For a moment, it looked like the tech world’s powerbrokers had pulled it off. Buried deep in a Republican infrastructure and tax package was a sleeper provision — the so-called AI moratorium — that would have blocked states from passing their own AI laws for up to a decade. It was an audacious move: centralize control over one of the most consequential technologies in history, bypass 50 state legislatures, and hand the reins to a small circle of federal agencies and especially to tech industry insiders.
But then it collapsed.
The Senate voted 99–1 to strike the moratorium. Governors rebelled. Attorneys general sounded the alarm. Artists, parents, workers, and privacy advocates from across the political spectrum said “no.” Even hardline conservatives like Ted Cruz eventually reversed course when it came down to the final vote. The message to Big Tech or the famous “Little Tech” was clear: the states still matter — and America’s tech elite ignore that at their peril. (“Little Tech” is the latest rhetorical deflection promoted by Big Tech aka propaganda.)
The old Google crowd pushed the moratorium–their fingerprints were obvious. Having gotten fabulously rich off of their two favorites: The DMCA farce and the Section 230 shakedown. But there’s increasing speculation that White House AI Czar and Silicon Valley Viceroy David Sacks, PayPal alum and vocal MAGA-world player, was calling the ball. If true, that makes this defeat even more revealing.
Sacks represents something of a new breed of power-hungry tech-right influencer — part of the emerging “Red Tech” movement that claims to reject woke capitalism and coastal elitism but still wants experts to shape national policy from Silicon Valley, a chapter straight out of Philip Dru: Administrator. Sacks is tied to figures like Peter Thiel, Elon Musk, and a growing network of Trump-aligned venture capitalists. But even that alignment couldn’t save the moratorium.
Why? Because the core problem wasn’t left vs. right. It was top vs. bottom.
In 1964, Ronald Reagan’s classic speech called A Time for Choosing warned about “a little intellectual elite in a far-distant capitol” deciding what’s best for everyone else. That warning still rings true — except now the “capitol” might just be a server farm in Menlo Park or a podcast studio in LA.
The AI moratorium was an attempt to govern by preemption and fiat, not by consent. And the backlash wasn’t partisan. It came from red states and blue ones alike — places where elected leaders still think they have the right to protect their citizens from unregulated surveillance, deepfakes, data scraping, and economic disruption.
So yes, the defeat of the moratorium was a blow to Google’s strategy of soft-power dominance. But it was also a shot across the bow for David Sacks and the would-be masters of tech populism. You can’t have populism without the people.
If Sacks and his cohort want to play a long game in AI policy, they’ll have to do more than drop ideas into the policy laundry of think tank white papers and Beltway briefings. They’ll need to win public trust, respect state sovereignty, and remember that governing by sneaky safe harbors is no substitute for legitimacy.
The moratorium failed because it presumed America could be governed like a tech startup — from the top, at speed, with no dissent. Turns out the country is still under the impression they have something to say about how they are governed, especially by Big Tech.
Tag: AI Legislation
The Patchwork They Fear Is Accountability: Why Big AI Wants a Moratorium on State Laws
Why Big Tech’s Push for a Federal AI Moratorium Is Really About Avoiding State Investigations, Liability, and Transparency
As Congress debates the so-called “One Big Beautiful Bill Act,” one of its most explosive provisions has stayed largely below the radar: a 10-year or 5-year or any-year federal moratorium on state and local regulation of artificial intelligence. Supporters frame it as a common sense way to prevent a “patchwork” of conflicting state laws. But the real reason for the moratorium may be more self-serving—and more ominous.
The truth is, the patchwork they fear is not complexity. It’s accountability.
Liability Landmines Beneath the Surface
As has been well-documented by the New York Times and others, generative AI platforms have likely ingested and processed staggering volumes of data that implicate state-level consumer protections. This includes biometric data (like voiceprints and faces), personal communications, educational records, and sensitive metadata—all of which are protected under laws in states like Illinois (BIPA), California (CCPA/CPRA), and Texas.
If these platforms scraped and trained on such data without notice or consent, they are sitting on massive latent liability. Unlike federal laws, which are often narrow or toothless, many state statutes allow private lawsuits and statutory damages. Class action risk is not hypothetical—it is systemic. It is crucial for policymakers to have a clear understanding of where we are today with respect to the collision between AI and consumer rights, including copyright. The corrosion of consumer rights by the richest corporations in commercial history is not something that may happen in the future. Massive violations have already occurred, are occurring this minute, and will continue to occur into the future at an increasing rate.
