This second post in our Future of Ownership: Perspectives from Creators series dives into one of the workshop’s most intriguing discussions: the potential and pitfalls of GenAI in creative industries. A discussion that revealed the tension between AI’s promises and the forces driving its adoption.
The Promise and Perils of AI in Creative Fields
On one side, some participants saw AI as a “doorway into possibilities”—a tool with the potential to democratize creativity by making resources more accessible, saving time, and allowing artists to build on the collective legacy of those who came before. One participant shared a personal example, noting that without the technological tools available today, he wouldn’t have been able to learn about music composition and production. This view frames AI as a means of broadening creative access and empowering more people to express themselves artistically.
However, others voiced concerns that by automating creative tasks, AI could displace entry-level jobs in creative fields, ultimately reducing opportunities for new talent to learn and grow. This concern was echoed by participants from the music industry, who worry about the impact of AI-generated music on streaming revenues, which many artists already find to be dismally low. Alongside these worries, some participants highlighted issues around digital inequality, challenging the view of AI as a democratizing tool. And they are not mistaken. According to a recent report from The Guardian, “almost half of UK families with children lack the online skills or access to devices, data, and broadband required to participate in today’s digital society.” This digital divide is particularly pronounced among families from lower socioeconomic backgrounds and minority ethnic groups, raising the question of how accessible AI-driven creative tools really are and can be in practice.
The Economic Forces Driving AI Adoption
The tensions mentioned above lead to a larger question: Is AI itself the issue, or does it simply amplify existing economic problems rooted in capitalism? Gordon Johnstone, one of the workshop’s participants, said: “AI isn’t creating new problems; it’s just exacerbating old ones. Capitalism always finds the cheapest way to do something. ” Johnstone’s comment resonates with the reality that AI’s use as a cost-saving measure isn’t unique. It reflects a broader tendency within capitalism to maximize efficiency by reducing labour costs.
The recent Writers Guild and SAG-AFTRA strikes shed light on these issues. At the heart of these strikes were concerns about residual revenues in the context of streaming services, which have negatively impacted the earnings of writers and actors. Alongside the pushback for better compensations regarding these revenues, were concerns about generative AI’s ability to replicate writers’ styles for scripts and mimic actors’ voices and likenesses without consent or compensation. Although AI’s role in the entertainment industry is not entirely new—recommendation algorithms, for example, are already well-integrated—the shift toward using AI to replace human involvement in more creative decisions marks a more pressing development. Take, for example, the controversy surrounding the AI-assisted opening credits of Marvel’s Secret Invasion series, which surely is just one of many more coming examples of this uneasy intersection between AI and human creative labour.
Finally, the strikes concluded with an agreement that partially addressed the role of generative AI in T.V and film industries. Under the new terms companies are prohibited from forcing writers to use generative AI, and any AI-generated material won’t be classified as literary content. Additionally, production companies now can reject generative AI use when it threatens copyright protections. For actors, the agreement mandates explicit consent for the use of their likeness or voice in AI-generated work, preventing unauthorized reproductions and preserving their control over their identity.
Ultimately, the strikes draw attention to the necessity for robust labour protections, strong unions, and policies that uphold fair wages and job security —not only in creative fields where AI might replace human roles but across the entire productivity chain in every industry. As technology advances, the importance of securing fair and ethical practices remains paramount to ensure that innovation doesn’t come at the cost of human dignity and opportunity.
Automation, and Bullshit Jobs.
In his book Bullshit Jobs, David Graeber contends that many people worldwide hold jobs that are repetitive, unnecessary, and lacking any real purpose—what he terms “bullshit jobs.” These are roles that even the people who perform them recognize as having no meaningful impact on society, and their disappearance would leave little trace. Graeber’s analysis highlights an irony: while automation has indeed eliminated some jobs, particularly in industrial settings, it has simultaneously led to the rise of new “professional, managerial, clerical, sales, and service” roles that he argues, offer questionable value. As automation advances, these sectors—such as financial services, human resources, and public relations—have expanded, yet the people in truly productive roles often remain underpaid and exploited. In cases where manual labour is cheaper than automation, human workers continue to be exploited, demonstrating a persistent imbalance in the labour market.
