Her talk on the social relations of AI production will focus on private and public sector bodies, and Big Tech companies that aggressively harvest personal data with a logic of extraction that mirrors historical forms of colonialism. Datasets are used to advance profits and shareholder interests, and managers feed the same data into machines, where new technological systems and tools advance the commodification of social relations. The hegemonic drive is for AI production, but data subjects experience a new violence, where any possibility for social relations outside of the restrictions of capitalism is disappearing.

Ultimately, workers’ capacity to consent, both to data capture and to forms of profiling, are under threat. In this keynote talk Professor Moore will focus on increased coercion exceeding consent, the rise in inequalities and fall of autonomies in the social relations of AI production.

Questions from Grazia Errichiello

 

The theme of this year’s EAEPE conference refers to the “Janus face” of AI—its dual potential for empowerment and harm. How does this duality manifest in your own research and professional experience?

Moore: I do not write about the potential benefits for AI, because I think forecasting such an overture is a cognitive error. ‘Artificial intelligence’ is ‘artificial’. In my professional life, I do not frequently argue that something artificial is preferable to the ‘real’, unless the real has been damaged beyond comprehension for a fix that can also be maintained by processes within the real. I want to spend time on intentional human real time future building, and therefore, spending my research energies endorsing anything that cannot be transversally contrasted would lend itself to justifiable skepticism. I am staying with the trouble, in that I am revealing the real before relishing the replica or redeeming a ruse.

As a scholar working at the intersection of public interest, international affairs, and the future of work, what do you believe are the most urgent societal questions we should be asking about AI today?

Moore: The most urgent societal questions we should be asking about today, are not about AI. We should be asking why governments are funding ‘artificial intelligence’, rather than funding the welfare state, education, housing, eliminating climate change, and fighting the far right. Funding AI development is akin to the promotion of Big Tech norms, promoting the rupture of green spaces for data centers, and providing a decorated but eminently obvious pipeline for automation of some aspects of work, but not all jobs.

We hear about the displacement of jobs due to AI. What does the rise of AI mean for workplace autonomy and dignity?

Moore: If there is no job, one cannot imagine autonomy nor dignity. However, as has been proven repeatedly, AI does not replace jobs in all industries. Technologies replace jobs and indeed, should replace jobs. Robots work in factories now where people once worked, but that is better for humans, where there is retraining, upskilling and job mobility on the cards (it often is not). Managers use slide deck-powered ‘AI salvation’ strategizing with higher skilled workers, where the middle-tier of skilled workers in IT work have seen their workloads not reduced, and their jobs not replaced as such, but instead, their workloads have intensified. Introducing new ‘AI’ software usually leads to work intensification for a few workers, deskilling of a few workers, and the worsening of work for a lot of workers.

How can trade unions, worker advocacy groups, and policymakers respond effectively to algorithmic control and the changing nature of labour?

Moore: Trade unions are responding to the issues of digitalization internationally. A good way to find out about this is to look at our AI Observatory for Work in the Digital Economy, where in the journal I edit, Global Political Economy, I am publishing the Symposium on AI and the world of work in the September edition. We are publishing updates about what a series of countries and jurisdictions are enacting and also are dealing with, in the face of AI advancements internationally. See: https://www.essex.ac.uk/research-projects/ai-policy-observatory-for-the-world-of-work

Our Brazil case report, by Grohmann, Parana, Valente, and Figaro, explores Brazil’s AI governance as a political battleground. While the Brazilian Artificial Intelligence Plan (2024–2028) emphasizes innovation and digital sovereignty, labour rights are largely overlooked. The authors call for inclusive governance centred on labour protections. In our India report, Roy and Das Sarma highlight fragmented yet fast-evolving AI policy amid inequality and informality. Weak regulation ignores worker rights, fueling precarity and surveillance. Cohesive, labour-centred regulation is urgently needed. Donoghue’s essay on China notes strong state-led AI development, focusing on societal risks but neglecting workers’ rights. In our Canada country report, Hung et al. critique techno-nationalist AI narratives, urging a shift toward public-interest governance, labour inclusion, and accountability. In our report about the EU, I argue, with Petrucci, and Muldoon, that AI is treated as an inevitable advancement, driven by economic goals and business interests. Current regulation promotes innovation but avoids deeper political debate. We are overall calling for political resistance, worker-led governance, and urgent engagement with how AI is reshaping labour and the future of work.

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