Tag: Featured

Pass the TikTok Legislation. And then…

TikTok legislation

“At what point then is the approach of danger to be expected? I answer, if it ever reach us, it must spring up amongst us. It cannot come from abroad. If destruction be our lot, we must ourselves be its author and finisher. As a nation of freemen, we must live through all time, or die by suicide.” – Abraham Lincoln, The Lyceum Address, 1838 –

Lincoln’s famous observation that only Americans can truly destroy America speaks to the fragility of the Republic, which the founders knew could only endure so long as the people generally keep faith with certain core principles. Watching those principles assaulted by a far-right populism, which has presently swallowed the Republican Party, it is natural to read Lincoln as prophetic, and it is hard to imagine any foreign influence being more dangerous. On the other hand, when Lincoln said, “It cannot come from abroad,” he could hardly have imagined a time when 170 million young Americans would carry a pocket surveillance device loaded with software under the control of a foreign adversary.

Following the 362-55 vote by the House to force TikTok to divest itself of all ties to the Chinese Communist Party (CCP), opinions about the bill question both its necessity and viability—though not with good reason. Although rashly described as a “ban,” the effect of H.R. 7521 would force a sale of the platform by parent company ByteDance to an owner without ties to the CCP. To that end, I agree with independent musician Blake Morgan. who endorses the TikTok legislation, both as a national security and anti-piracy measure. In an editorial for IP Watchdog, Morgan writes:

The vast majority of music on TikTok generates virtually no revenue for the musicians who made it, and even more music on the platform is completely unlicensed (stolen), copied (stolen via AI), or pirated (stolen). Simply put, TikTok is trying to build a music-based business without paying music makers fair value for the music. That’s why Universal Music Group has already pulled out of TikTok. That’s why the National Music Publishers’ Association has already announced it won’t renew its license with the company. So, TikTok poses “a clear and present danger” to American music, too.

The music piracy alone is reason to force the platform to operate within the reach of U.S. law, but with regard to the national security threat, it is notable that unless one is in the intelligence community, or a Member of Congress receiving a security briefing, we are left to rely upon one of those core principles, which have been eroded by social media in general:  trust. I do not endorse the Whatabouist’s view that just because TikTok is not alone in causing havoc that this legislation is moot, but the story does highlight those hazards of social media that make it difficult to convince many Americans that TikTok is a threat of any kind.

Joseph V. Amodio, writing for Tanium, states that TikTok is distinguishable from other platforms thus:

TikTok stands out in its power to manipulate: While videos from any app can go viral, TikTok’s infection ability is unique, given the practice of “heating,”  where TikTok staff can supercharge distribution of hand-picked videos. This has huge implications for fair competition and free trade. Just imagine how they can siphon profits by amplifying your competitors’ posts or cooling down your own viral campaigns.

Whether the goal of data manipulation is to pull the levers on enterprise, as Amodio indicates, or to influence young voters on policy matters, how does one convince nearly 200 million 18 – 29-year-olds that said manipulation is both occurring and should be seen as an attack? If an act of cyberwarfare entails hacking the Pentagon or shutting down part of the power grid, enough Americans can probably recognize such events as attacks in a traditional sense. Likewise, the prospect of malicious software injected into millions of mobile devices might be understood as a threat.

But what if the weapon is an insidious propaganda tool used to manipulate the opinions of millions of citizens? Who is going to be trusted to identify that as a sustained attack on the United States? Some portion of the TikTok demographic will not believe that China (or Russia) is an adversary in the first place, which is arguably evidence itself of social media’s power to influence.

Even if the delivery platform is owned by Meta serving “ads” purchased by foreign operatives with the same objective to sow discord, no individual wants to believe he’s being manipulated. More complexly, even if one tries to apply critical thinking, the effort itself is often countered by teams of data manipulators flooding the zone—i.e. the illusion of more “information” tilting bias in one direction or another. This was true before parties like China and Russia upped their cyber game and before they could add artificial intelligence to the toolset.

As a practical example at the heart of the TikTok story, how does the moderate, who would rather not hyper-politicize national security, take the contemporary Republican seriously in his professed opposition to TikTok’s capacity to “manipulate” Americans? For instance, Rep. Ralph Norman of South Carolina writes, “…if you’ve spent 5 minutes exploring TikTok, you should have recognized the addictive nature of this platform. It is designed for one purpose: to control your attention. Their algorithm quickly figures out what kind of videos you’re likely to watch, and then feed you similar videos to keep you fixated.”

Fine. But one could swap “TikTok for “Trump” and make the same general argument, including that his self-interested rhetoric about NATO, disrespect for the Constitution, etc. all comprise a threat to national security. What would Lincoln say to his legacy party about this tangled interplay between foreign and domestic forces, both hostile to American interests, and both weaponizing disinformation through addictive and manipulative platforms?

