In the age of AI, when models like DALL-E and ChatGPT impact countless aspects of our lives, the dehumanizing and harmful features of AI that have plagued data science since its inception continue resulting in the routine erasure, exploitation, and subjugation of people of color, Indigenous people, women, queer, non-binary, immigrant, dis/abled, and non-Western people. Far from a “glitch” or unintentional error, these endemic issues are a function of the systemic oppression upon which the global AI industry is built. Rooted in colonialism, heteropatriarchy, and racial capitalism, this perpetual oppression shows that we live not simply in the Age of AI but in the Age of AI Empire. Since Big Data and algorithms only further reinforce the logics of hegemony, extractivism, surveillance, and subjugation which drive AI Empire, we argue that reforming AI from within the same oppressive system that created it can do little beyond providing band-aid solutions.

Instead, to advance justice, we must radically transform our ideas about data and technology and develop them from the ground-up, from the perspectives of those who stand the most risk of being harmed. Rather than being perceived as “vulnerable,” the people and communities most directly impacted by AI are more properly understood as demonstrating technological ingenuity and sustained resistances against AI Empire – revolutionary tactics we call Data Resurgence. Through the lessons learned from Indigenous, decolonial, and queer communities, we show that data resurgence can be a powerful collective response to AI Empire based on Anti-coloniality, Relationality, Sovereignty, and Liberatory Praxis.

This paper reflects on the role of ideology in the development of artificial intelligence and potential alternatives to dominant discourses in the technology industry. Besides widely documented ideologies such as White supremacy, techno-libertarianism, and techno-universalism, longtermism has become more prominent in recent years. As another horizon, this paper contrasts these ideologies with lessons from Latin American struggles, presenting ideas from vivir bien (to live well) philosophy that emerged from indigenous and afro grassroots organizations and has influenced progressive politics in the region for the past decades. Instead of focusing on the individual and utilitarian approaches to technology development, living well philosophy centers on communities and their relationship with their territories. The paper concludes with an invitation to imagine a future where communities can live well with technology.

Cloud infrastructure platforms underpin most of today’s internet, functioning as the operating system of the internet and representing the most important source of revenue for Big Tech companies. While most of the current hype around (“generative”) AI is focused on specific successful products and initiatives like OpenAI (ChatGPT, DALL·E 2) and Stability AI (Stable Diffusion), they would not have been possible without the significant infrastructural support and investments from Big Tech companies. This paper critically examines what we call Big AI, or those types and deployments of AI that simply would not be feasible or even possible without the infrastructural support, partnerships, or investments provided by Big Tech companies. To account for this, we articulate the key components of AI and how they are connected. By focusing on Big Tech’s own products and service offerings, third-party applications, and models, we gain a more comprehensive understanding of what Big AI is, or looks like today, and what it may become in the years to come—for which the infrastructure is being made right now. Further, we make a distinction between the cloud platform products and service offerings from Big Tech (i.e. the cloud as an infrastructure for AI) and Big Tech as the host or provided of marketplaces for diverse (AI-based) products and services from third-party businesses and developers (i.e. the cloud as a marketplace for AI). Overall, this research provides the basis for a better understanding of the critical political economy of (Big) AI.