Ethical and Equitable Data Science: Bridging Social Justice and Technical Innovation ADBIS 2025 Doctoral Consortium Lecture
Résumé
This paper summarises the fundamental background of the Doctoral Consortium titled "Ethical and Equitable Data Science". It introduces Freda, a methodology for designing ethical, frugal, and equitable data and algorithm-driven science. It bridges technical innovation with social justice by integrating data sovereignty, fairness-aware analytics, and community-in-the-loop infrastructure. Rooted in decolonial and feminist perspectives, Freda addresses transparency, accountability, and epistemic diversity through policy-aware Spark pipelines, federated learning, and negotiated resource dispatching. A case study illustrates how sovereignty-aware pipelines enable community control, minimise extractivism, and embed plural, justice-centred values into AI systems.