Elon Musk listens as President Donald Trump speaks during an event at the US Institute of Peace, Oct. 8, 2026, in Washington. (AP Photo/Julia Demaree Nikhinson, File)

Pull the Plug on Technofascism Before It Reboots

Exterior view of the US headquarters of TikTok in Culver City, California, in 2022. Shutterstock

Exterior view of the US headquarters of TikTok in Culver City, California, in 2022. 

Social Media Addiction Cases Are Settling Before Trial. What Does It Mean?

Online Radicalization Concept with Digital Propaganda, Social Media Manipulation, Extremist Influence, Algorithmic Amplification, Hate Speech, Misinformation, Polarization and Online Safety Risks

Hate Speech Still Pays on YouTube. Regulators Should Follow the Money

Anti-data center demonstrators protest at the Pennsylvania Capitol, Tuesday, Oct. 6, 2026, in Harrisburg, Pa. (AP Photo/Marc Levy)

Voters Handed Congress a Mandate to Confront Corporate Power and Technofascism

Democratic Senate candidate Texas state Rep. James Talarico concludes a victory speech at an election night event in Austin, Texas, Tuesday, Nov. 3, 2026. (AP Photo/Eric Gay)

Democrats Target AI, Data Centers, Elon Musk and Big Tech in Midterm Victory Speeches

A protester hidden behind a poster with slogans against Meta holds a mask with the face of Mark Zuckerberg with devil horns over it. 

A protest outside Meta headquarters in Sao Paulo, Brazil, on October 19, 2026.  (Allison Sales/NurPhoto)

In Brazil, Lula's Army Fought Meta on Meta's Own Turf

A digital collage combining a historical painting of a miner with a large grid of small online images. At the center, a muscular miner works underground with a heavy drill inside a dark tunnel. To the left and along the bottom, hundreds of tiny square images form a dense mosaic, suggesting scraped internet content. A bright beam of light connects the image grid to the miner’s drill. On the right, a block of colorful digital noise contrasts with the detailed painting, reinforcing the link between physical mining and data extraction.

Primitive Accumulation by Daniela Zampieri / 

What the New AI Training Opt-Out Really Means

What Teenagers' AI Use Reveals About the EU Kids Act

A sunrise in the horizon over icy waters. 

The Ilulissat Ice fjord in Greenland, where rising temperatures are contributing to rapid glacier melt, July3, 2024. (Photo by Ulrik Pedersen/NurPhoto)

Good News and Bad News About AGI and Climate Change

A voter casts their ballot on Election Day, Nov. 3, 2026, in Atlanta, Georgia (AP Photo/Brynn Anderson)

Protect Elections by Punishing Deception Narrowly, Not by Banning Technology

The Claude app icon is displayed on a computer screen photographed with a kaleidoscopic-effect filter in Creteil, France, on October 27, 2026, as Anthropic filed a Form S-1 with the Securities and Exchange Commission (SEC) for a planned initial public offering in the United States. (Photo by Samuel Boivin/NurPhoto via AP)

The Incident Report Is Becoming a Building Block of AI Governance

A banner with a portrait of Elon Musk is carried by members of Swadeshi Jagaran Manch, an organization affiliated to Hindu nationalist Rashtriya Swayamsevak Sangh (RSS), as they stage a protest against Elon Musk's Starlink, in New Delhi, India, Friday, Oct. 23, 2026. (AP Photo/Vipin)

Starlink, Reliance, and the Public Battle for India’s Orbit

OpenAI CEO Sam Altman sits for a conversation with Salesforce CEO Marc Benioff at Salesforce's Dreamforce conference at the Moscone Center on September 15, 2026 in San Francisco, California. (Photo by Benjamin Fanjoy/Getty Images)

Don’t Let ‘Misaligned’ and ‘Rogue’ Agents Obscure Corporate Accountability in OpenAI–Hugging Face Probes

In this photo illustration, the icon for the AI app "Claude" by Anthropic is seen through running water as it is displayed on a digital screen on September 16, 2026 in London, England. (Photo by Leon Neal/Getty Images)



Anthropic Needs to Disclose Its Tokenomics Before Its IPO

Anthropic CEO Dario Amodei looks on as United States President Donald Trump holds a press briefing with AI executives following a meeting on artificial intelligence, outside the West Wing of the White House on September 29, 2026 in Washington, DC. (Photo by Kevin Dietsch/Getty Images)

The SEC Should Block Anthropic’s IPO to Protect the Public

Director of National Intelligence and recently named head of the Super Intelligence Task Force Jay Clayton attends a roundtable discussion hosted by President Donald Trump on cybercrime in the East Room of the White House on October 21, 2026 in Washington, DC. (Photo by Alex Wong/Getty Images)

October 2026 US Tech Policy Roundup

A photo of a group of men in suits and ties gathered outdoors, speaking and smiling with trees in the background. Anthropic's CEO Dario Amodei is in the foreground speaking with big hand gestures and eyes closed. 

