Caroline Sinders

Caroline Sinders is a machine learning design researcher who investigates artificial intelligence through a feminist lens. Her signature work, the Feminist Data Set, interrogates AI training pipelines by examining the data and design choices that shape how machine learning systems learn and make decisions. Rather than accepting AI development as a neutral technical process, Sinders brings critical scrutiny to the foundations of algorithmic systems, asking whose perspectives are represented, whose are excluded, and what consequences follow from these choices.

Sinders' research and practice span fellowships and collaborations with prestigious institutions including Harvard Kennedy School, Mozilla, Pioneer Works, Eyebeam, and Ars Electronica. She founded Convocation, a design and research consultancy dedicated to interrogating technology systems. Through these roles, she has developed a substantial track record of examining how bias, power, and gender intersect within the technical infrastructure of artificial intelligence and machine learning design.

Audiences who engage with Sinders encounter a rigorous, evidence-based critique of AI development practices. Her work matters because it centers questions typically marginalized in technology discourse: How do training data sets embed assumptions about gender, labor, and value? What happens when we design AI systems without interrogating their foundational data? Sinders offers concrete frameworks for understanding these systems, moving beyond abstract discussions of "bias" toward meaningful analysis of how design decisions reproduce or resist structural inequalities.