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Today's Topics:
1. Search Engines, AI, And The Long Fight Over Fair Use (Kim Holburn)
2. Re: Search Engines, AI, And The Long Fight Over Fair Use (David)
3. Re: Search Engines, AI, And The Long Fight Over Fair Use (David)
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Message: 1
Date: Sun, 1 Feb 2026 18:24:00 +1100
From: Kim Holburn <[email protected]>
To: Link mailing list <[email protected]>
Subject: [LINK] Search Engines, AI, And The Long Fight Over Fair Use
Message-ID: <[email protected]>
Content-Type: text/plain; charset=UTF-8; format=flowed
https://www.techdirt.com/2026/01/30/search-engines-ai-and-the-long-fight-over-fair-use/
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.
--
Kim Holburn
IT Network & Security Consultant
+61 404072753
mailto:[email protected] aim://kimholburn
skype://kholburn - PGP Public Key on request
------------------------------
Message: 2
Date: Mon, 02 Feb 2026 11:18:49 +1100
From: David <[email protected]>
To: [email protected]
Subject: Re: [LINK] Search Engines, AI, And The Long Fight Over Fair
Use
Message-ID: <5806992.ZASKD2KPVS@ulysses>
Content-Type: text/plain; charset="utf-8"
On Sunday, 1 February 2026 18:24:00 AEDT Kim Holburn wrote:
> 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.
"...they enable new forms of knowledge and expression" AND PROFIT.
The local Municipal Library, a University Library, and the National Library in
Canberra are all run for the noble aims the article proclaims so loudly &
piously. But does anyone seriously think Google would have its' search engine
if it were a loss-making venture?
By indexing the content of a textbook and making it available online as a
supposed right without negotiating payment, Google is arguably stealing the
publisher's right to make a profit by publishing the book / periodical / paper
in the first place. As a business model it seems ultimately self-defeating,
but we'll see.
Then there's the parallel dimension of privacy. How many people are really
aware that every email having an originator or recipient with a "free" gmail
address has it scanned with an AI tool?
_DavidL_
------------------------------
Message: 3
Date: Mon, 02 Feb 2026 11:39:00 +1100
From: David <[email protected]>
To: [email protected]
Cc: [email protected]
Subject: Re: [LINK] Search Engines, AI, And The Long Fight Over Fair
Use
Message-ID: <2718454.vYhyI6sBWr@ulysses>
Content-Type: text/plain; charset="us-ascii"
Sorry about this Kim, but I neglected to state that you were quoting from an
article in
https://www.techdirt.com/2026/01/30/search-engines-ai-and-the-long-fight-over-fair-use/
On Monday, 2 February 2026 11:18:49 AEDT I wrote:
> On Sunday, 1 February 2026 18:24:00 AEDT Kim Holburn wrote:
>> Copying that works in order to understand them, [...]
_DavidL_
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