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Modern copyright law can't keep pace with thinking machines

Modern copyright law can't keep pace with thinking machines
From Engadget - December 13, 2017

Questions like, "If a human can learn from a copyrighted book, can a machine learn from [it] as well?," Reben recently posited to Engadget. Much of Reben's art, supported by non-profit Stochastic Labs, seeks to raise such conundrums. "Doing something that's provocative and doing something that's public, I think, starts the conversation and gets them going in a place where the general public can start thinking about them," he told Engadget.

To that end, Reben creates projects like Let Us Exaggerate, "an algorithm which creates gobbly-gook art-speak from learning Artforum articles," Synthetic Penmanship, which accurately mimics a person's handwriting, Korible Bibloran, an algorithm that generates new scripture based on its understanding of the Bible and Koran, or Algorithmic Collaboration: Fractal Flame, which blurs the line of creatorship between human and machine.

"I start with a program which generates phrases for me to think about, for example 'obtrusive grass,'" Reben explained. He then thinks about the phrase while an EEG and other sensors record his reactions. That data is then fed into an art generating algorithm to create an image. "The digital version uses IFS fractal generation where the color palette is chosen by the computer from the phrase used in Google image search results," he said, "then displays different versions for me to choose from by measuring my reactions to the images."

New technology running afoul of existing copyright law is nothing new, mind you. "In the 1980s, US Courts of Appeals evaluated who 'authors' images of a videogame that are generated by software in response to a player's input," Ben Sobel, an Affiliate at the Berkman Klein Center for Internet and Society, Harvard University, told Intellectual Property Watch in August. "IP scholars have been writing about how to treat output generated by an artificial intelligence for at least 30 years."

One of the big sticking points between AI and copyright law centers around how these systems are trained, specifically the process machine learning. Most such systems rely on vast quantities of data -- images, text, or audio -- that enable the computer to discover patterns within them. "Well-designed AI systems can automatically tweak their analyzes of patterns in response to new data," Dr. Amanda Levendowski, a clinical teaching fellow at New York University Law School, argues in her forthcoming Washington Law Review study. "Which is why these systems are particularly useful for tasks that reliance on principles that are difficult to explain, such as the organization of adverbs in English, or when coding the program would be impossibly complicated."

Problems arise, however, when the datasets used to train AIs include copyrighted works without the permission of the rightsholder. "This is presumptively copyright infringement unless it's excused by something like fair use," Sobel explained. This is precisely the issue that Google ran into when it launched the Google Books initiative in 2005 and was promptly sued for copyright infringement.

In Authors Guild v. Google, the plaintiff argued that by digitizing and annotating some 20 million titles, the search company had violated the Guild's copyrights. Google countered by arguing its actions were protected under fair use. The case was finally resolved last year when the Supreme Court declined to hear the Guild's appeal, leaving a lower court's ruling in favor of Google standing. "This is often because the uses are what some scholars call 'non-expressive,'" Sobel told IPW. "They analyze facts about works instead of using authors' copyrightable expression."

Things get even stickier when AI is trained to create expressive works, like how Google fed its system 11,000 romance novels to improve the AI's conversational tone. The fear, Sobel explains, is that the subsequent, AI-generated work will supplant the market for the original. "We are concerned about the ways in which particular works are used, how it would affect demand for that work," he said.

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