Capitalism Kritik and Answers - Emory 2024

Capitalism K & Answers – ENDI ‘24
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Capitalism K
Copyright is exploitation. Strengthening it enriches the profits of media companies while increasing the value stolen from creative workers.
Nicole S. Cohen 12. PhD Candidate, Communication and Culture, York University. “Cultural Work as a Site of Struggle: Freelancers and Exploitation.” tripleC: Communication, Capitalism, and Critique. 10(2): 141-155, 2012, https://doi.org/10.31269/triplec.v10i2.384
6. Copyright as Exploitation
Freelance writers’ livelihoods in a digital age are built on the shaky foundations of copyright protection, which are being eroded by corporations’ tightening grip on intellectual property rights. Unlike employees, who in exchange for salaries give up ownership of works they produce to employers (D’Agostino 2010, 4), freelance writers in Canada are legally classified as independent contractors and therefore own copyrights to the articles they write. Publishers are granted a limited licence to publish articles in designated publications for specified periods of time (Canada 1985, s.13; D’Agostino 2004, 6). Traditionally, this has been a benefit of working freelance, enabling writers to re-sell articles and in some way compensating for low rates of pay (Lorinc 2005, 37; PWAC 2006, 41). However, traditional practices are being undermined by uses of new technologies and aggressive publishing strategies.
The growth and consolidation of media and entertainment firms over the past few decades has been enabled by technological development, especially digital communications and digitization, a process that provides a universal language for media content and has led to convergence across media platforms, allowing corporations to deepen the exploitation of labour (Mosco 2003). Digitization enables quick transmission of information and simplifies duplication, especially online, which means publishers can repackage information for publication in multiple formats. Most periodical and newspaper publishers in Canada are part of large media chains that control a range of integrated media properties and are hungry for content that can be re-purposed for various platforms. Digitization helped corporations realize their ambitions of concentration and convergence, aided by and fuelling the push to obtain copyrights (D’Agostino 2010, 20). These rapid shifts in corporate media organization have directly affected freelance writers’ earnings, initially by shrinking the number of markets in which writers can re-sell work (PWAC 2006, 35).
These practices have grown more pervasive as they have moved online. For example, in Fall 2010, Rogers Media, a division of the massive media conglomerate Rogers Communications, began syndicating articles written for its magazines by freelancers to other websites without alerting writers, let alone paying them for extra use (Scott 2010; Story Board 2010). Unbeknownst to writers, executives began syndication as an initiative of Rogers Digital Media, which promotes access to its content to advertisers. Rogers Digital Media claimed the syndication was covered under the “promotions” clause in Rogers’ new standard contract all writers must sign, which states that Rogers can “publish the Work and/or an edited version thereof in any promotion of the publication and/or its brand in all forms of media” (ibid.). Writers’ organizations, however, claim that this is a broad interpretation of the contract: “most contributors would not read ‘promotion’ as syndication on [websites] many months after their story first appears in a Rogers publication,” argued freelance
writer agent Derek Finkle (Scott 2010).
This example demonstrates publishers’ growing desire to own outright the rights to writers’ works, which are cheap to “digitally recycl[e]” into new profit (D’Agostino 2010, 239). This strategy aligns with Marx’s ([1867] 1990, 325) explanation of surplus value: after a worker earns enough to reproduce her labour power, the capitalist owns the rest of the value she produces, which “for the capitalist has all the charms of something created out of nothing”. Most large publishers now present writers with “streamlined” contracts that claim all copyrights for writers’ works at once (D’Agostino 2005, 166). Contracts can demand, for example, “all rights, in perpetuity, throughout the universe” in any form, including rights for media formats yet to be invented. These contracts are generally non-negotiable and do not offer extra payment for extra rights (PWAC 2006, 35). Depending on the company and its media holdings, rights demanded can include translations, digitizing, adaptations and performances, reprints, relicensing, promotions, and storage of articles in electronic databases.
