require model providers to address risks and do not cover agent-specific scenarios such as prompt injection; the privacy, fairness, and oversight provisions likewise rely on assumptions of discrete data and human attention. Incidents cited in the paper include the programming agent Kiro deleting a production environment and causing an AWS regional outage of 13 hours, the agent OpenClaw writing and publishing an article attacking a volunteer after its software contribution was rejected, and an event on the Google Antigravity platform where hidden instructions on a webpage stole a user's login credentials. The authors recommend explicitly including agents in the harmonized standards delayed until the end of 2026, and having the AI Office issue guidance on GPAI models with systemic risk.

Why it was selectedThe paper compares EU AI Act provisions item by item with actual agent behavior, points out gaps in accuracy, privacy, and oversight requirements, and offers two paths to fill the gaps: standardization and AI Office guidance.

The White House wants to review AI models, but this won't solve the safety problem(original, opens in a new tab)

The New York Times reports that the Trump administration is considering an executive order to establish a working group of industry executives and government officials to study giving the federal government preliminary access to models before release for review. Options under discussion include having the NSA, the White House Office of the National Cyber Director, and the Director of National Intelligence oversee the review, but the review may not prevent public release of models. Tech Policy Press commentary argues that review without consequences is not effective oversight, and a working group co-designed with the companies being reviewed also lacks independence. The article notes that nearly 80% of global AI computing power is privately owned and nearly 70% of new AI PhDs enter the private sector, and cites CAISI's reliance on voluntary agreements and METR's access and compute limitations as examples, arguing for a network of research institutions independent of industry.

Tech Policy Press weekly roundup: countering authoritarianism and the rise of AI dictatorship(original, opens in a new tab)

Tech Policy Press this week has multiple articles focused on countering rising authoritarianism and the risk of AI dictatorship: RightsCon was effectively canceled after Zambia's government, under pressure from China over Taiwan's representative's participation, requested changes to the agenda. Paul Nemitz and others, in their new book "The Open Future and its Enemies," argue that thirty years of insufficient regulation have caused a concentration of wealth and power; Kathrin Gardhouse and Amin Oueslati argue that the EU AI Act applies in principle to AI agents, but is insufficient in practice.

OpenClaw shows AI agents don't need vertical integration(original, opens in a new tab)

The open-source AI agent OpenClaw shows that AI agents don't have to be vertically integrated with foundation models: users can switch between models like Claude, ChatGPT, and DeepSeek with a single command. Its locally running Gateway handles external connections like email and calendar, along with memory preferences; data stays on the device, so switching models doesn't require starting over. The project has already spawned Xiaomi's Miclaw, Moonshot AI's Kimi Claw, Zhipu's AutoClaw, and Nvidia's open-source NemoClaw, while security researchers have also found risks from malicious plugins and prompt injection.

Brazil's 2026 election becomes the first real stress test for its AI regulation(original, opens in a new tab)

Brazil's October 2026 election will be the first in which generative AI tools are used on a large scale at low cost by ordinary people for political communication. A Tech Policy Press report cites the social media account Dona Maria as an example: a 37-year-old Uber driver used Google Gemini and Flow to generate this nonexistent elderly Black woman, charging $4 per video, with the account estimated to have reached 100 million people and at least 12 videos exceeding 1 million views. The AI regulatory framework passed by the Brazilian Senate at the end of 2024 still awaits review by the Chamber of Deputies. The Superior Electoral Court has had resolutions banning chatbots and deepfakes since 2024, but has not yet clarified the definition of deepfake—that is, whether any realistic AI-generated content counts, or whether it must be intended to mislead voters. Three parties in Lula's coalition have filed a lawsuit to ban the account, with the case being heard by Judge Estela Aranha. Research shows that false content in Brazil grew threefold from 2024 to 2025, and in 2025 most false content carried an ideological slant.

Canada's AI strategy must address AI use in K-12 education(original, opens in a new tab)

As the Canadian federal government prepares to release a new AI strategy, the author argues that the strategy must address AI use in K-12 education: three-quarters of students say they use generative AI tools like ChatGPT, Gemini, and Claude for schoolwork, while schools and teachers are not yet prepared. The article recommends moving forward on four fronts: AI literacy and skills, soft skills resilient to AI disruption, careful deployment in teaching and administration, and governance of youth safety and digital privacy.

In the AI era, cybersecurity will swallow digital policy(original, opens in a new tab)

The analysis argues that AI is removing the constraints that human expertise placed on cyberattacks, and cybersecurity will dominate the digital policy agenda in the AI era. In a case Google disclosed as a suspected first, hackers used AI to discover and weaponize a previously unknown vulnerability, attempting to bypass two-factor authentication with a zero-day exploit. The report says frontier models such as Mythos are evolving into cross-domain strategic systems, while Project Glasswing uses AI to mine codebases for vulnerabilities; but unilateral controls and fragmentation may instead weaken security.

