| Elena Razlogova on Fri, 28 Oct 2022 09:58:12 +0200 (CEST) |
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| Re: <nettime> Thoughts on Stable Diffusion and Free Culture |
Common Crawl captures the spirit of free culture. In its launch in 2011, Lisa Green, director of the nonprofit 501(c)(3) organization, announced “It is crucial [in] our information-based society that Web crawl data be open and accessible to anyone who desires to utilize it”. Carl Malamud, a 2022 Internet Archive Hero Award, serves on Common Crawl’s board further stressing Common Crawl’s roots in a free culture movement embracing the internet as an information commons and advocating for the protection of the public domain.
Strange then that Common Crawl is behind our intense moment of financial speculation around artificial intelligence, the foundation of the highly-concentrated market of AI firms. Common Crawl provides the training data for the biggest names in AI today, Open AI’s GPT-3 and Stable Diffusion. Its crawls of the internet, its efforts to make the Internet available to anyone, have been embraced by an open source AI movement.
I want to focus on this paradox between free culture and commercial AI as the later’s success marks the former’s diminish. If all that free culture does is feed a new round of venture capitalism, an aggressive automation of arts and culture, and a negation of digital life as anything other than data, then free culture is no more. Just another cheap data source.
The decline has been a long time coming. Darin Barney, two decades ago, warned that the Internet could become a standing reserve of bits, another way of describing the mantra that data is the new oil. Barney’s warning was to others a site of political struggle, to resist what we once called the digital enclosures and to let the Internet become a third-way. Free culture and free software were movements that joined technical and political innovation. What has becoming striking after the commercialization of free software as open source and the depoliticization of piracy is that now Common Crawl marks the end of free culture as a viable tactic as well.
What is Open Source AI
Stable Diffusion and other “open source” AI movement restate the commons as a business practice. The roots of the movement might just as well be seen in the AI Commons movement. The AI Commons is a movement, part of AI4Good, but one that marked a clear sense of how information commons and commercial AI could be completely complimentary. The AI Commons marked an important shift in commercial technology firms moving from private code to public code, from private data to public data that in turn moved these idea from critique to opportunity.
That the commons could be a business model is at the core of the paradox marking the demise of free culture. Where once free culture marked a rebuttal of information feudalism or what Rebecca Giblin and Cory Doctorow call chokepoint capitalism, what I find is that market valuations depend on free culture. From Microsoft’s new Autopilot for GitHub that turns GPL and other free licenses into training data to write new code to GPT-3 and Stable Diffusion that rely on Common Crawls to create its text and image generation tools.
Openness and free culture have allowed and legitimated a new round of AI start-ups claiming to be a continuation of the open source movement. Emad Mostaque, the founder of Stability AI, explained how openness is behind the ethics of Stable Diffusion to the New York Times, “Who is responsible for AI? Who is responsible for the output of AI? And how can we make sure that it’s open and positive? But I don’t think that happens if the only debate that happens is behind closed doors and big technology companies.” By a strict reading of open source and the creative commons these companies seem a success story.
Perhaps we might call this moment, optimistically, late-stage capitalist Internet as an attempt for scholar to periodize early political approaches to computing and to acknowledge a near total imbrication of technology and capitalism at work online. The term for me is a response at least to Chris Kelty’s reflections of the end of free software and open source as a mode of politics. I have always been haunted by this line, “There is no free software. And the problem it solved is yet with us”. Kelty’s conclusion remains an enduring provocation to reimagine, for me at least, to reimagine the early pirate politics and free/libre software movements undone by their internal politics but kinds of critiques we remain in need of.
After Free Culture?
The paradox then becomes productive because we need to define what specifically about open source AI negates free culture and what needs to be done?
The immediate point, one well articulated in the The First Nations Principles of OCAP, is that public and open can be quite contradictory where openness negates the relations to the community and the public. How immediately might companies using the commons be held to account, not unlike how the GPL once expected code derived from the commons to return to the commons.
There is another easy leap toward solidarity -- such as Google Walkouts over Project Maven -- that reflects on AI’s applications. Where the Google Walkouts demonstrated a refusal to work on military AI similiar movements need to question why AI continues to be what Solon Barocas calls a co-opting machine. How is it that the greatest advances in AI seemingly undermine creative labour, one of the last fronts in an overall de-skilling of labours following Astra Taylor’s precinct observations in the The People’s Platform.
The commons itself is also increasingly contentious as an institution. Anna Tsing’s latent commons or Fred Moten and Stefano Harney’s undercommons question the very being of the commons as a stable form, or as a definite space clearly at odds with the Creative Commons movement responsible for Common Crawl. These critiques of the commons point at an advantage in ambiguity, though I worry that the uneven application of copyright and the law continues to advantage forms over others. Corporate piracy over peer sharing as one immediate example.
These reactions, I think, help us to imagine what a public culture might be after free culture’s demise. What remains, however, is to recapture that productive engine of Kelty’s recursive publics that drive cryptocurrency and web3 today in building other hyper-capitalist futures. If commons-based peer production is a joke. If free culture is a ruse. What ways of doing with technology remain? Just as Jackie Wang has productively re-read theories of control through racial capitalism, I see a continued challenge of reimagining democracy, addressing its historic exclusions, and colonial underpinnings.
Perhaps as a final word I stay with Cristian Dunbar-Hester’s closing sentence in Hacking Diversity. “A focus on technology itself... may be confining to a social justice agenda. It might be possible to build more democratic technology -- undoubtably, it is possible -- but at the same time, democratic praxis should never be limited to a technological imaginary” (p. 242). Therein, we might consider what was free culture as a proxy for new prototypes of being, of citizenship that never succeed but are still needed.
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