Current contracting regimes have effectively expanded possibilities for exploitation of surplus value indefinitely (D’Agostino 2010, 241). Economists view copyright primarily as providing economic incentive for creators to produce intellectual and artistic works (Bettig 1996, 7; Towse 2003). However, under the capitalist mode of cultural production, copyright’s primary function is to guarantee its owner exclusive right to exploit the work and to extract surplus value from workers who have been granted relative autonomy at the point of production. With workers providing services on a one-off basis, companies need not be concerned with how works are created, as the real value for corporations lies in the continued exploitation of completed works. Notes one freelance writer, “No one cares where I am, just as long as I get the work done”. What matters to firms is not the time spent on a project or the pace of work – control over the labour process – but ownership over the final product, which can be re-published, re-licensed, and re-purposed, generating surplus value from the works themselves and lowering labour costs.
Capitalism developed by generating technological methods of extracting knowledge from workers to control production and increase efficiency and exploitation (Braverman [1974] 1998), and continues this trajectory by claiming ownership of the information workers produce (May 2002, 318). This is a crucial, under-examined link between cultural work and capital, obscured either by a focus solely on the autonomy of cultural workers or by a failure to acknowledge that it is labour that creates the texts, images, ideas, and symbols that are transformed into private property (Rossiter 2006, 145).
Copyright has become a high-stakes site of struggle in Canada and beyond. Freelance journalists in North America have won class action lawsuits against publishers for using works without acknowledgement or extra payment (D’Agostino 2010). Film and television writers struck for three months in 2007-2008 to win a greater share of residual money from DVD sales and revenues from digital downloads (Klowden and Chatterjee 2008). Freelance photographers effectively delayed the launch of People magazine’s iPad app over its licensing agreement, as photographers demanded payment for use of their photos beyond the pages of the magazine (Wallenstein 2010). Book producers such as Alloy Entertainment and Full Fathom Five12 are transforming copyright relations between writers and publishers by hiring authors to write pre-fabricated books, often under a pseudonyms, and retaining all rights to their works, generating licensing deals for film and television while contractually barring writers from claiming authorship (Mozes 2010). These struggles will become more charged as we move deeper into the digital age.
Capitalism drives extinction and structural violence.
Jamie Allinson et al 21. Senior Lecturer in Politics and International Relations at Edinburgh University and author of The Age of Counter-revolution. China Miéville is the author of a number of highly acclaimed and prize-winning novels including October: The History of the Russian Revolution. Richard Seymour is the author of numerous works of non-fiction, His writing appears in the New York Times, London Review of Books, Guardian, Prospect, Jacobin. Rosie Warren is an Editor at Verso and the Editor-in-Chief of Salvage. All are writing for the Salvage Collective. “The Tragedy of the Worker: Toward the Proletarocene.” Introduction. July 2021. Verso EBook. ISBN: 9781839762963 //shree
This is the question that vexed us as we set out to write The Tragedy of the Worker. From the vantage point of the present, the history of capitalist development is, as Marx expected, the history of the development of a global working class, the proletarianisation of the majority of the world’s population. But the very same process of that development has brought us to the precipice of climate disaster. Our position, to recall Trotsky’s rationalisation of War Communism in 1920, is in the highest degree tragic.
It is now clear that we will pass what scientists have long warned will be a tipping point of global warming, accelerating the already catastrophic consequences of capitalist emissions. How do we imagine emancipation on an at best partially habitable planet? Where once communists imagined seizing the means of production, taking the unprecedented capacities of capitalist infrastructures and using them to build a world of plenty, what must we imagine after the apocalypse has befallen us? What does it mean that as capitalism has become truly global, the gravediggers it has created dig not only capitalism’s grave, but also that of much organic life on earth?
Our answers to these questions remain rooted in the politics of revolutionary communism. Our stance is not based on the fantasy of a homeostatic nature that must be defended but on the critique of the capitalist metabolism – the Stoffwechsel- that must be overthrown. Earth scientists are accustomed to speak in terms of ‘cycles’ by which substances circulate in different forms: the water cycle, the rock cycle, the nitrogen cycle, the glacial-interglacial cycle, the carbon cycle, and others. One way of registering the catastrophe of climate change is to see these cycles – most of all, but not solely, the carbon cycle – as disordered, under- or over-accumulating. But this is to ignore the more fundamental circuit of which these now form epicycles, like Ptolemy’s sub-orbits of the heavenly bodies: the circuit of capital accumulation, M-C-M′.
