AI Copyright Aff - Emory 2024

Aff – AI Copyright – ENDI ‘24
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Inherency---1AC
Existing regulations grant AI developers unlimited access to copyrighted material. New legislation is necessary to protect creators.
Hannah Algar 24. Writer about developments in technology and AI. "Why copyright law is failing to protect content right holders against generative AI". AI Journal. 2-16-2024. https://aijourn.com/why-copyright-law-is-failing-to-protect-content-right-holders-against-generative-ai/
The fair use clause
The second limitation of the DMCA is that its fair use clause has given AI developers a legal loophole to justify the unlimited and unauthorised use of copyright protected content for generative AI training. This clause provides exemption from the content right holder’s exclusive right to distribute their work according to how well the repurposing of the content meets the following criteria:
Whether the repurposing of the content is for non-profit and educational use.
If the copyrighted content is of a more factual or imaginative nature.
How much of the content is used, and the significance of this portion within the original work.
The impact of the original content’s unauthorized use on its potential market value.
Ian Crosby, US attorney at Susman Godfrey LLP, defines the fair use clause as a way of ‘balancing the value of the new technology to society in general with the cost to the people who are being used to create it’, as part of his discussion on generative AI in a webinar from the Digital Media Licensing Agency.
Now acting as lead counsel for the New York Times in their lawsuit against OpenAI and Microsoft, Crosby has asserted that the tech companies’ use of the news outlet’s content does not constitute ‘fair use by any measure’, in a comment sent to The Verge.
However, this opinion may be in the minority, at least within the tech community, with a poll by the AI Journal finding that 32% of respondents supported OpenAI vs only 19% who supported the New York Times in this lawsuit. This is likely due to widespread recognition of AI models’ reliance on vast amounts of data and the vast potential that AI has to transform industries, solve global crises, and assist humans in their day-to-day lives.
In copyright lawsuits, the plaintiffs are claiming that there is significant cost to the content creators whose work is being used to fuel generative AI, with the New York Times lawsuit demanding reparations of ‘billions of dollars in statutory and actual damages’.
However, concrete proof of the financial loss caused by AI’s use of content is hard to come by, and is typically just speculative. For this reason, the fair use clause of the DMCA is likely to work in the favour of AI developers, who can further strengthen their defence by illustrating several non-for-profit and educational uses of generative AI.
This has recently played out in a California court’s partial dismissal of the lawsuit filed by Sarah Silverman and other authors against OpenAI. Out of six allegations they made, including unfair competition and unjust enrichment, the judge threw out all claims except direct copyright infringement, as per OpenAI’s request. The case will therefore rest on whether or not will depend on whether Silverman et al. can prove that any of ChatGPT’s outputs have reproduced their writing verbatim.
Conclusion
The DMCA does not account for the wider implications of AI’s use of human produced content, and how this could threaten the stability of creative industries in the future. A review of the DMCA by the Senate Subcommittee on Intellectual Property back in 2020 highlighted the need to ensure that the DMCA’s prerogative was not to serve companies as much as individual users such as artists and writers. With the fair use clause providing tech companies with a legal loophole for their use of writers and artists’ content, this priority seems to have been lost amidst the hype of generative AI and the perceived importance of its technology to the future of the humanity.
Overall, the shortcoming of the DMCA in addressing the bigger picture that is at stake in copyright lawsuits is putting pressure on policymakers to evaluate the potential need for revised legislation in clarifying the future relationship between generative AI and its sources, and ensuring that the needs of content creators do not go ignored.
Thus, the plan: the United States federal government should require licensing for generative artificial intelligence that trains on copyrighted material.
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AI is an existential crisis for news media. Only strengthening copyright law can save the industry.
Lucas Ropek 24. Staff Writer at Gizmodo. "Congress: Maybe We Shouldn't Let AI Destroy the News Media". 1-13-2024. https://gizmodo.com/openai-new-york-times-congress-chatgpt-conde-nast-rabbi-1851160779
Last year, after Buzzfeed laid off its entire newsroom and made a pronounced pivot to AI-generated content, I made the argument that journalists should treat the technology as an existential threat. It seemed clear that companies like OpenAI were creating content-generating algorithms that could be used to compete with traditional (read: human) reporters. I added the qualification that I might, potentially, be indulging in alarmism. It was early days and, just because it seemed like AI could prove a big problem for the news industry, that didn’t mean that things would necessarily pan out that way.
Since then, however, nothing has particularly happened to soften my stance. More and more, it seems like the journalism industry is under threat from a technology that is intent on using content created by humans to replace them.
Thankfully, it seems like Congress is finally on the same page. This week, the US Senate Judiciary Committee held a hearing dubbed “Oversight of A.I.: The Future of Journalism.” It was chaired by Sen. Richard Blumenthal (D-Connecticut), and gave representatives from media companies the opportunity to speak about the potential harms that AI was doing to their industry. Blumenthal described AI as an “existential crisis” for the news media and spoke of the need to swiftly address the harms it could cause: “We need to move more quickly than we did on social media and learn from our mistakes in the delay there,” he said.