The integration of AI into creative industries adds a layer of complexity to the labour dynamics Graeber critiques. Unlike the “bullshit jobs” he identifies, the positions AI could replace in creative fields are often foundational. These entry-level and early-career roles are crucial for junior professionals, providing them with the experience and skill development needed to refine their craft and establish careers. As discussed in the workshop, if AI automates these roles, it may ironically transform what were once valuable, skill-building jobs into “bullshit jobs,” reducing creativity to task-driven work with minimal impact or purpose. Even more concerning, this shift could end up funnelling displaced creatives into genuinely “bullshit jobs” in other industries. AI’s impact on labour, then, is not merely about job displacement; it may redefine the nature of creative work itself, challenging who can afford to remain in these industries and raising questions about the future accessibility and diversity of creative expression.
Science Fiction’s Perspective on AI and Labor: Machinehood
Turning to the science fiction angle—after all, this is the SF section of the Digital Constitutionalist—the issues raised in the workshop brought to mind S.B. Divya’s Machinehood, a novel I read a few months ago and that envisions a future where AI has taken over much of the labour force. In this world, people are pushed into a hyper-competitive gig economy, forced to rely on cognitive-enhancing drugs just to keep pace with AI-driven productivity standards. Others end up doing what could only be called “babysitting” weaker AIs in roles that used to be their own jobs.
While Machinehood begins with a manifesto from machine rights activists advocating for AI protection, the story ultimately speaks to the fears of job instability and societal breakdown in a world where technology has failed to fulfil its utopian promise of reducing work, improving welfare, and alleviating social inequality. The novel presents a future where technology exacerbates disparities, with those at the margins facing even greater economic precarity. Divya’s novel warns of a future where the supposed collaboration between humans and machines becomes a façade, masking an underlying dynamic of exploitation and relentless productivity that benefits only a few.
Divya’s world encapsulates the worst-case scenario if human-machine collaboration devolves into a relentless pursuit of efficiency and productivity. The novel challenges us to think critically about the trajectory of AI in our own time: Should technology be harnessed solely as a tool to save time and increase output, or can it be reimagined to support creativity, cultivate meaningful work, and uplift social well-being?
Reimagining Copyright and Ownership for the Creative Industry
The workshop concluded with a crucial question: what role can copyright law play in fostering stability and opportunity within the creative industries? In the days following the workshop, I found myself returning to this question, reflecting on how our discussions had centred on protecting opportunities for creatives, yet we had done so within a copyright system fundamentally shaped by proprietarianism—a framework that mirrors capitalist values. This proprietarian approach tends to frame copyright primarily as a tool for asserting ownership and extracting financial value from creative work. But perhaps it’s time to reassess this approach.
Reflecting further, I thought about the solutions we had encountered. In the Writers Guild and SAG-AFTRA strikes, the outcome was, in part, a rejection of AI technologies in creative processes. Meanwhile, in Bullshit Jobs, David Graeber proposes a radical alternative: collectivizing AI technology, recognizing it as the product of years of collective human effort and therefore belonging to humanity. Which of these approaches is the best solution? I’m not entirely certain. What is clear, however, is that to truly address the tension between AI’s promise and its economic impact, we need a creative rethinking of copyright’s goals—one that looks beyond merely protecting individual property rights. This means exploring how copyright might better support creativity and originality, especially in a world where AI opens new collaborative possibilities. Is copyright’s primary purpose to protect property rights, as is common practice today, or could it evolve to support innovation and the cultivation of creativity more broadly? In my view, resolving the tension between AI’s potential and the economic reality of creative work requires a conversation that reimagines copyright’s objectives.
Daniel Chia Matallana
Daniel Chia Matallana is a PhD Candidate at the Centre for Science in Society at Victoria University of Wellington.