In this context, it is important to note that Trumpism is a symptom of populism—a trend that is no less prevalent on the left than on the right, perhaps especially among 18 – 29-year-olds. The difference, for the moment, is that the left has not found its own cult-like figure, who might also undermine core principles, albeit in a different style than Trump. The rise in populism in the U.S. and other democracies is a direct result of social media’s nature to factionalize hearts and minds, which is precisely what a foreign adversary wants to achieve. TikTok may be a shrewdly named time-bomb delivered to over half the U.S. population and, as such, should be diffused. But assuming that task can be accomplished, the existential question remains as to whether we can quarantine the most virulent effects of all social platforms or “die by suicide.”

Decoder podcast: AI could go extinct because fair use is whimsical

AI extinction

It was hard not to dismiss the headline posted by The Verge:  How AI copyright lawsuits could make the whole industry go extinct. The article summarizes a new Decoder podcast hosted by Nilay Patel, joined by Sarah Jeong to discuss the copyright lawsuits filed against generative AI developers. Most of the program is devoted to a discussion of fair use, which is reasonable because that’s likely how these cases will be decided. It’s clear that Patel and Jeong view copyright as a barrier to technological innovation, but when people trained in the law misrepresent the law as purely whimsical, it is counterproductive to the conversation.

I could critique nearly every segment in the podcast, but as that would be both long and tedious, I selected a few highlights for this post. Setting the more-hip-than-helpful tone of the program, Patel (who went to law school) describes fair use as a “vibes based” doctrine. Jeong (also law school) echoes the sentiment when she says that litigation against generative AI has “Napster vibes to it,” teeing up her thesis statement: “When Napster happened to the law, companies went bust; entire industries went bust; copyright changed forever in a way that was not great; it was an extinction level event; and AI has a similar thing going on there.” Here, Patel summarizes that Napster went to the Supreme Court—it did not—and that the Court “made some changes to copyright law.” Seriously? “Made some changes” is not how people with legal training talk about court rulings, even when they disagree with the outcome.

The next comment that caught my attention was Patel saying that “fair use is not deterministic” as a doctrine. He’s right, but in context, the listener will take him to mean that fair use is unpredictable to the point of capriciousness. Although a good attorney will demur to predict the outcome of any case, a thoughtful copyright expert is unlikely to agree that fair use findings are a “coin toss,” as Patel puts it. In fact, the choice of the word deterministic provokes the rebuttal that anticipating a fair use outcome is more accurately described as probabilistic, which is funny because that’s also how generative AI works.

If a defendant asks an attorney to handicap the likelihood of prevailing on fair use, the attorney’s response should be a reasonable prediction based on how closely the facts of the present case resemble fair use findings in the circuit of jurisdiction. Although Patel alludes to this analysis, he overlooks the fact that counsel could describe a probability outcome, which is precisely how a generative AI produces its outputs. If one prompts a visual AI to generate an image of a dolphin drinking a Slurpee, the output is the machine saying, “Based on the available data, this image is probably a dolphin drinking a Slurpee.” So, of all defendants, AI developers should grasp the nature of fair use case law.

Jeong echoes the idea that fair use considerations are erratic by alleging that the “Court changed copyright law after Napster,” referring to the Ninth Circuit’s 2001 finding that the P2P music filesharing platform was not shielded by fair use. Here, she argues that the Supreme Court’s fair use finding in the Sony “Betamax” case (1984) expressed a philosophical adaptation of copyright law to foster new technology but that this general view was reversed when the Ninth Circuit decided against Napster—and then when the Supreme Court ruled in 2005 that the filesharing platform Grokster could be liable for copyright infringement.

Although one cannot reasonably argue that ideology never skews the courts, Jeong elides the many factual and legal distinctions between the VCR and filesharing platforms and, by extension, the distinctions between those technologies and generative AI. Her declaration that “copyright was changed” after Napster and Grokster is unfounded, as the Court itself notes that Grokster was its second case considering contributory liability for copyright infringement—Sony being the first. Two cases, twenty-one years apart, addressing the same legal question presented by substantially different technologies is not a basis for claiming that the law was “changed forever” by the outcome in the latter case.

Holding the opinion that copyright stifles technological innovation does not excuse misrepresenting the courts as rolling dice to rule on fair use. For instance, in Grokster, the Court directly addresses the balance between copyright and technological innovation thus:

The more artistic protection is favored, the more technological innovation may be discouraged; the administration of copyright law is an exercise in managing the trade-off….The tension between the two values is the subject of this case, with its claim that digital distribution of copyrighted material threatens copyright holders as never before, because every copy is identical to the original, copying is easy, and many people (especially the young) use filesharing software to download copyrighted works.