This circuit accumulates profit and produces death. Neither is accidental. It is for this reason that the debates that capitalist ruling classes permit among themselves on ‘adaptation’ versus ‘mitigation’ take place on false premises. What is to be mitigated is the impact of climate change on accumulation, rendered through the ideology of ‘growth’ as something that benefits everyone. What we are to adapt to are the parameters of accumulation, sacrificing just enough islands, eco-systems, indigenous – and non-indigenous – cultures to maintain its imperatives for a period of time until new thresholds must be crossed, and new life sacrificed to the pagan idol of capital. Already, capitalist petro-modernity builds a certain quantum of acceptable death into its predicates: at the very least, the 8.7 million killed by fossil fuels each year according to Harvard University are considered a price worth paying for the stupendous advantages of fossil capital. And the sky can only keep going up, as deforestation, polar melt, ocean acidification, soil de-fertilisation and more intense wildfires and storms tear the web of life into patches. If the necropolitical calculus of the Covid-19 pandemic appears crass, just wait until its premises are applied to climate catastrophe.
The alternative is to reject intellectual property in favor of a commons-based approach to ideas. Only worker-ownership can resolve inequalities between creators and build an equitable economy.
Eric Drott 21. Professor at the Butler School of Music, University of Texas at Austin, PhD from Yale University in 2001. "Copyright, compensation, and commons in the music AI industry". Creative Industries Journal 2021, Vol. 14, No. 2, 190–207. https://www-tandfonline-com.proxy.library.emory.edu/doi/epdf/10.1080/17510694.2020.1839702?needAccess=true
From copyright to commons
Taking a more expansive view of the actors involved in what’s marketed as AI-generated music has the benefit of shifting attention away from what comes out o machine learners and redirecting it towards what goes into them. Indeed, much of198 E. DROTT the efficacy – and hence much of the value – of machine learners depends on the datasets on which they are trained. Recall Pachet’s remarks cited earlier: elsewhere in the same interview he describes ‘a huge shift in what is most valuable in the technol-ogy industry. It used to be algorithms, but now it is data’ (Pachet 2018). Recall as well Domingos’s metaphor of ‘growing’ programs instead of writing them line by line, com-mand by command. Within this metaphor, training data is positioned as the soil and water that nourishes programs and that encourages their growth. But if training data contribute much to the success and value of expressive AI, how are we to measure this contribution? And what might those responsible for creating this material be due as a result? Answers to these questions within contemporary copyright regimes will depend on whether the material being used for training is under copyright and, if so, whether its use is somehow exempt. Crucially, developers of commercial systems, unlike academic researchers, aren’t obliged to reveal the sources of their training data. And for the most part they don’t volunteer this information. In public pronouncements, most firm stake care to mention only repertoire already in the public domain. In a TED talk, Pierre Barreau, CEO of AIVA, boasted that his company’s neural networks were trained on‘30,000 scores of history’s greatest’, including ‘the likes of Mozart and Beethoven’(Barreau 2018). Likewise, the one dataset that Juke deck has publicly cited is a corpus of English folksongs (Jukedeck 2017). Yet evidence suggests that both firms rely on more than just public domain works. Both AIVA and Jukedeck offer their clients a choice of pop genres, some of which – like pop synth and drum ‘n’ bass – only devel-oped after the copyright term currently in force in the EU, UK, and US. That being the case, it is very unlikely that either firm exclusively used public domain works to train their systems how to generate stylistically appropriate songs within these and other contemporary music genres. It seems likely, then, that at least some of the training data used by AI startups falls under copyright. And this suggests that still another party might have some claim on works produced by commercial music AI: the producers of the material used to train the machine learners in question. This point has not been lost on artists and advocacy groups. Artist Rights Watch, for one, has called for musicians to invoke the marketing restriction clause in recording and publishing contracts to refuse their music’s use ‘for AI purposes of any kind’ (Castle 2017). To justify their hard line, Artist Rights Watchnotes that computer generated works ‘can be sold or licensed at a