Search Engines, AI, And The Long Fight Over Fair Use

11 hours 22 minutes ago

We're taking part in Copyright Week, a series of actions and discussions supporting key principles that should guide copyright policy. Every day this week, various groups are taking on different elements of copyright law and policy, and addressing what's at stake, and what we need to do to make sure that copyright promotes creativity and innovation.

Long before generative AI, copyright holders warned that new technologies for reading and analyzing information would destroy creativity. Internet search engines, they argued, were infringement machines—tools that copied copyrighted works at scale without permission. As they had with earlier information technologies like the photocopier and the VCR, copyright owners sued.

Courts disagreed. They recognized that copying works in order to understand, index, and locate information is a classic fair use—and a necessary condition for a free and open internet.

Today, the same argument is being recycled against AI. It’s whether copyright owners should be allowed to control how others analyze, reuse, and build on existing works.

Fair Use Protects Analysis—Even When It’s Automated

U.S. courts have long recognized that copying for purposes of analysis, indexing, and learning is a classic fair use. That principle didn’t originate with artificial intelligence. It doesn’t disappear just because the processes are performed by a machine.

Copying that works in order to understand them, extract information from them, or make them searchable is transformative and lawful. That’s why search engines can index the web, libraries can make digital indexes, and researchers can analyze large collections of text and data without negotiating licenses from millions of rightsholders. These uses don’t substitute for the original works; they enable new forms of knowledge and expression.

Training AI models fits squarely within that tradition. An AI system learns by analyzing patterns across many works. The purpose of that copying is not to reproduce or replace the original texts, but to extract statistical relationships that allow the AI system to generate new outputs. That is the hallmark of a transformative use. 

Attacking AI training on copyright grounds misunderstands what’s at stake. If copyright law is expanded to require permission for analyzing or learning from existing works, the damage won’t be limited to generative AI tools. It could threaten long-standing practices in machine learning and text-and-data mining that underpin research in science, medicine, and technology. 

Researchers already rely on fair use to analyze massive datasets such as scientific literature. Requiring licenses for these uses would often be impractical or impossible, and it would advantage only the largest companies with the money to negotiate blanket deals. Fair use exists to prevent copyright from becoming a barrier to understanding the world. The law has protected learning before. It should continue to do so now, even when that learning is automated. 

A Road Forward For AI Training And Fair Use 

One court has already shown how these cases should be analyzed. In Bartz v. Anthropic, the court found that using copyrighted works to train an AI model is a highly transformative use. Training is a kind of studying how language works—not about reproducing or supplanting the original books. Any harm to the market for the original works was speculative. 

The court in Bartz rejected the idea that an AI model might infringe because, in some abstract sense, its output competes with existing works. While EFF disagrees with other parts of the decision, the court’s ruling on AI training and fair use offers a good approach. Courts should focus on whether training is transformative and non-substitutive, not on fear-based speculation about how a new tool could affect someone’s market share. 

AI Can Create Problems, But Expanding Copyright Is the Wrong Fix 

Workers’ concerns about automation and displacement are real and should not be ignored. But copyright is the wrong tool to address them. Managing economic transitions and protecting workers during turbulent times may be core functions of government, but copyright law doesn’t help with that task in the slightest. Expanding copyright control over learning and analysis won’t stop new forms of worker automation—it never has. But it will distort copyright law and undermine free expression. 

Broad licensing mandates may also do harm by entrenching the current biggest incumbent companies. Only the largest tech firms can afford to negotiate massive licensing deals covering millions of works. Smaller developers, research teams, nonprofits, and open-source projects will all get locked out. Copyright expansion won’t restrain Big Tech—it will give it a new advantage.  

Fair Use Still Matters

Learning from prior work is foundational to free expression. Rightsholders cannot be allowed to control it. Courts have rejected that move before, and they should do so again.

Search, indexing, and analysis didn’t destroy creativity. Nor did the photocopier, nor the VCR. They expanded speech, access to knowledge, and participation in culture. Artificial intelligence raises hard new questions, but fair use remains the right starting point for thinking about training.