Wednesday’s speakers included Roger Lynch, the CEO of Condé Nast, who gave one of the better defenses of the role that actual, non-AI humans should play in the journalism industry. Lynch said:
I personally enjoy leading companies through times of great technological change. Generative AI (Gen AI) is certainly bringing about change and is already demonstrating tremendous potential to make the world a better place. But Gen AI cannot replace journalism. It takes reporters with grit, integrity, ambition and human creativity to develop the stories that allow free markets, free speech, and freedom itself to thrive...
Unfortunately, current Gen AI tools have been built with stolen goods. Gen AI companies copy and display our content without permission or compensation in order to build massive commercial businesses that directly compete with us. Such use violates copyright law and threatens the continued production of high-quality media content. These companies argue that their machines are just “learning” from our content just as humans learn, and that no licenses are required for that. But Gen AI models do not learn like humans do. There are many examples where the Chatbots display content plainly derived from the works they ingest. In effect, they are mashing up copies at enormous scale and speed.
At the end of the day, the committee largely seemed amenable to passing laws that would force AI companies to license content that they use to train their algorithms. This would force those companies to enter into bartering arrangements with media companies, instead of simply stealing their material.
The New York Times recently sued OpenAI, accusing the company of violating copyright law by using its material to train GPT-4, the LLM that powers the company’s popular chatbot, ChatGPT. Legal experts contend that the Times’ lawsuit is one of the strongest attacks yet on the AI industry’s “fair use” doctrine when it comes to algorithm-training material. In response to the Times’ lawsuit, OpenAI released a statement, referring to it as “without merit.”
The truth is that the news media already had a strained and not altogether healthy relationship with the tech industry before AI came along. Over the past two decades, tech companies have sucked up a vast majority of the ad revenue that formerly went to news organizations. This trend has drastically reshaped the media economy and helped to hollow out what was once a vibrant and diverse news industry.
In recent times, some governments have attempted to level the playing field by imposing profit-sharing agreements between tech companies and the media. Companies like Facebook, obviously aware of how much money they’d be losing by acquiescing to those agreements, have opted to play hardball with regulators. This is why you can’t read news on Facebook in Canada anymore.
Now, as outlets scrimp and scrape to get by, a new breed of tech companies is basically threatening to deliver a killing blow. If the AI companies get their way, every piece of web content—whether it’s a painting, a blog, a recent novel, or a 4,000 word exposé from the New York Times—will be fodder for algorithms that are being openly marketed as an “efficient” way to replace many of the human creators behind those original works. Do we really want to live in a world where that’s the case?
AI’s backers have largely framed it as a technological leap forward so profound that there is little that anyone can do but get out of its way. It is true that technological shifts do occasionally occur that are so momentous that they are largely beyond the average, everyday person’s control. But that’s not the case here. The question of copyright law is very much under our control. Congress can make a decision that responsibly protects the Fourth Estate and creates new legal precedents that force tech companies to pay for the data they use when training their algorithms. If paying for content makes the AI industry unsustainable well, frankly, that’s just too damn bad. One thing is clear: America needs the New York Times a whole lot more than it needs ChatGPT.
Otherwise, journalism will collapse, which crushes democracy and access to reliable information.
Courtney C. Radsch 24. Ph.D. in international relations from American University, Nonresident Fellow in Governance Studies at the Brookings Center for Technology Innovation; and Director at the Center for Journalism and Liberty at the Open Markets Institute. "Can journalism survive AI?". Brookings. 3-25-2024. https://www.brookings.edu/articles/can-journalism-survive-ai/
Can journalism survive artificial intelligence (AI)? The answer will depend on whether journalism can adapt its business models to the AI era. If policymakers intervene to correct market imbalances, they must enforce intellectual property rights and ensure that journalism has a fighting chance in the era of generative AI.
Over the past nearly two decades, as tech companies like Apple, Amazon, Google, Meta, and Microsoft grew to become some of the most valuable companies in the world, the United States lost a third of its newspapers and two-thirds of its newspaper journalists. They cannot be replaced with AI.
Last year alone, the U.S. journalism industry slashed 2,700 jobs, and 2.5 newspapers closed each week on average. Despite a 43% rise in traffic to the top 46 news sites over the past decade, their revenues declined 56%. The dominance of less than a handful of privately owned, Silicon Valley-based tech corporations over digital advertising, publishing, audience, data, cloud, and search decimated the business models of journalism worldwide. And now AI is doing it again.
But unlike journalists, AI can not go into the courtroom or interview a defendant behind bars, meet with the grieving parents of the latest school shooting victim, cultivate the trust of a whistleblower, or brave the frontlines of the latest war. Furthermore, without access to human-created, high-quality content that is a relatively accurate portrayal of reality—and that journalism provides—the foundational models that fuel machine learning and generative AI applications of all types will malfunction, degrade, and potentially even collapse, putting the entire system at risk.
The rapid advances in artificial intelligence are becoming yet another way for a handful of powerful tech corporations to extend and entrench their already dominant market positions. This will make it difficult, if not impossible, for sectors like journalism or the creative industries to remain independent, much less to maintain a public interest orientation as should be the case for the news industry.