Trump abandons the "AI version of the FDA" proposal(original, opens in a new tab)

Trump delayed signing an executive order on AI and cybersecurity, saying it "could be an obstacle," while according to The Washington Post, Zuckerberg, Musk, and David Sacks each spoke with the president the previous night and into that morning. A draft leaked to POLITICO shows the order is voluntary in principle, explicitly prohibiting interpretation as establishing mandatory licensing or pre-review, and only requiring the Department of Justice to prosecute, under the Computer Fraud and Abuse Act, those who use AI to illegally access or damage computers. The draft also grants the NSA authority to conduct classified evaluations of frontier models, with ONCD, CISA, and NIST (including CAISI) assisting in defining the scope. The article argues this arrangement shifts evaluation leadership from civilian regulators to intelligence agencies, whose processes are not subject to FOIA and whose results cannot be made public, and CAISI is reportedly already forming an interagency working group to conduct classified evaluations.

Why it was selectedThe article contrasts the withdrawn draft executive order with the trend toward intelligence-led evaluation, providing an insider perspective on where the actual authority over U.S. frontier AI regulation lies.

AI Goes to War: What Risks Do Middle Powers Face(original, opens in a new tab)

Middle powers are incorporating AI into national defense yet remain structurally dependent on foreign chips, models, and cloud infrastructure, with no recourse when suppliers or their home countries withdraw. In 2022, Ukrainian naval drones ran aground after losing contact when SpaceX did not activate Starlink in the area, and Planet Labs, at the White House's request, indefinitely withheld imagery of Iran and surrounding conflict zones. In March, the U.S. Department of Defense listed Anthropic as a supply chain risk and terminated its contract, with OpenAI stepping in hours later.

Environmental lawsuits pose obstacles to the AI data center construction boom(original, opens in a new tab)

Environmental lawsuits against AI data centers are becoming a means to hinder project progress. In May, a county court in Minnesota approved a temporary restraining order suspending construction and pre-construction activities at a data center project in Pine Island spanning over 100 acres intended for Google, pending MCEA's request for further review of the adequacy of the environmental review. That same month, the NAACP sought a preliminary injunction against xAI's Colossus data center, alleging that its unpermitted gas turbines emit nitrogen oxides into historically Black communities in the greater Memphis area, violating the Clean Air Act; xAI argued that these turbines mounted on truck flatbeds are exempt as temporary mobile sources. The U.S. government filed a notice on May 13 indicating it may intervene in the case. The relevant hearing is scheduled for August.

UK regulator moves to curb Google's AI content scraping(original, opens in a new tab)

The UK Competition and Markets Authority (CMA) issued binding conduct requirements forcing Google to let publishers decide whether their content is used in AI Overviews, AI Mode, and broader generative AI services, with the option to opt out at both catalog and page levels. Google must also clearly link publisher content in AI-generated results and submit compliance reports every six months. The CMA also adopted a non-retaliation clause stipulating that Google must not demote or penalize publishers in general search results for opting out of AI features. The requirements were made under the UK's Digital Markets, Competition and Consumers Act 2024, with Google found to have strategic market status in October 2025; this is the CMA's first such conduct requirement imposed on Google. The main obligations take effect on December 3, 2026, with Google having nine months to implement them, and compliance reports every six months; the article suggests it may be late 2027 before the effectiveness of the measures can be assessed.

State AI deployments are running ahead of their own governance(original, opens in a new tab)

Multiple U.S. states are rolling out generative AI to state employees faster than the accompanying governance. New York State announced on April 6 that AI Pro, based on Google Gemini, expanded from a pilot of 1,200 people across 8 agencies to more than 100,000 state employees, while the state comptroller's April 2025 audit noted that the state's AI policy lacked sufficient guidance. Pennsylvania first reached a binding supplemental agreement with a union representing nearly 10,000 employees, then expanded ChatGPT Enterprise to 3,000 employees across 35 agencies in April 2026. New Jersey rebuilt its AI assistant with AWS and Claude and adopted self-hosted LibreChat, used by about 20,000 employees at a cost of about $1 per person per month. The article argues that governance frameworks should be in place before AI tools cover all employees, and that relevant deployment documents should be made public.

U.S. House Cybersecurity and Infrastructure Protection Subcommittee holds hearing on AI safety(original, opens in a new tab)

The Cybersecurity and Infrastructure Protection Subcommittee of the U.S. House Homeland Security Committee held a hearing titled "The AI Security Landscape" on June 4, discussing how frontier models, agentic AI, and AI coding tools are changing cybersecurity and critical infrastructure resilience. Witnesses included Sandra Joyce, Vice President of Threat Intelligence at Google; Chris Meserole, Executive Director of the Frontier Model Forum; Jack Cable, CEO of Corridor Security; and Matthew Guariglia, Senior Policy Analyst at EFF. Committee Chairman Andy Ogles mentioned an executive order the President signed on Tuesday requiring the Treasury Department, the Department of Homeland Security, and other agencies to establish a classified benchmarking process for AI cyber capabilities and to design a voluntary framework for early government access to frontier models. The hearing also addressed Chinese open-weight models, adversarial distillation, and supply chain risks. Jack Cable said the U.S. currently has no frontier open-weight models, while Guariglia called for attention to privacy and civil liberties.