Joe Mullin

【経済】サナエノミクスに市場が警告! 国債頼み 薄氷の財政 黒字化〝命綱〟手放すな 怖い日本版トラスショック=志田義寧

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JCJ

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Rent-Only Copyright Culture Makes Us All Worse Off

1 day 12 hours ago

We're taking part in Copyright Week, a series of actions and discussions supporting key principles that should guide copyright policy. Every day this week, various groups are taking on different elements of copyright law and policy, and addressing what's at stake, and what we need to do to make sure that copyright promotes creativity and innovation.

In the Netflix/Spotify/Amazon era, many of us access copyrighted works purely in digital form – and that means we rarely have the chance to buy them. Instead, we are stuck renting them, subject to all kinds of terms and conditions. And because the content is digital, reselling it, lending it, even preserving it for your own use inevitably requires copying. Unfortunately, when it comes to copying digital media, US copyright law has pretty much lost the plot.

As we approach the 50th anniversary of the 1976 Copyrights, the last major overhaul of US copyright law, we’re not the only ones wondering if it’s time for the next one. It’s a high-risk proposition, given the wealth and influence of entrenched copyright interests who will not hesitate to send carefully selected celebrities to argue for changes that will send more money, into fewer pockets, for longer terms. But it’s equally clear that and nowhere is that more evident than the waning influence of Section 109, aka the first sale doctrine.

First sale—the principle that once you buy a copyrighted work you have the right to re-sell it, lend it, hide it under the bed, or set it on fire in protest—is deeply rooted in US copyright law. Indeed, in an era where so many judges are looking to the Framers for guidance on how to interpret current law, it’s worth noting that the first sale principles (also characterized as “copyright exhaustion”) can be found in the earliest copyright cases and applied across the rights in the so-called “copyright bundle.”

Unfortunately, courts have held that first sale, at least as it was codified in the Copyright Act, only applies to distribution, not reproduction. So even if you want to copy a rented digital textbook to a second device, and you go through the trouble of deleting it from the first device, the doctrine does not protect you.

We’re all worse off as a result. Our access to culture, from hit songs to obscure indie films, are mediated by the whims of major corporations. With physical media the first sale principle built bustling second hand markets, community swaps, and libraries—places where culture can be shared and celebrated, while making it more affordable for everyone.

And while these new subscription or rental services have an appealing upfront cost, it comes with a lot more precarity. If you love rewatching a show, you may be chasing it between services or find it is suddenly unavailable on any platform. Or, as fans of Mad Men or Buffy the Vampire Slayer know, you could be stuck with a terrible remaster as the only digital version available

Last year we saw one improvement with California Assembly Bill 2426 taking effect. In California companies must now at least disclose to potential customers if a “purchase” is a revocable license—i.e. If they can blow it up after you pay. A story driving this change was Ubisoft revoking access to “The Crew” and making customers’ copies unplayable a decade after launch. 

On the federal level, EFF, Public Knowledge, and 15 other public interest organizations backed Sen. Ron Wyden’s message to the FTC to similarly establish clear ground rules for digital ownership and sales of goods. Unfortunately FTC Chairman Andrew Ferguson has thus far turned down this easy win for consumers.

As for the courts, some scholars think they have just gotten it wrong. We agree, but it appears we need Congress to set them straight. The Copyright Act might not need a complete overhaul, but Section 109 certainly does. The current version hurts consumers, artists, and the millions of ordinary people who depend on software and digital works every day for entertainment, education, transportation, and, yes, to grow our food. 

We realize this might not be the most urgent problem Congress confronts in 2026—to be honest, we wish it was—but it’s a relatively easy one to solve. That solution could release a wave of new innovation, and equally importantly, restore some degree of agency to American consumers by making them owners again.

Corynne McSherry

[B] 日韓首脳会談で遺骨のDNA鑑定協力に合意 市民団体が政府説明を受けて記者会見

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長生炭鉱水没事故における犠牲者の遺骨返還を巡り、1月13日に行われた日韓首脳会談において、遺骨の身元特定に向けたDNA鑑定を日韓両政府が協力して行うことが合意された。この合意を受けて、遺骨収容・返還事業に取り組む市民団体「長生炭鉱の水非常を歴史に刻む会」(以下、「刻む会」)は、1月20日に政府(外務省、警察庁)からDNA鑑定の実施に向けた非公開の説明を受けたとして、説明会後、記者会見を開いた。(小栗俊也)
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