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<h1>Copyright Throughout a Creative AI Pipeline</h1><div class="byline">By Sancho McCann · <span class="date">
<time datetime="2021-07-27">2021-07-27</time>, <a href="https://github.com/sanchom/sanchom.github.io/commits/master-source/AI-copyright.html.pm">edited</a>: <time datetime="2023-03-26">2023-03-26</time>
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<root><figure><p><img potential-feature="potential-feature" src="assets/cortes-wheat.jpg"/></p><figcaption>This is an im­age I cre­at­ed us­ing the AI tool, <em><a href="https://deepdreamgenerator.com">Deep Dream Generator</a></em>. I used it to ap­ply the style of Van Gogh’s <em><a href="https://en.wikipedia.org/wiki/Wheat_Field_with_Cypresses">A Wheatfield with Cypresses</a></em> to a pho­to that I took of a bay at Cortes Island. That web­site does not claim own­er­ship of the AI out­put.</figcaption></figure><p>My ar­ti­cle, “Copyright Throughout a Creative AI Pipeline,”<span class="sidenote-wrapper"><span><label for="fn-1" class="margin-toggle sidenote-number"></label><input type="checkbox" id="fn-1" class="margin-toggle"/><input type="checkbox" id="fn-1-expand" class="margin-expand"/><label for="fn-1-expand" class="sidenote" hyphens="none"><span class="bibliography-entry full-form-citation" data-citation-id="AI-copyright.html.pm-McCann" data-citation-pinpoint="false" data-citation-parenthetical="false" data-citation-judge="false" data-citation-speaker="false" data-citation-signal="false" data-citation-terminal=".">Sancho McCann, “<a href="https://digitalcommons.schulichlaw.dal.ca/cjlt/vol19/iss1/5/">Copyright Throughout a Creative AI Pipeline</a>” (2021) 19 Can JL &amp; Tech 109<span data-short-form-placeholder="AI-copyright.html.pm-McCann"></span>.</span></label></span></span> was just pub­lished by the Canadian Journal of Law &amp; Technology. It is avail­able open-ac­cess <a href="https://digitalcommons.schulichlaw.dal.ca/cjlt/vol19/iss1/5/">here</a>.</p><p>This work is in­creas­ing­ly rel­e­vant as AI tools such as Dall-E, Stable Diffusion, ChatGPT (and oth­er large-lan­guage mod­els—LLMs) are pro­duc­ing ar­guably nov­el out­puts. And the ques­tion of who owns the copy­right to the mod­el weights or pa­ra­me­ters has be­come rel­e­vant giv­en the <a href="https://www.vice.com/en/article/xgwqgw/facebooks-powerful-large-language-model-leaks-online-4chan-llama">leak of the mod­el pa­ra­me­ters be­hind one in­stance of Facebook’s LLaMa</a> (Large Language Model Meta AI). One <a href="https://twitter.com/d_feldman/status/1631761126219292672">Twitter user asks</a>, “Is re­dis­trib­ut­ing the LLaMa weights [] even le­gal? Can copy­right cov­er a big ta­ble of ma­chine gen­er­at­ed num­bers?” I hope this pa­per pro­vides a start­ing point for think­ing about these prob­lems.</p><h3 hyphens="none">Abstract</h3><p>Consider the fol­low­ing fact pat­tern.</p><blockquote><p>Alex paints some orig­i­nal works on can­vas and posts pho­tos of them on­line. Becca down­loads those im­ages and uses them to train an AI (train­ing configures the AI’s mod­el pa­ra­me­ters to use­ful val­ues). Becca posts the re­sult­ing trained pa­ra­me­ter val­ues on her web­site un­der a li­cense that re­serves to Becca the right to use the pa­ra­me­ters com­mer­cial­ly. Cory uses those pa­ra­me­ter val­ues in a pro­gram that is de­signed to pro­duce art­work. Cory clicks cre­ate and the pro­gram pro­duces a work. This work is new to Cory, but it looks a lot like one of Alex’s orig­i­nal can­vas im­ages. Cory sells the work. Advise Cory about their po­ten­tial copy­right li­a­bil­i­ty to Alex (for the sub­stan­tial­ly sim­i­lar work that the pro­gram pro­duced and that Cory sub­se­quent­ly sold) and to Becca (for tak­ing Becca’s pa­ra­me­ters and us­ing them com­mer­cial­ly, con­trary to the li­cense).</p><p>Cory clicks cre­ate again. The pro­gram pro­duces an­oth­er work, this time quite different from any of Alex’s orig­i­nal paint­ings. Cory shares new work on Instagram. Danny copies this im­age from Cory’s Instagram feed and sells a bunch of post­cards that fea­ture that im­age. Advise Danny about their copy­right li­a­bil­i­ty to Cory.</p></blockquote><p>These sce­nar­ios are not as con­trived as they might ini­tial­ly seem. People fre­quent­ly use copy­right­ed works when train­ing an AI (more pre­cise­ly: when train­ing an AI’s pa­ra­me­ters). The re­sult­ing trained pa­ra­me­ters are be­ing shared un­der li­cences that as­sume the pa­ra­me­ters are the sub­ject of copy­right. People do use these pa­ra­me­ters in pro­grams that can pro­duce nov­el con­tent. The re­sult­ing work can be quite sur­pris­ing to the end-user and there are gen­er­al­ly no checks in place to en­sure that the new works do not take too di­rect­ly from the orig­i­nal train­ing data. However, many of the new works will be quite different from any con­tent al­ready in the world. And the end-users of the cre­ative pro­gram of­ten claim copy­right own­er­ship over the re­sult­ing nov­el work.