President Trump, left, speaks with Meta CEO Mark Zuckerberg as Dario Amodei, CEO and co-founder of Anthropic addresses reporters outside the White House, Sept. 29, 2026, in Washington DC. (AP Photo/Alex Brandon)

How AI Companies Want to Be Governed, and What That Means for AI Governance

Canada’s Prime Minister Mark Carney shakes hands with European Commission President Ursula von der Leyen following their closing news conference during the EU-Canada summit in Montreal on Friday, Oct. 30, 2026. (Christinne Muschi/The Canadian Press via AP)

Europe and Canada Plot a Digital Alliance as US Ties Fray

Michael Kratsios, Assistant to the President and Director of the White House Office of Science and Technology Policy attends Security Council meeting on Artificial intelligence and international security at UN Headquarters in New York, NY on September 23, 2026. (Photo by Lev Radin/Sipa USA via AP Images)

What’s Really Behind the Science Slowdown the White House Wants to Fix?

Photograph of a child staring at his smartphone in the dark with the light from the phone illuminating his face. 

Why Parental Consent Policies for Social Media Do Not Help Families

For every dollar an advertiser spends on a YouTube video, the platform keeps 45 cents. YouTube is not a neutral host that occasionally misses bad actors. It is a business partner in every monetized video, and it profits when those videos perform, including, new research suggests, ones that could break its own rules.

A new report from the Global Disinformation Index (GDI), “

,” puts a price on that partnership. GDI estimates that 100 English-language channels publishing what it classifies as hate speech are on track to earn about $13.3 million in ad revenue in 2026: $7.3 million for creators, $6 million for YouTube. One channel, earning an estimated $2.2 million a year, carried content that may breach YouTube’s Community Guidelines and German law. In September, it was still online, still showing ads and still viewable in Germany.

The report’s most revealing finding is not the size of these sums. It is how little anyone outside YouTube can know about them, and how conveniently that serves the company.

Six million dollars is a rounding error for a platform that 

 from ads and subscriptions in 2025 alone. The more plausible explanation for weak enforcement is not that hate is too lucrative to give up, but that enforcement costs time, staff and creator goodwill, while inaction costs little.

For creators, though, $2.2 million a year is a career. Recommendation systems tend to reward content that edges toward a platform’s policy line, and because YouTube shares the revenue, its interest in a high-performing video is aligned with the creator’s, not with the people that video targets.

GDI’s numbers deserve scrutiny. Five large language models labeled 19,297 videos; analysts manually reviewed 200. Its definition of hate speech follows the 

 and is broader than YouTube’s, so much of what it flagged is permitted on the platform. Critics will say GDI is counting lawful speech. But that gap is the point: YouTube’s narrow definitions decide what is monetizable, and only YouTube can test GDI’s estimates against real data.

YouTube’s repeat-offender clause applies in “rare cases” and never defines “repeatedly.” GDI found no evidence it had been used against the content it reviewed. A rule with an undefined trigger and unreported use is not really a rule. It is discretion. YouTube pledged to tighten its rules on monetizing hateful content after an 

. The pattern suggests enforcement tightens when revenue is threatened, then slackens when attention moves on.

What meaningful transparency would look like

YouTube’s transparency reports count removals, not videos that stay online but lose ads. Meaningful transparency would measure money, not takedowns. In practice, that means:

Enforcement data that matches the business model

 how many videos and channels are demonetized under the hate speech policy, by country of viewing.

A defined repeat-offender threshold, with annual figures on how often it is triggered. A rule YouTube must report on is a rule it must use.

 how much a video earned before demonetization, and how long it took. This shows whether enforcement removes the incentive or arrives after the money is made.

Video-level placement reports, so advertisers can see, and stop paying for, what their budgets fund.

Much of this sits within existing law. The 

 (DSA) requires platforms to explain any “restriction of monetary payments” to the affected user (

), and those explanations feed the Commission’s public 

. Regulators could check whether YouTube logs hate speech demonetizations there at all. The Commission can demand data on viewer location and revenue under 

 adopted in July 2025 lets vetted researchers request non-public platform data. In the UK, Category 1 transparency reports under the 

, due in 2027, give Ofcom a chance to require demonetization figures, not just removals.