The Quiet Race to Avoid Discovery
State laws don’t just authorize penalties; they open the door to discovery. Once an investigation or civil case proceeds, AI platforms could be forced to disclose exactly what data they trained on, how it was retained, and whether any red flags were ignored.
This mirrors the arc of the social media addiction lawsuits now consolidated in multidistrict litigation. Platforms denied culpability for years—until internal documents showed what they knew and when. The same thing could happen here, but on a far larger scale.
Preemption as Shield and Sword
The proposed AI moratorium isn’t a regulatory timeout. It’s a firewall. By halting enforcement of state AI laws, the moratorium could prevent lawsuits, derail investigations, and shield past conduct from scrutiny.
Even worse, the Senate version conditions broadband infrastructure funding (BEAD) on states agreeing to the moratorium—an unconstitutional act of coercion that trades state police powers for federal dollars. The legal implications are staggering, especially under the anti-commandeering doctrine of Murphy v. NCAA and Printz v. United States.
This Isn’t About Clarity. It’s About Control.
Supporters of the moratorium, including senior federal officials and lobbying arms of Big Tech, claim that a single federal standard is needed to avoid chaos. But the evidence tells a different story.
States are acting precisely because Congress hasn’t. Illinois’ BIPA led to real enforcement. California’s privacy framework has teeth. Dozens of other states are pursuing legislation to respond to harms AI is already causing.
In this light, the moratorium is not a policy solution. It’s a preemptive strike.
Who Gets Hurt?
– Consumers, whose biometric data may have been ingested without consent
– Parents and students, whose educational data may now be part of generative models
– Artists, writers, and journalists, whose copyrighted work has been scraped and reused
– State AGs and legislatures, who lose the ability to investigate and enforce
Google Is an Example of Potential Exposure
Google’s former executive chairman Eric Schmidt has seemed very, very interested in writing the law for AI. For example, Schmidt worked behind the scenes for the two years at least to establish US artificial intelligence policy under President Biden. Those efforts produced the “Executive Order on the Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence“, the longest executive order in history. That EO was signed into effect by President Biden on October 30. In his own words during an Axios interview with Mike Allen, the Biden AI EO was signed just in time for Mr. Schmidt to present that EO as what Mr. Schmidt calls “bait” to the UK government–which convened a global AI safety conference at Bletchley Park in the UK convened by His Excellency Rishi Sunak (the UK’s tech bro Prime Minister) that just happened to start on November 1, the day after President Biden signed the EO. And now look at the disaster that the UK AI proposal would be.
As Mr. Schmidt told Axios:
So far we are on a win, the taste of winning is there. If you look at the UK event which I was part of, the UK government took the bait, took the ideas, decided to lead, they’re very good at this, and they came out with very sensible guidelines. Because the US and UK have worked really well together—there’s a group within the National Security Council here that is particularly good at this, and they got it right, and that produced this EO which is I think is the longest EO in history, that says all aspects of our government are to be organized around this.
Apparently, Mr. Schmidt hasn’t gotten tired of winning. Of course, President Trump rescinded the Biden AI EO which may explain why we are now talking about a total moratorium on state enforcement which percolated at a very pro-Google shillery called R Street Institute, apparently by one Adam Thierer . But why might Google be so interested in this idea?
Google may face exponentially acute liability under state laws if it turns out that biometric or behavioral data from platforms like YouTube Kids or Google for Education were ingested into AI training sets.
These services, marketed to families and schools, collect sensitive information from minors—potentially implicating both federal protections like COPPA and more expansive state statutes. As far back as 2015, Senator Ben Nelson raised alarms about YouTube Kids, calling it “ridiculously porous” in terms of oversight and lack of safeguards. If any of that youth-targeted data has been harvested by generative AI tools, the resulting exposure is not just a regulatory lapse—it’s a landmine.
The moratorium could be seen as an attempt to preempt the very investigations that might uncover how far that exposure goes.
What is to be Done?
Instead of smuggling this moratorium into a must-pass bill, Congress should strip it out and hold open hearings. If there’s merit to federal preemption, let it be debated on its own. But do not allow one of the most sweeping power grabs in modern tech policy to go unchallenged.
The public deserves better. Our children deserve better. And the states have every right to defend their people. Because the patchwork they fear isn’t legal confusion.
It’s accountability.