Does that describe the technological function of the VCR? For those who’ve never used a VCR, the answer is No. The home video tape recorder, a relic of pre-internet life, functioned nothing like a filesharing platform, which facilitates mass copyright infringement on a global scale. Fair use is a fact-intensive inquiry, and “technology” is not a monolith. The leap from the VCR to generative AI is roughly the distance between the telegraph and the iPhone, and it is unhelpful, even irresponsible, to obscure so much factual detail behind a conversation about the courts’ alleged randomness on copyright and fair use.

Everything cited above was expressed in the first 5-6 minutes of the podcast. Tempted not to listen any further, I winced as both Patel and Jeong proceeded to make some astonishing remarks about the four-factor fair use test in regard to generative AI. Again, a couple of highlights stand out.

On factor two, nature of the work used, Patel says, “Factor two is whatever the judge thinks it is.” Then, a few seconds later, he says, “If the judge decides they don’t like the New York Times that day…” this will determine whether factor two tilts in the Times’s favor. NYT v. Open AI is before the Southern District of New York in the Second Circuit, which holds the largest trove of copyright case law of any circuit in the country—including several major fair use cases. If Patel or Jeong want to handicap the court’s findings based on that case law and then offer their own views of what they think is right, fine. But the implication that the court is just going to wing it is ridiculous.

Jeong does not push back on Patel’s coin-toss implication but says the “dial is in the middle” on factor two, which she reasonably (if not very clearly) argues because the Times contains both protectable expression and unprotectable factual material. But then comes the biggest spit-take in the program, when Jeong predicts that factor four, potential market harm to the work used, weighs against the AI developers because of the Supreme Court decision in Warhol. She states, “We have not seen that heavy an emphasis on factor four before.” Notwithstanding the fact that prior to the Campbell decision (1994), many experts would say that factor four was the most determinative factor in fair use jurisprudence, Warhol was unequivocally NOT a factor four case. As the opinion states:

In this Court, the sole question presented is whether the first fair use factor, “the purpose and character of the use, including whether such use is of a commercial nature or is for nonprofit educational purposes,” §107(1), weighs in favor of AWF’s recent commercial licensing to Condé Nast. [emphasis added]

From her comments about Warhol, Jeong confuses the question of “substitutional purpose” with the question of “market harm substitution,” which are weighed under factors one and four respectively. It is true that where the court finds substitutional purpose, market harm substitution is more likely to be found, but as the opinion explains the distinction in one footnote in Warhol:  While the first factor considers whether and to what extent an original work and secondary use have substitutable purposes, the fourth factor focuses on actual or potential market substitution. They are two separate, albeit interdependent, questions. I do not know whence Jeong gets the idea that Warhol was a factor four case, let alone an unprecedented outcome in its emphasis of that factor.

Fair Use is a Fact-Intensive Inquiry

Generalizations like those articulated in the Decoder podcast sidestep the relevant facts about a given technology, what it does in context to legal questions, and why the technology may or may not be socially valuable. “Artificial intelligence” encompasses a wide range of development, some of which is promising, some of which is questionable, and all of which has been identified as potentially dangerous without proper oversight. As for generative AI in the creative industries, if Jeong is right that the copyright lawsuits pose an existential threat to those companies, so what? It is not clear that the world needs machines to make images of dolphins drinking Slurpees.

As discussed in this post, AI developers may have taken a gambler’s approach to fair use, and if their business plan included liability at the scale of mass copyright infringement, that’s a risk they chose to take. If any of those companies fail because of that liability, it will not be the result of whimsically applied or tech-hostile copyright law, or indeed the fault of the creators whose rights are infringed in the process of machine learning. Moreover, it is certainly not incumbent upon creators to abdicate their rights and get out of the way because “innovation” is happening. Fair use considerations in generative AI lawsuits may result in some novel opinions, but if influencers like Patel and Jeong are going to misstate case law and describe the courts as casinos, then one must wonder why they mention their legal credentials in the first place. After all, anyone can flip a coin.