, as GDI summarizes it, found trusted-flagger notices alleging illegal hate speech were not prioritized. Reporting can harden into box-ticking, and a demonetization figure means little without an independent sense of how much violating content exists. That is why researcher access matters as much as company reporting.

Following the money sidesteps the censorship fight

US-based creators account for 81% of the estimated revenue, an easy target in the transatlantic row over the DSA. But EU users were shown ads on sampled videos. If even 10% of views came from the EU, GDI estimates, that would mean $0.9 million in hate-linked ad revenue from January to August. This is only an estimate because YouTube alone knows where its viewers are.

Demonetization removes no video and silences no one. It asks a company to stop paying for, and profiting from, content that breaks its own rules or the law where it is viewed. That shifts the question from “what should come down” to “what should be paid for.” A platform that cannot answer it with data has already told regulators something.

After United States midterm elections in which Democrats posted 

, candidates took the stage to deliver victory speeches. Consistent with the salience of AI and data centers in the political discourse, concerns over the influence of tech oligarchs such as Elon Musk, and the role of Big Tech in shaping the information ecosystem and the economy, many candidates named these issues directly. Some also complained about AI deepfakes.

What follows is a sample of such statements from races in a variety of jurisdictions.

Courtney C. Radsch, PhD, is a journalist, scholar and human rights advocate who currently directs the Center for Media & Digital Governance at Open Markets Institute and is a non-resident fellow at the Brookings Institution. She serves on the board of Tech Policy Press.

 and across state offices represent more than just an opportunity to stave off democratic decline. They are also an instructive referendum on the power of Big Tech and AI, and the broad desire among the electorate to hold tech to account.

Concerns about unfettered power of tech firms and their aggressive AI vision have propelled a 

 against the infestation of data centers in communities around the country, fueled the movement against 

 and the concentration of power in a handful of Big Tech firms, and underpinned discontent with the vast corruption and collusion between the political class and the Trump administration in particular.

When the new Congress takes office in January, the question is: will this majority confront concentrated corporate power and technofascism—or simply oversee its continued expansion?

AI governance, Big Tech accountability, monopoly break-ups, media plurality and press freedom belong on the same agenda.

The states have already shown where popular will is headed in terms of putting limits on permissible types of 

Each of these ongoing regulatory dramas is an expression of the same underlying failure of Congress do its job on behalf of the American people. Policymakers have stood by as profit-maximizing corporations built business models on the commercial exploitation of personal and commercial data, rewarding social and psychological manipulation, and

There remains a massive legal vacuum where basic protective frameworks like fiduciary duties, liability standards, enforceable transparency and privacy safeguards simply do not exist that the next Congress can now address. It must take action to reinforce these efforts at the federal level. 

Congress must also mitigate concentration of power over our information and communications system, from 

 at the root of AI training and inference and 

, we cannot let the transition to AI entrench the same gatekeepers under new business models. Independent journalism must have the power to negotiate with tech firms through collective bargaining, statutory licensing and enforcement of copyright and antitrust law, and not merely the option to accept whatever terms platforms offer.

Understanding the power that the new majority in Congress has offers a useful framework for turning this opening into action — check out the 

We Build Progress explainer on majority power

Use hearings and lawful subpoenas to demand answers from both corporate executives and public officials and hold them accountable. The agenda should include: Examining media consolidation and editorial retaliation by the Trump administration and formerly independent regulators that are supposed to provide oversight. Scrutinizing media mergers and investigating whether regulatory or licensing powers are being used to pressure independent reporting. Investigating exclusionary deals, lobbying and political influence by Big Tech and its AI brethren.

 Make room for sustained scrutiny of AI — both frontier and sectoral AI — information markets and communication systems to avoid another cycle of CEO appearances with no follow-through.

: Choose leaders prepared to challenge corporate gatekeepers, including when their influence reaches inside the Democratic Party, and resist the temptation to rely once again on Big Tech largess. The people voted for accountability; Democrats should provide it.

Put enforceable AI safeguards including related to design and liability; stronger competition protections; updated protections against media consolidation that accounts for Big Tech players in streaming, TV and cloud; and proactive protections for workers, including information producers and the creative sectors, as well as advertising in AI on the voting agenda. Reject efforts to trade away state AI protections for industry-friendly federal inaction.

Specifically, Congress should investigate reports that Meta interfered in democratic elections in the US (for example, 

 Indivisible’s accounts during national No Kings protests) and Brazil (Meta faced 

, that it favored President Lula da Silva’s challenger in the recent elections by suspending Lula's campaign advertising account, suppressing posts, and blocking AI-generated content). Congressional investigators should do 

 into how Big Tech and AI companies politically interfere in or manipulate access to information and discriminate against specific types of accounts or content based on 

 from independent, non-partisan experts and force executives to testify under oath.