Machines Don’t Let Machines Do Opt Outs: Why robots.txt won’t get it done for AI Opt Outs
[Following is based on an except from the Artist Rights Institute’s submission to the UK Intellectual Property Office consultation on a UK AI legislative proposal]
The fundamental element of any rights reservation regime is knowing which work is being blocked by which rights owner. This will require creating a metadata identification regime for all works of authorship, a regime that has never existed and must be created from whole cloth. As the IPO is aware, metadata for songs is quite challenging as was demonstrated in the IPO’s UK Industry Agreement on Music Streaming Metadata Working Groups.
Using machine-readable formats for reservations sounds like would be an easy fix, but it creates an enormous burden on the artist, i.e., the target of the data scraper, and is a major gift to the AI platform delivered by government. We can look to the experience with robots.txt for guidance.
Using a robots.txt file or similar “do not index” file puts far too big a bet on machines getting it right in the silence of the Internet. Big Tech has used this opt-out mantra for years in a somewhat successful attempt to fool lawmakers into believing that blocking is all so easy. If only there was a database, even a machine can do it. And yet there are still massive numbers of webpages copied and those pages that were copied for search (or the Internet Archive) are now being used to train AI.
It also must be said that a “disallow” signal is designed to work with file types or folders, not millions of song titles or sound recordings (see GEMA’s lawsuits against AI platforms). For example, this robots.txt code will recognize and block a “private-directory” folder but would otherwise allow Google to freely index the site while blocking Bing from indexing images:
User-agent: *
Disallow: /private-directory/
User-agent: Googlebot
Allow: /
User-agent: Bingbot
Disallow: /images/
Theoretically, existing robots.txt files could be configured to block AI crawlers entirely by designating known crawlers as user-agents such as ChatGPT. However, there are many known defects when robots.txt can fail to block web crawlers or AI data scrapers including:
Malicious or non-compliant crawlers might ignore the rules in a robots.txt file and continue to scrape a website despite the directives.
Incorrect Syntax of a robots.txt file can lead to unintended results, such as not blocking the intended paths or blocking too many paths.
Issues with server configuration can prevent the robots.txt file from being correctly read or accessed by crawlers.
Content generated dynamically through JavaScript or AJAX requests might not be blocked if robots.txt is not properly configured to account for these resources.
Unlisted crawlers or scrapers not known to the user may not adhere to the intended rules.
Crawlers using cached versions of a site may bypass rules in a robots.txt file, particularly updated rules since the cache was created.
Subdomains and Subdirectories limiting the scope of the rules can lead to not blocking all intended subdomains or subdirectories.
Missing Entire Lists of Songs, Recordings, or Audiovisual works.
While robots.txt and similar techniques theoretically are useful tools for managing crawler access, they are not foolproof. Implementing additional security measures, such as IP blocking, CAPTCHA, rate limiting, and monitoring server logs, can help strengthen a site’s defenses against unwanted scraping. However, like the other tools that were supposed to level the playing field for artists against Big Tech, none of these tools are free, all of them require more programming knowledge than can reasonably be expected, all require maintenance, and at scale, all of them can be gamed or will eventually fail.
It must be said that all of the headaches and expense of keeping Big Tech out is because Big Tech so desperately wants to get in.
The difference between blocking a search engine crawler and an AI data scraper (which could each be operated by the same company in the case of Meta, Bing or Google) is that failing to block a search engine crawler is inconvenient for artists, but failing to block an AI data scraper is catastrophic for artists.
Even if the crawlers worked seamlessly, should any of these folders change names and the site admin forgets to change the robots.txt file, that is asking a lot of every website on the Internet.
It must also be said that pages using machine readable blocking tools may result in pages being downranked, particularly for AI platforms closely associated with search engines. Robots.txt blocking already has problems with crawlers and downranking for several reasons. A robots.txt file itself doesn’t directly cause pages to be downranked in search results. However, it can indirectly affect rankings by limiting search engine crawlers’ access to certain parts of a website. Here’s how:
Restricted Crawling: If you block crawlers from accessing important pages using robots.txt, those pages won’t be indexed. Without indexing, they won’t appear in search results, let alone rank.
Crawl Budget Mismanagement: For large websites, search engines allocate a “crawl budget”—the number of pages they crawl in a given time. If robots.txt doesn’t guide crawlers efficiently, that may randomly leave pages unindexed.
No Content Evaluation: If a page is blocked by robots.txt but still linked elsewhere, search engines might index its URL without evaluating its content. This can result in poor rankings since the page’s relevance and quality can’t be assessed.
The TDM safe harbor is too valuable and potentially too dangerous to leave to machines.
Music Tech Solutions 