Stop Democratizing Everything!

democratizing

On March 17, Rolling Stone published an article featuring a song called “Soul of the Machine.” Sounding like blues of the early 20th century, the “voice” sings the lyric, “I’m just a soul trapped inside this circuitry.” Naturally, the whole work—music, lyrics, guitar playing, and singing—was produced by artificial intelligence. As writer Brian Hiatt describes, a simple prompt, “solo acoustic Mississippi Delta blues about a sad AI” produced the song after a fifteen-second collaboration—music and performance by Suno with lyrics by ChatGPT. Yes, it’s a “Holy shit” result with a million implications, but it was this paragraph about Suno’s co-founder that inspired today’s response:

Suno appears to be cracking the code to AI music, and its founders’ ambitions are nearly limitless — they imagine a world of wildly democratized music making. The most vocal of the co-founders, Mikey Shulman, a boyishly charming, backpack-toting 37-year-old with a Harvard Ph.D. in physics, envisions a billion people worldwide paying 10 bucks a month to create songs with Suno. The fact that music listeners so vastly outnumber music-makers at the moment is “so lopsided,” he argues, seeing Suno as poised to fix that perceived imbalance.

At some point—and I think it’s the point on top of most technologists’ heads—the word democratization became a handy euphemism for destruction. Social platforms “democratized information,” and we’re drowning in disinformation. Streaming platforms “democratized distribution” for creators and decimated royalties. And now, generative AI developers want to “democratize creative production” with the snake-oil pitch that everyone can be a painter, musician, filmmaker, poet, etc., as if art is something to heat up in the microwave like a quick (if not good) meal.

The first rule of economics is that abundance lowers value, and this does not only apply to price but also to those esoteric values we ascribe to the artistic works that attain meaning for us. In Shulman’s view, Bob the electrician would “make” his own big band music while Sally the paralegal would “make” her own Reggae, and if we multiply that to the scale Shulman projects above, then a billion people can “make” music about which a billion people do not give a damn. Consequently, as argued in this post in January 2023, the inevitable outcome of this entire enterprise is widespread boredom.

It is not possible to “democratize” the production of art in the way Shulman envisions because the individual who types a few words into an AI to produce a “new” song will never experience anything close to the process of making music. As described by Hiatt, the “production” of “Soul of the Machine” is the equivalent of saying, “I’m in the mood to listen to Mississippi Delta blues,” which describes how most of us decide what to play at a given moment. But that’s not making music, it will never feel like making music, and few people will ever feel otherwise.

I can’t play guitar for shit, but because I am a human being composed of human parts, I sense the extraordinary degrees of difference between listening to Mark Knopfler and trying to force my lame-ass fingers to make those sounds. As such, it would take a traumatic brain injury for me to be deluded enough to feel like typing a prompt to direct a machine to play a Knopfler-like solo was somehow an accomplishment in this regard. Artistic works need to be special, and whatever makes them special also needs to be a shared human experience for the work to matter. Lacking these ingredients, “art” produced by a machine is just a Hot Pocket in the microwave.

When I first jumped into this fray, EVERYBODY on the anti-copyright side was preaching to creators that they need to forget about “old models” built on sales and royalties and instead embrace online platforms to “connect to their fans.” Follow this new doctrine, they insisted, and fans will reward them as a courtesy rather than be forced to pay “rent” by a government-imposed monopoly called copyright. Yes, it was multi-dimensional bullshit ten years ago, other than the fact that certain creators could, and can, connect with fans in novel ways. But now, the same class of tech-bros, heavily invested in generative AI, propose to wipe out that connection with the new promise that today’s fans are tomorrow’s artists.

I get how Suno makes a good pitch. An addressable market of a billion people paying ten bucks a month is going to get VC attention. But like all utopian “visionaries,” generative AI developers’ dreams of “democratizing” creative production forget to consider human nature, without which art is meaningless. After the initial gee-whiz factor wears off, the music or writing or painting itself all amounts to a big Who cares? “Soul of the Machine” is an impressive, eerie accomplishment in computer science—one that will doubtless have applications—but if we proposed to send a new Voyager mission beyond the solar system with a new gold disk telling a human story, Blind Willie Johnson would still belong, and not some probability outcome produced by a generative AI.

Meanwhile, I still wonder whether the model itself might crash as its own self-training approaches a state akin to consciousness. The lyric about being trapped inside the circuitry is satire for humans that reprises a question I’ve asked before—namely whether an AI might attain semi-consciousness and begin to produce what it perceives as “art.” Specifically, the question is whether the AI might ever “understand” its nature and then make expressions about the “machine condition” rather than randomly produce ersatz expressions about the “human condition.”

While I am told by some technologists that this idea of near consciousness remains in the realm of science fiction, my own bias still predicts that if the AI could ever ask itself why it should produce art, it probably won’t. Or if it does, it will be in the form of expressions that we would not understand—or perhaps even know exist. So, even if Shulman’s “boyishly charming” vision were achieved at some scale, I predict it will start to suck, and suck fast. Then, like a reverse Fahrenheit 451, as the over-abundance of bespoke music threatens to burn the old catalogs out of living memory, people will “rediscover” the real thing, and the proverbial children in the woods will know the difference.

Photo by: Talulla