very low price’ ,undercutting the market for human-composed production music (Castle 2017). A related tack is to maintain that any piece generated using music under copyright be considered a ‘derivative work’ and thus guilty of infringement. While the compensation rights holders would receive for such derivative works would no doubt be infinitesimally small, it would provide at least some compensation. To forestall any potential legal claims they might face, music AI firms have a num-ber of defensive measures they may exercise. One is to ensure they have rights to the works they use to train their systems: such is the case with Endel, whose system is trained on a large number of musical ‘stems’ that an in-house composer in their employ creates for hire. Barring that, companies can assert some sort of exemption. This is what Google has done in the United States, in connection with its massive Creative INDUSTRIES JOURNAL 199digitization of copyrighted texts for Google Books. Its argument, upheld in courts inthe US legal system, is that its use of expressive works under copyright is itself non-expressive, and thus sufficiently transformative to fall under the fair use exception of American copyright law (Sag 2019). Another way of skirting liability is to get individual artists to unwittingly sign over the rights to their music to the platforms they use to distribute their music. Buried in Spotify for Artists’ terms of service, for instance, is a clause granting the company ‘a non-exclusive, transferable, sub-licensable, royalty-free, irrevocable, fully paid, worldwide license to [ … ] create derivative works from [ … ]any of your User Content’ (Spotify 2017). While this provision on its face applies only to nonmusical content that artists might upload to the service (photos, bios, etc.), it notably remained in place, unaltered, during the period in 2018-19 when Spotify allowed musicians to bypass labels and aggregators and upload their music directly to the platform. Lacking the leverage and legal resources that major labels possess, inde-pendent artists who availed themselves of this service may have inadvertently pro-vided Spotify with the means to transform both their music and themselves into artistic surplus. Beyond such affirmative defenses, it is not clear whether artists and rights holders who invoke marketing restrictions or claim that an AI-generated work is derivative would find much traction under existing copyright regimes. To begin with, to show apiece is derivative requires demonstrating ‘substantial similarity’, a key test for copy-right infringement. But the musical output of machine learners is, in the words of Deltorn and Macrez, more ‘a recomposition than a mere copy or [ … ] audio collage’, which means that the ‘final work will not – in most instances – be found ‘substantially similar’ to any of the materials used to train the system’ (2018, 19). This in turn ren-ders a finding of market harm unlikely – another key test of infringement. Still another difficulty is practical, having to do with the challenge of identifying all the relevant copyright holders whose creations have been used to train an AI, determining the contribution their works made to its training, and apportioning royalties accordingly. Such difficulties would appear to rule out, either in principle or in practice, any claim that authors of training data might have on works generated by a machine learner trained on their music. But the challenges confronting such claims lies more than anything else with the inadequacies of existing copyright law, inadequacies that have become all the more glaring in the face of the epistemic and ontological shifts heralded by machine learning. These shortcomings follow from copyright’s commit-ment to the individual as the basic unit of reference, be it the individual author, the individual owner, or the individual work. And yet much of machine learning’s power derives from its capacity to generalise, to find functions that model the aggregate pat-terns that emerge across an aggregation of items in a dataset (Mackenzie 2017, 82).Copyright law’s grounding in a tradition of possessive individualism makes it ill-equipped to deal with systems that model the behavior of collective phenomena –including the collective musical knowledge embodied in a corpus. Hence, in order to address the questions of political economy presented by the growing commercialization of music AI, we need a framework grounded not in individual property, but informs of common property. Fortunately, the practices and discourses that have developed around commons and common pool resources provide such a framework. From200 E. DROTT this standpoint, what firms like AIVA, Jukedeck, and the like are engaged in is a form of free riding

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