This past Monday’s ruling from the Ninth Circuit Appeals Court in Lenz v. Universal Music Group, a/k/a the Dancing Baby Video case, is being hailed as an important one in establishing the role of fair use in the online world. The case involved a common enough occurrence: a homemade video clip of someone’s child, with music (Prince’s “Let’s Go Crazy”) in the background, posted to YouTube.* UMG sent a takedown notice, Stephanie Lenz sent a counter-notice, and an eight-year legal battle ensued. Monday’s ruling was not a decision on the defendant’s liability but merely a denial of summary judgment, meaning that case will now go to trial.
The three-judge panel produced two important holdings: first, that fair use is really a user’s right, and not just an affirmative defense to a charge of infringement. The second is that copyright holders have to take fair use into account in issuing DMCA takedown notices. As we’ll discuss here, this will have some effect on copyright holders’ ability to use automated means to enforce copyright online.
Under the DMCA (Section 512 of U.S. copyright law), online service providers can avoid copyright liability if they respond to notices requesting that allegedly infringing material be taken down. Notices have to comply with legal requirements, one of which is a good faith belief that the user who put the work up online was not authorized to do so. This court now says that fair use is not merely a defense to a charge of infringement — to be asserted after the copyright holder files a lawsuit — but is actually a form of authorization.
It follows that the copyright holder must profess a good faith belief that the user wasn’t making a fair use of the work in order for a takedown notice to be valid. The court also held that this good faith belief can be “subjective” rather than based on objective facts; but it’s ultimately up to a jury to decide whether it buys the complainant’s basis for its good faith belief.
The question for us here is how this ruling will affect the technologies and automated processes that many copyright owners use to police their works online, often through copyright monitoring services like MarkMonitor, Muso, Friend MTS, Entura, and various others. These services use fingerprinting and other techniques to identify content online, create takedown notices from templates, and send them — many thousands per day — to online services. Page 19 of the Lenz decision contains a hint:
“We note, without passing judgment, that the implementation of computer algorithms appears to be a valid and good faith middle ground for processing a plethora of content while still meeting the DMCA’s requirements to somehow consider fair use. . . . For example, consideration of fair use may be sufficient if copyright holders utilize computer programs that automatically identify for takedown notifications content where: (1) the video track matches the video track of a copyrighted work submitted by a content owner; (2) the audio track matches the audio track of that same copyrighted work; and (3) nearly the entirety . . . is comprised of a single copyrighted work. . . . Copyright holders could then employ [humans] to review the minimal remaining content a computer program does not cull.” (Internal citations and quotation marks omitted.)
At the same time, another clue lies in pp. 31-32, in a footnote to Judge Milan Smith’s partial dissent:
“The majority opinion implies that a copyright holder could form a good faith belief that a work was not a fair use by utilizing computer programs that automatically identify possible infringing content. I agree that such programs may be useful in identifying infringing content. However, the record does not disclose whether these programs are currently capable of analyzing fair use. Section 107 specifically enumerates the factors to be considered in analyzing fair use. These include: ‘the purpose and character of the use, including whether such use is of a commercial nature or is for nonprofit educational purposes’; ‘the nature of the copyrighted work; ‘the amount and substantiality of the portion used in relation to the copyrighted work as a whole’; and ‘the effect of the use upon the potential market for or value of the copyrighted work.’ 17 U.S.C. § 107. For a copyright holder to rely solely on a computer algorithm to form a good faith belief that a work is infringing, that algorithm must be capable of applying the factors enumerated in § 107.”
To follow this ruling, takedown notices will now presumably have to contain language that describes the copyright holder’s good faith belief that the user who posted the file did not have a fair use right. This can be a “subjective” basis, and the source of that information cannot “solely” be a “computer algorithm.”
It is, of course, impossible for any computer algorithm to determine whether a copy of a file was made by fair use; there is no such thing as a “fair use deciding machine.” But that’s not what’s required here — only evidence that some (unspecified portion) of the four fair use factors were not met, other than “because I said so.” Two of the four factors are easy: “the nature of the copyrighted work” ought to be self-evident to the owner of the copyright, and today’s widely-used content recognition tools can determine whether “the amount and substantiality of the portion used” was the entire work. The majority in Lenz suggested that this latter factor “may be sufficient . . . for consideration of fair use.” Apart from that, for example, the fact that a file appears on a website touting “Free MP3 downloads!” and featuring banner ads could be cited as evidence of an “effect of the use upon the potential market for or value of the copyrighted work” or “the purpose and character of the use.”
In other words, some of the characterizations of a work as “not fair use” that are often written into lawsuit complaints (written by lawyers) may have to find their way into takedown notices (generated automatically by technology). As a practical matter, copyright monitoring services may want to produce takedown notices with more situation-specific information in order to pass the non-fair use test — such as characterizations of the online service or other circumstances in which works are found. This could require a greater number of different takedown notice templates and more effort required to populate them with specifics before sending them to online services — yet the processes still ought to be automatable.
The upshot of the Lenz decision, then, is that copyright holders may have to go to somewhat more effort to generated automated takedown notices under the DMCA that will survive a court challenge. Just how much more effort and how much more verbiage in notices is necessary will be a subject for the Lenz trial and future litigations. But today’s basic paradigm of copyright monitoring services using content recognition algorithms and other technological tools to automate enforcement processes is likely to continue, largely unchanged.