Engaging Our Power Beyond Algorithmic Bias: Reframing and Resisting AI Empire
Introduction and Context
The presentation begins by addressing the influence of algorithmic bias in AI systems and introduces the term AI Empire. This framework is a critical lens through which the presenter examines how the ideologies of capitalism, colonialism, racism, and heteropatriarchy fuel AI's development and perpetuate social inequalities.These interlocking systems of oppression, deeply embedded in the technology sector, manifest in the automation of social control and essentialism (reducing individuals to predefined characteristics), serving capitalist ends such as profit and societal domination.
The AI Empire is an understatement as a technological advancement. It is better understood as a socio-technical system in which AI and society shape each other in culture. AI, in particular, plays a pivotal role in influencing societal structures and behaviors. It's time to move beyond the notion of AI as a neutral tool and acknowledge its active role in maintaining power structures.
This approach reflects a broader challenge. Libraries were initially designed to uphold the social and moral order rather than to encourage or enable radical change. This historical context creates friction in the current technological landscape, where innovation is rapid, and libraries struggle to keep up while maintaining ethical and inclusive practices.
The AI Empire is an understatement as a technological advancement. It is better understood as a socio-technical system in which AI and society shape each other in culture. AI, in particular, plays a pivotal role in influencing societal structures and behaviors. It's time to move beyond the notion of AI as a neutral tool and acknowledge its active role in maintaining power structures.
AI in Libraries: Resistance and Implication
The presenter highlights that libraries and librarians, historically positioned as gatekeepers of knowledge, are often framed as reactionary to technological advancements. The dominant narrative suggests that librarians must constantly defend their relevance, especially in the face of innovations like the internet and, more recently, AI tools like ChatGPT.This approach reflects a broader challenge. Libraries were initially designed to uphold the social and moral order rather than to encourage or enable radical change. This historical context creates friction in the current technological landscape, where innovation is rapid, and libraries struggle to keep up while maintaining ethical and inclusive practices.
A crucial concept here is classification—a fundamental task of libraries.
While designed to organize knowledge, classification systems (such as cataloging and collection development) have often upheld systems of inequality. Despite efforts to become more inclusive, Libraries continue to engage in gatekeeping practices by defining who has access to certain types of knowledge or spaces. In this sense, libraries are not immune to the broader AI Empire, as they, too, are implicated in sustaining systems of control through their organizational structures.
AI Empire and Socio-Technical Systems
The presenter introduces AI Empire to challenge the common perception of AI as a tool that can be improved by correcting biases or refining algorithms. Instead, AI must be considered part of a socio-technical system, where society and technology are co-constitutive—that is, they shape each other.
AI Empire and Socio-Technical Systems
The presenter introduces AI Empire to challenge the common perception of AI as a tool that can be improved by correcting biases or refining algorithms. Instead, AI must be considered part of a socio-technical system, where society and technology are co-constitutive—that is, they shape each other.
For libraries, this means recognizing that AI technologies cannot be fully understood or critiqued without addressing the broader systems (capitalism, patriarchy, colonialism) that influence their design and deployment. This understanding equips librarians with a more comprehensive approach to AI.
To better illustrate this point, the presenter discusses the history of libraries as institutions that have historically upheld oppressive systems. For example, libraries once played a role in segregation (e.g., segregated spaces or discriminatory access policies) and continue to perpetuate social inequality through policies that restrict access based on literacy or socioeconomic status.
Resistance Strategies: Beyond Algorithmic Literacy
Algorithmic literacy, which emphasizes understanding how AI works and identifying biases in AI systems, is an essential but insufficient step in addressing the root issues. The presenter argues that focusing solely on the technological artifact (the AI tool itself) overlooks the structural biases intentionally embedded within these systems to maintain inequality. In this regard, AI does not merely reflect society's biases—it is built to reinforce them.
To honestly resist the AI Empire, librarians, and academic institutions have the potential to move beyond the "bad apples" or "biased algorithms" narrative and engage with the foundational ideologies—capitalism, colonialism, patriarchy, and white supremacy—that underpin AI's development. This potential for change requires a broader critical consciousness about the systems in which AI operates and the power it wields over society.
To better illustrate this point, the presenter discusses the history of libraries as institutions that have historically upheld oppressive systems. For example, libraries once played a role in segregation (e.g., segregated spaces or discriminatory access policies) and continue to perpetuate social inequality through policies that restrict access based on literacy or socioeconomic status.
Resistance Strategies: Beyond Algorithmic Literacy
Algorithmic literacy, which emphasizes understanding how AI works and identifying biases in AI systems, is an essential but insufficient step in addressing the root issues. The presenter argues that focusing solely on the technological artifact (the AI tool itself) overlooks the structural biases intentionally embedded within these systems to maintain inequality. In this regard, AI does not merely reflect society's biases—it is built to reinforce them.
To honestly resist the AI Empire, librarians, and academic institutions have the potential to move beyond the "bad apples" or "biased algorithms" narrative and engage with the foundational ideologies—capitalism, colonialism, patriarchy, and white supremacy—that underpin AI's development. This potential for change requires a broader critical consciousness about the systems in which AI operates and the power it wields over society.
Frameworks for Reframing AI: Critical Concepts
The presentation references two key frameworks that deepen our understanding of how AI and its socio-technical systems function: AI Empire: As already defined, this framework conceptualizes AI as a tool of social control deeply embedded in the same power structures that dominate society—capitalism, colonialism, racism, and patriarchy. Rather than seeing AI as a neutral or objective tool, this framework calls attention to how AI perpetuates existing systems of inequality.The presenter delves into the ethical costs of AI development, including its impact on marginalized communities and environmental degradation. AI technology's huge language models are built on vast amounts of data extracted from existing systems of knowledge production, most of which have been shaped by Western, white, male perspectives. This creates a feedback loop where the elite's biases and assumptions are amplified and perpetuated through AI, with the effects disproportionately felt by the global majority and marginalized communities.
Moreover, the environmental cost of AI systems, such as the massive computational power required for machine learning models, must be addressed. The extraction of resources for server farms and the energy needed to run them are significant contributors to environmental destruction, further exacerbating global inequalities.
Moreover, the environmental cost of AI systems, such as the massive computational power required for machine learning models, must be addressed. The extraction of resources for server farms and the energy needed to run them are significant contributors to environmental destruction, further exacerbating global inequalities.
Practical Steps: Resisting AI Empire in Libraries
The presentation concludes with practical advice for librarians and information professionals on resisting the AI Empire: Encouraging critical reflection, the presenter urges librarians to question their practices and the systems they uphold. This involves critically examining the role of technology in reinforcing existing power structures and considering how they can resist these forces in their day-to-day work. Fostering Critical Consciousness: Librarians should strive to cultivate critical consciousness among their communities, helping users understand how to use AI tools and how they are implicated in broader power systems.Collective Imagination: The presenter emphasizes the importance of collective imagination—envisioning and working towards new systems of knowledge that challenge the status quo. This could involve designing alternative classification systems, promoting open access to information, and actively working to decolonize library practices.
Strategizing and Organizing: The presenter calls for organizing within the library profession to build collective power. This involves solidarity with marginalized groups and actively resisting technologies and systems reinforcing inequality.