The AI revolution underway extends the “platformization” of journalism and the power that a handful of tech firms maintain over our information channels and our public discourse. This, in turn, will exacerbate the ways in which these corporations are already threatening and cheapening real journalism while exploiting the labor of millions of journalists and others to build their models and develop applications that alter our economies and societies.
Journalism is particularly valuable to generative AI search, where it provides real-time information, context, fact-checking, and human language. This is where journalism, including local journalism, could be particularly valuable and thus must be able to monetize. Searching for information about local businesses, community issues, or government is going to be lot less useful if there is no local journalism informing the results. Similarly, journalism that focuses on niche topics, breaking news, and investigative reporting are also likely to be especially valuable to applications that want to provide up-to-date, relevant, and timely information to their users while fighting the scourge of misinformation and low-quality content online.
Publishers are deeply concerned about how AI will further exacerbate the trend toward zero-click searches, which display the information requested without sending a user to an actual news site. They have been on a steady upward trend since 2019. A 2022 study found that half of all Google generative AI searches were zero-click and just a tiny fraction of Facebook users click through on the content in their newsfeeds.
Equally distressing is the way that AI companies are building their systems on the widescale theft of intellectual property and uncompensated use of journalistic content, which is far more than just a collection of facts and is often collected at great costs to the journalists who report the news. Journalism is an essential part of many of the foundational data sets used to develop and train generative artificial intelligence systems. News makes up half of the top 10 sites in the training data of a Google dataset that is used to train some of the most popular large language models (LLMs), and accounts for nearly half of the top 25 most represented sites in the Colossal Clean Crawled Corpus, a snapshot of the open source Common Crawl dataset filtered to retain high-quality English sources and discard low-quality and problematic content like profanity and hate speech.
Even content that was put behind paywalls and intended to be restricted to paid users is present in LLMs and recycled in generated responses. Last year, ChatGPT and Bing had to stop a new product partnership because users were able to bypass publisher paywalls. More than half of 1,159 publishers surveyed have requested AI web crawlers to stop scanning their sites, though compliance is voluntary and can be ignored with impunity.
If AI companies are allowed to further cannibalize content and revenue from the journalism industry, as has been the case with search and social media, they will divert readers and potential subscribers away from publishers. This further reduces revenues that could be earned from subscription, advertising, licensing, and affiliates, undermining not just the ability to produce quality journalism but also the underlying business models for the entire sector.
Luckily, despite protestations that freely using journalism to develop foundation models and fuel generative AI applications like search and content generation is fair use, AI companies have already started to strike deals with news publishers for access to their content. OpenAI, which is substantially owned by Microsoft, has inked licensing agreements with some of the largest journalism organizations in the world including the Associated Press, Axel Springer, Le Monde, and Spanish media conglomerate Prisa, while several more are reportedly in discussion with Apple and Google. Although the terms are largely unknown, many of them appear to cover licensing content, including archives, for a defined period (two years seems to be the norm) as well as access to AI tools in the newsrooms.
But smaller, niche, minority, investigative, and local media are being left behind, in part because they don’t necessarily understand the value proposition of their journalism throughout the AI value chain, the resources and sway to seek out deals, or the power to negotiate effectively.
How we decide to allocate intellectual property rights and how we decide on whether fair use applies to developing and training artificial intelligence systems will have profound ramifications. This is where efforts to require tech platforms to negotiate with news publishers and allow publishers to collectively bargain for use of their content could be particularly helpful.
News media bargaining codes, which are already in place in Australia and Canada and under consideration in a dozen more jurisdictions including the United States and several states, were initially seen as a way to require fair compensation for the value that news snippets provide to Google Search and Meta’s social media platforms. But they could, and should, be used to demand compensation for the scraping and crawling of content for AI systems as well, as I told the California Senate, Canadian Parliament, and South African Competition Commission in hearings held over the past few months.
The erosion of the media makes polarization inevitable. This erodes epistemic commons and renders societies unable to respond to existential risks.
Daniel Schmachtenberger 21. Founding member of The Consilience Project, researcher at Civilization Emerging, “It's a MAD Information War,” Consilience Project, 7-25-2021, https://consilienceproject.org/its-a-mad-information-war/
Can humanity survive digitally enhanced psychological warfare?
No matter where you live, if you are on the Internet you are in a war zone. You may not feel the terror of bombs dropping around you, nor the horrors of physical violence, but there is war nonetheless. For as long as humans have fought, military tactics have always involved propaganda, information manipulation, and deception. Today, digital communication technologies have changed the landscape of what the U.S. military calls “irregular warfare.”[1] As opposed to “conventional warfare,” this kind of war is not primarily about the use of physical force, and it is not primarily about targeting an adversary’s military assets. Irregular warfare includes economic warfare (sanctions), cyber warfare (attacks within the digital domain), and political warfare (diplomacy), but it most pervasively manifests as some version of population-centric information and narrative warfare. The goal is the same as conventional war: to acquire by coercive means some political or strategic good, such as economic, geographical, or military advantage. In this kind of war, the mind of every citizen is a potential target, and tactical victories could include a delegitimized ele

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