Analytical Frameworks
Theoretical lenses for critically examining AI systems
Critical Race Theory in AI
Critical race theorists analyze how AI systems encode systemic racial biases and perpetuate existing inequalities, emphasizing the need to critically assess the societal impacts of technology. They argue that algorithmic decision-making often reflects broader power structures and biases, calling for accountability and inclusive practices in AI development.
Decolonial Critique of AI
Decolonial scholars emphasize the need to challenge Western-centric epistemologies in AI development. They argue that AI technologies often perpetuate colonial power dynamics, extracting local data without consent and favoring Western narratives. A decolonial approach calls for technology that centers the voices of marginalized communities and respects their sovereignty.
Feminist AI Critique
Feminist scholars critique AI systems by highlighting the embedded biases in technology that disproportionately affect women and marginalized groups. They argue that these biases stem from historical power structures and advocate for incorporating gender-specific indicators in AI development to ensure fair representation and equitable outcomes.
Intersectional AI Critique
This analytical framework integrates Black feminist thought to examine how AI systems perpetuate interlocking oppressions by centering the voices of those most affected. It calls for intersectionality to be at the forefront of AI ethics, stressing that understanding AI harm requires acknowledging and elevating the experiences of Black and Indigenous women.
Indigenous Data Sovereignty and AI
This framework emphasizes the right of Indigenous communities to control data concerning their own cultures and lands, challenging AI systems that exploit Indigenous data without consent. It critiques the intersections of technology and colonialism, advocating for community-led data governance that resists patterns of colonial extraction inherent in AI systems.
The New Jim Code and Algorithmic Inequality
Developed by Ruha Benjamin, the 'New Jim Code' framework explores how algorithms and AI technologies encode and amplify racial hierarchies, perpetuating discriminatory practices under the guise of objectivity. This approach critiques the normalization of technologies that reinforce systemic racism, compelling scholars and practitioners to explore alternatives that center the experiences of marginalized groups.
Data Feminism in AI Research
Data Feminism advocates for an intersectional approach to AI research methodologies, challenging the patriarchal and colonial assumptions embedded in prevailing data practices. This framework promotes the examination of who benefits from AI systems and how decision-making processes can be restructured to ensure equitable representation and data usage.
Black Feminist AI Critique
This framework draws from Black feminist thought to analyze how AI systems perpetuate interlocking oppressions based on race, gender, and class. It emphasizes the importance of intersectionality in understanding the unique harms caused by AI technologies and advocates for centering the voices of Black and Indigenous women in AI ethics discussions.
Decolonial-Feminist AI Literacy
This framework advocates for a critical understanding of AI technologies through a decolonial-feminist lens, emphasizing the importance of equipping diverse individuals with the skills to analyze and challenge power dynamics in AI systems. It argues that AI often perpetuates existing inequalities and marginalizes voices that are traditionally excluded from technological narratives, leading to a need for inclusivity in AI discourse.
Not My AI: A Feminist Framework to Challenge Algorithmic Decision-Making
This framework critiques the deployment of AI systems in public services, particularly how they disproportionately surveil vulnerable populations like women, migrants, and people of color. It calls for accountability and community involvement in the decision-making processes surrounding AI, emphasizing the role of feminist and anti-colonial perspectives in shaping ethical frameworks. This approach aims to disrupt colonial legacies in technological practices.
Black Feminism and Artificial Intelligence
This framework utilizes Black feminist thought to critique AI systems, highlighting the compounded discrimination faced by Black women and other marginalized groups. It emphasizes intersectionality as critical for understanding the multilayered impacts of AI, asserting that dominant ethical frameworks often overlook the unique experiences and perspectives of these communities. This perspective seeks to center their voices in the discourse around AI development and ethics.
Data Feminism for AI
This framework applies principles of Data Feminism to interrogate the methodologies employed in AI research, advocating for intersectional standards that prioritize equity. By examining whose data is used and who benefits from AI systems, it pushes for a restructuring of research practices to include diverse perspectives. This framework highlights the necessity of feminist interventions in the creation and implementation of AI technologies.
Algorithms of Oppression
This framework critiques the ways in which AI systems, particularly search engines, reinforce systemic racism and devalue marginalized communities. By foregrounding the biases that underpin algorithmic decision-making, it underscores the imperative of recognizing how technology perpetuates social inequalities, suggesting that these biases are a reflection of broader societal issues rather than mere technical flaws.
Critical AI Literacy
This framework emphasizes the need for critical engagement with AI technologies to address power imbalances and give voice to marginalized communities. By equipping individuals with the skills to analyze and question AI's implications, it advocates for a more inclusive discourse that challenges dominant narratives in technology. Critical AI Literacy seeks to transform how people interact with AI, aiming for a more equitable technological landscape.
Political Economy of AI
This framework analyzes AI through the lens of capital accumulation, labor relations, and market power. It asks who profits from AI, how it restructures work, and how platform monopolies concentrate power. It connects AI development to broader dynamics of surveillance capitalism and the gig economy.
Actor-Network Theory
ANT treats both human and non-human entities as 'actants' within networks. Applied to AI, it dissolves the boundary between 'the algorithm' and 'the social,' tracing how AI systems are assembled from heterogeneous elements — data, code, labor, infrastructure, legal frameworks, and cultural assumptions. It asks: who and what makes an AI system act?
Infrastructure Studies
Infrastructure studies examines the material substrates — data centers, undersea cables, mining operations, energy grids — that make AI possible but remain invisible. It reveals how AI's 'immateriality' is a myth, exposing the environmental costs, geographic inequalities, and maintenance labor undergirding these systems.
Postcolonial Computing
Postcolonial computing examines how AI systems reproduce colonial logics — extracting data and labor from the Global South while centering design in the Global North. It interrogates whose knowledge is encoded, whose is excluded, and how AI becomes a vector for epistemic violence and technological dependency.
Feminist Technoscience
Feminist technoscience brings attention to the gendered, racialized, and embodied dimensions of AI. It questions the 'view from nowhere' that AI claims, insisting on situated knowledge and accountability. It foregrounds the care work, emotional labor, and reproductive labor hidden within AI systems.