</p><p>I will first present the train­ing and use of a cre­ative pro­gram based on a neur­al net­work, a pop­u­lar mod­el that forms the ba­sis of state-of-the-art cre­ative AIs. Then, I will ex­am­ine each of the is­sues just raised:</p><p>1. Does the per­son man­ag­ing the au­to­mat­ic train­ing of a neur­al net­work’s pa­ra­me­ters ob­tain a copy­right in the re­sult­ing trained pa­ra­me­ters?</p><p>2. Does a per­son us­ing a pro­gram that pro­duces artis­tic out­put ob­tain a copy­right in that out­put?</p><p>3. The au­to­mat­ic train­ing of a neur­al net­work re­quires large amounts of ex­am­ple data (a train­ing set). Can im­ages from around the in­ter­net be copied for the pur­pose of train­ing a neur­al net­work?</p><p>4. What if a per­son uses an AI to pro­duce a work that looks sub­stan­tial­ly sim­i­lar to one of the train­ing ex­am­ples? Is that an in­fringe­ment? And who is in­fring­ing?</p><p>Today’s state-of-the-art “cre­ative” AI tools are based on a tech­nol­o­gy (neur­al net­works) that serve to sep­a­rate the pro­gram­mer and train­er from any of the even­tu­al ex­pres­sion, even the ex­pres­sion stored in the au­to­mat­i­cal­ly-learned net­work pa­ra­me­ters. It would be very rare that a pro­gram­mer or train­er might ob­tain copy­right in the out­put from an au­to­mat­i­cal­ly trained “cre­ative” AI. However, there are a mul­ti­tude of ways to use such an AI to pro­duce out­put, many of which would very well jus­ti­fy award­ing copy­right to the end-user, es­pe­cial­ly when they use the AI as an elab­o­rate brush with which to bring their own ideas to life in ex­pres­sion.</p><p>The cur­rent meth­ods of train­ing these cre­ative AI tools re­quires large amounts of train­ing data: ex­ist­ing works of­ten pro­tect­ed by copy­right. It is un­clear whether Canada’s fair deal­ing user right al­lows for such copy­ing for the pur­pose of train­ing a neur­al net­work, par­tic­u­lar­ly when not for pri­vate pur­pos­es. When a fair deal­ing user right is not avail­able, this copy­ing would be copy­right in­fringe­ment: unau­tho­rized re­pro­duc­tion of ex­ist­ing works. Canada should clar­i­fy or ex­pand the fair deal­ing user right to al­low for such copy­ing.</p><p>Trainers must be care­ful that they have not sim­ply em­bed­ded a rep­re­sen­ta­tion of the train­ing ex­am­ples in the AI. If the AI effectively con­tains “di­rect reflections” of the train­ing data such that it reg­u­lar­ly re­pro­duces them, dis­trib­ut­ing such an AI would be copy­right in­fringe­ment. The train­er has a bur­den to ver­i­fy that they are not dis­trib­ut­ing copies of the train­ing data.</p><p>This analy­sis al­lo­cates copy­right in a man­ner con­sis­tent with a prag­mat­ic con­cep­tion of cre­ativ­i­ty and art. It keeps the fo­cus on hu­man ex­pres­sion and al­lows for free dis­tri­bu­tion of the ma­te­r­i­al need­ed for more peo­ple to have more prac­tice with cre­ative tools while pre­serv­ing pro­tec­tion for orig­i­nal ex­pres­sion.</p><h3 hyphens="none">Acknowledgements</h3><p>I would like to thank Professor Jon Festinger, Q.C., for many help­ful dis­cus­sions while su­per­vis­ing this work and Professor Graham Reynolds for valu­able feed­back on an ear­li­er draft.</p><div class="endnotes print-only"><p><h2 hyphens="none">Notes</h2></p><p class="footnote" id="fn-1">1. <a href="#fn-source-1" class="backlink undecorated"> ↑ </a><span class="bibliography-entry full-form-citation" data-citation-id="AI-copyright.html.pm-McCann" data-citation-pinpoint="false" data-citation-parenthetical="false" data-citation-judge="false" data-citation-speaker="false" data-citation-signal="false" data-citation-terminal=".">Sancho McCann, “<a href="https://digitalcommons.schulichlaw.dal.ca/cjlt/vol19/iss1/5/">Copyright Throughout a Creative AI Pipeline</a>” (2021) 19 Can JL &amp; Tech 109<span data-short-form-placeholder="AI-copyright.html.pm-McCann"></span>.</span></p></div></root>
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25 changes: 25 additions & 0 deletions LICENSE.txt
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This license applies only to the files with `.rkt`, `.p`, or `.pp`
extensions in this repository. To be clear, it does not apply to the
files with `.pm` extensions.

MIT License

Copyright (c) 2018--2019 Sancho McCann

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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