Congressional leaders should also take full advantage of their public platform to elevate oversight, press freedom and democratic accountability rather than to confer prestige on those seeking to escape scrutiny, as has been the pattern over the past few years.

A majority is not a magic wand, but at least it’s a check on unfettered one-party rule. The 

 and presidential veto remain real constraints on legislation and will undoubtedly be deployed in Trump’s remaining lame duck term. Congress does not itself decide individual merger cases, and the Supreme Court 

 the role of independent agencies originally set up by Congress. But those limits are no excuse to abandon oversight, agenda-setting or the work of building stronger democratic protections and passing new laws where needed.

Winning a majority opens the door. The extent to which Democrats effectively wield public power to disperse private power, break up Big Tech’s influence over the information and communications ecosystem and defend an independent press is the test that will determine if this shift in power will curb rising autocracy and technofascism in America.

Alissa Cooper is the executive director of the 

 all announced plans to support a new mechanism that lets web publishers express their desire to opt out of having their content used to train AI models. The 

, authored by Anthropic’s Kevin Kelley, attracted considerable attention across the tech press (see 

, with the coverage highlighting the prospect of giving publishers greater control over how AI companies use their content.

But the announcements — and much of the subsequent coverage — leave out important context about the relationship between the product changes, ongoing standardization activity, and the policy environment. Understanding these nuances requires looking at the ongoing standards process and the broader policy debates surrounding AI, search, and competition.

The new proposal comes after years of disputes between publishers and companies that crawl the web — in court rooms, industry standards bodies, and public forums. Nearly two years ago, the Internet Engineering Task Force (IETF), the premier internet standards development organization, launched an effort known as 

 (“AIPREF”) to develop new standards that would, among other things, give websites expanded options for automatically expressing preferences about how their content gets used for AI-related purposes. This work is meant to build in part on a prior IETF standard, 

, which specifies the format for the commonly used “robots.txt” files employed by websites to control crawlers. Participants from Anthropic, Google, and Microsoft have all been actively involved in the AIPREF group, while OpenAI contributions have been minimal, despite the company stating last week that the announcement “strengthens our continued participation in the IETF standards discussions.”

This AIPREF work was sparked in part by the process of developing the 

, a voluntary compliance mechanism under the EU AI Act. Is signatories (most of the largest American and European AI model companies) commit to abide by the machine-readable preferences that sites express.

When looking beyond the headlines, what’s most important to understand about these announcements?

1. The mechanism is not an official “standard” — but adoption by the four largest search and AI providers might make it a de facto one.

Last week’s proposal has no official status in the IETF. It will need to be discussed and debated (probably at some length) to see if it will move forward toward standardization. But when the largest companies deploy support for it (all have committed to do so by 2027), that standardization status may not matter. If site operators are convinced to change their robots.txt files to comply with the new proposal, it may become the de facto way of signaling AI training preferences regardless of where the standards end up.

The proposal announced on October 30 (the “policy token draft,” for short) is documented in what is colloquially known as an “individual draft” — a submission to the IETF made by an author, which has no formal standing of any kind in the standards process. Anyone can submit an individual draft to the IETF, and over 1,000 are submitted each year.

The AIPREF working group already has two other drafts that are further along in the standards process, one that expresses a vocabulary for AI-related preferences (the “

”) and one that specifies how those preferences could be expressed in the widely used robots.txt files that many websites already publish (the “

”). In IETF parlance, these two drafts have been “adopted” by the AIPREF working group, which means the participants in the working group had rough consensus to pursue those approaches to meet the working group’s goals.

The policy token draft has no such consensus since it’s one individual’s submission that has not yet been considered by the group. After discussion, the group may or may not adopt it or integrate its contents into the attachment draft.

2. A training preference is nice to have, but a search-specific preference is missing, while the spotlight in the industry has shifted to inference.

Much of the discussion in the AIPREF working group over the last two years has centered on the definitions of new AI-related preferences in the vocabulary draft. These definitions matter because they are the categories for which sites will be able to express preferences in their robots.txt files (and via other technical mechanisms).

After significant discussion, the group has made progress towards settling on a definition of “AI training,” although discussions of some wording remain ongoing. After significantly 

 (and more heated) discussion, a definition of what it means for website content to be used in “search” has also been (mostly) provisionally agreed. Both definitions saw updates and new text added after the working group met in person at the end of August. Contentious discussions about a broader and more amorphous category — which has variously tried to cover “AI use,” “inference,” “grounding,” and related uses that occur separate from model training — are ongoing.

