The frameworks that ask the questions AI ethics rarely does.
Technical and policy frameworks dominate the field of AI ethics. They ask important questions about accuracy, transparency, and compliance. But they rarely ask the deeper questions: whose values are embedded in AI systems? Whose experiences are invisible to them? Whose interests do they serve?
Critical theory has been asking those questions for decades. This series brings four of the twentieth century’s most powerful intellectual traditions into direct conversation with Responsible AI, equipping seekers with analytical tools that go far beyond what conventional AI ethics frameworks provide.
This is not advocacy. It is rigorous intellectual inquiry, in the tradition of Ethos Sophia.
Five courses. One integrated lens.
The first four courses can be taken in any order. The fifth is a capstone that brings all four together.
Race, Power and Algorithms
Critical Race Theory and AI
Who does AI see, and who does it fail to see? Critical Race Theory gives us the most rigorous available framework for understanding why AI systems so frequently harm people of colour, and why those harms are so rarely remedied.
Topics covered: structural racism and algorithms, racial bias in hiring and credit scoring, facial recognition failures, predictive policing, interest convergence and AI reform, community voice in AI governance.
Duration: 35 minutes | Level: Intermediate
Gender, Labour and Machines
Feminist Theory and AI
AI was not built in a vacuum. It was built in a world shaped by patriarchy, and it reflects that world. Feminist theory reveals the gendered assumptions encoded in AI systems, the invisible labour that makes AI possible.
Topics covered: feminist theory strands, the myth of objectivity, gendered AI design, voice assistants and patriarchal assumptions, data labelling as feminised labour, and feminist AI governance.
Duration: 35 minutes | Level: Intermediate
Capital, Labour and Code
Marxist Theory and AI
Who owns AI?
Who profits from it?
Who pays the cost? Marxist theory provides the analytical tools to answer these questions honestly, revealing the political economy of AI that other ethics frameworks consistently avoid.
Topics covered: surplus value and AI ownership, ideology and the neutrality myth, data as means of production, algorithmic management of workers, surveillance capitalism, class interests in AI regulation, democratic alternatives.
Duration: 30 minutes | Level: Intermediate
Truth, Power and Code
Postmodern Theory and AI
There is no view from nowhere. Not even in an algorithm. Postmodern theory interrogates the claims AI systems make about truth and objectivity, revealing how power shapes knowledge, how categories are constructed rather than discovered, and what genuine transparency requires.
Topics covered: Lyotard and metanarratives, Foucault on power-knowledge and discourse, the digital panopticon, how AI constructs social reality, the limits of explainability, deconstructing AI ethics frameworks, postmodern humility in design.
Duration: 30 minutes | Level: Intermediate
Capstone: The Critical Lens
Synthesising Theory for Responsible AI
One theory cannot see it all either. This capstone course brings CRT, Feminist, Marxist, and Postmodern theory into conversation, examines where they complement and where they tension with each other, and asks: what does Responsible AI look like when viewed through all four lenses simultaneously?
Topics covered: intersectionality as a synthesising concept, power across all four frameworks, productive tensions between frameworks, a full case study applying all four lenses, the critical theory toolkit for AI governance, Responsible AI as ongoing critical practice.
Recommended: complete the four framework courses before this capstone.
Duration: 30 minutes | Level: Intermediate
Who is this Series for?
This series is for seekers who are not satisfied with surface-level AI ethics. It is for L&D, HR, IT governance, compliance, and AI professionals who want to understand not just what AI systems do, but why they do it, who benefits, and what would have to change for AI to be genuinely responsible.
It assumes curiosity and intellectual seriousness. It does not assume prior knowledge of critical theory.