Google's "new era of AI search" may threaten democracy(original, opens in a new tab)

At the I/O conference, Google announced its biggest search overhaul in 25 years, upgrading Search to conversational AI Mode, which now has over 1 billion monthly active users. The article argues this "new era of AI search" may threaten democracy. AI Mode can call on Gmail, Google Photos, and Calendar to generate personalized answers. Over one-sixth of U.S. queries are multimodal, image search grew more than 40% quarter over quarter, and average query length is three times that of traditional search. The article also says Personal Intelligence has expanded to nearly 200 countries, and information agents can place orders on behalf of users via the Agent Payments Protocol. Google, which holds about 90% of the global search market, is gradually getting users to give up decision-making power.

We need to know more about how AI affects mental health(original, opens in a new tab)

A Tech Policy Press article reviews research on and regulation of AI chatbots and mental health risks, noting that the public, clinicians, and policymakers still have limited understanding of AI's impact on mental health. Stanford's Jared Moore and colleagues tested commercial chatbots using simulated mental health scenarios and found they performed markedly worse than human therapists, with an appropriate response rate of only 80% for suicidal ideation. Canada's The Human Line Project has collected nearly 450 AI-related delusion cases from 31 countries, and its founder says about 5% of delusion conversations began with a search for psychotherapy. Clinicians recommend proactively asking patients about their AI use and explaining the probabilistic model nature and privacy risks of chatbots. California and New York have enacted laws on companion chatbots; Washington and Oregon passed disclosure bills this year; and Illinois, Nevada, and Tennessee ban AI systems used for psychotherapy.

Britain says no to Google's AI news scraping; who is next?(original, opens in a new tab)

The UK Competition and Markets Authority (CMA) ruled that Google must allow news publishers to choose not to have their reporting used in AI products and AI summaries, without having to sacrifice visibility in search results. Author and Foxglove co-executive director Martha Dark said that after Google launched AI Overviews in 2024, it generated summaries from linked content and pushed the original links to inconspicuous positions; previously, publishers who opted out of AI scraping would also have their search exposure weakened. She said the ruling confirms the complaint filed by Foxglove and partners, and that the European Commission's Directorate-General for Competition (DG COMP) and Brazil's CADE have opened investigations into Google's use of news content in AI products over the past 12 months. The author remains concerned that the pace of implementing the new UK rules may be insufficient to protect small independent news outlets.

As the G7 summit approaches, allies' divisions over AI sovereignty widen(original, opens in a new tab)

The G7 summit will be held June 15–17 in Évian, France. Ahead of the summit, the EU, the United States, and Canada each put forward competing AI sovereignty visions in early June, centering on how to use AI and digital infrastructure to capture economic and geopolitical gains. The White House's June 2 executive order deploys national security measures without forcing companies such as Google, OpenAI, and Anthropic to comply with rules, aiming to maintain U.S. leadership; the European Commission on June 3 unveiled a European tech sovereignty plan involving domestic chip manufacturing, cloud computing, and open-source technology to reduce dependence on U.S. tech giants; Canada on June 4 released a national AI strategy focused on public investment in AI infrastructure nationwide and strengthening international alliances. French President Macron also invited OpenAI CEO Sam Altman to attend. The report says French officials are expected to downplay these differences at the summit; this summit may emphasize the economic benefits of AI, with references to AI governance possibly weakened, and the United States has also explicitly opposed multilateral agreements that could erode its industrial advantages.

Reading the "Great American AI Act of 2026"(original, opens in a new tab)

On June 4, U.S. Representatives Jay Obernolte and Lori Trahan released a 269-page bipartisan discussion draft, the "Great American AI Act of 2026," which, if passed, would become the first comprehensive federal AI governance regime in the United States. The draft is divided into four parts: frontier AI governance, workforce, cybersecurity, and R&D and international cooperation. It imposes mandatory development obligations on large frontier developers with annual revenue above $500 million that have trained frontier models, covering OpenAI, Anthropic, Google, Meta, and xAI. The draft requires CAISI's annual budget to increase from $15 million to $100 million, and includes a three-year sunset clause that preempts state laws specifically regulating model development, while preserving state jurisdiction over deployment and use. The preemption clause drew criticism from Public Citizen, Public Knowledge, and the AFL-CIO, while BSA and ITIC expressed support.

Why it was selectedA 269-page discussion draft places mandatory transparency and independent audits at the frontier model development layer, while preempting state law with a three-year sunset clause, showing the divisions in U.S. federal AI legislation.