The policy token draft specifically leverages the “AI training” definition from the vocabulary draft and proposes a way that sites could express a preference to disallow all AI training, across all crawlers, by adding a few simple lines to their existing robots.txt files. The attachment draft already contains a similar mechanism, but the advantage of the approach in the policy token draft is that it would more immediately be machine-readable by many crawlers that are already deployed. This is the key value of the approach in the policy token draft: for site owners suffering from having to constantly update an ever-growing list of crawlers that they individually disallow, the newly proposed mechanism offers the prospect of a single, simple solution to express a preference to disallow all crawlers from AI training.

But what about search uses? And inference-time uses more broadly?

It is notable that the policy token draft does not provide an equivalent mechanism to cover search, especially given that the two companies that represent almost the entire web search market have signed up already to support it. It could have been quite powerful and clarifying for them to send the message that they want to make “search: yes; AI training: no” simple for sites to declare. The search definition in the vocabulary draft could have been leveraged in the same way that the AI training definition was. Publishers’ inability to express search-specific preferences has been the subject of regulatory investigation and intervention across multiple jurisdictions, making this omission all the more striking.

The new proposal’s focus on training also reinforces the difficult line-drawing that is still to come around inference-time uses more broadly. While the AIPREF working group has churned through multiple attempts at defining an inference or “AI usage” category, consensus has remained elusive, even as negotiation of licensing deals has 

 towards inference and recurring revenue. Microsoft’s announcement indicated that the company will combine support for the policy token mechanism with its own company-specific grounding preference mechanism, demonstrating the need for preference signals that go beyond training.

3. Since the mechanism has yet to be standardized, signatories to the EU AI Act Code of Practice are not required to commit to recognizing it.

Google’s announcement stated that the proposed mechanism is “consistent with the EU Code of Practice for General Purpose AI (GPAI) Model Providers under the EU AI Act.” Yet 

 is clear that it commits signatories to follow 

Signatories commit … to employ web-crawlers that read and follow instructions expressed in accordance with the Robot Exclusion Protocol (robots.txt), as specified in the Internet Engineering Task Force (IETF) Request for Comments No. 9309, and any subsequent version of this Protocol for which the IETF demonstrates that it is technically feasible and implementable by AI providers and content providers, including rightsholders

As noted above, with the policy token draft having been published less than a week ago, it has a ways to go before being formally standardized, extending RFC 9309, or demonstrating technical feasibility. As much as all involved surely want a speedy resolution, giving interested stakeholders a chance to review and debate the mechanism’s design is a critical part of the process that helps yield stronger standards that are more easily deployable and (hopefully) meet the needs of more website owners.

A common mechanism supported by the largest AI and search providers could substantially reduce the burden on publishers who must currently manage crawler rules one crawler at a time. But it is important to be clear about the limitations of what has been announced: the preference applies only to AI training, leaving out search and other inference-time uses. As an individual draft, it has many steps to go before formal standardization, during which time its design could change significantly. That process should be allowed to run before a few of the world’s largest companies decide the rules for the wider web to have to follow.

A crowd of supporters surround President Lula holding a microphone at a podium draped with the Brazilian flag.

President Luiz Inacio Lula da Silva delivers a victory speech after winning the presidential runoff in Brazil, Oct. 25, 2026. (AP Photo/Andre Penner)

Lula’s Win Signals Fight to Regulate Social Media Will Escalate in Brazil

An illustrative photo of a man walking through the corridors of the European Parliament in Strasbourg, France.

Behind the scenes - European Parliament in Strasbourg

Despite Spyware Attacks on Its Own Officials, EU Response Falls Short

A person holds a giant Brazilian flag while perched above a crowd of people at a rally on a large avenue, a few people are holding phones in the air. One person holds their hand in the air in the L shape, signifying support for Lula. 

Supporters of President Luiz Inacio Lula da Silva at an election rally on Oct 11, 2026 in Sao Paulo, Brazil. (Rodilei Morais/Fotoarena/Sipa USA)

Meta Moderation Failures Loom Over Brazil’s Runoff Presidential Election

A voter leaves a polling station as voting continues in the Holborn and St Pancras by-election on October 8, 2026 in London, England. (Photo by Leon Neal/Getty Images)

UK Election Watchdog Develops AI System to Flag Deepfakes Within 3 Hours

Tech Policy Press - Technology and Democracy

Tech Policy Press is tracking laws and regulations, along with government investigations and litigation, that will shape the rules and accountability for tech companies.

Latest

Podcast

Recent

Our content delivered to your inbox

Thank you!

Around the globe