Critical Tools for Machine Learning: Situating, Figuring, Diffracting, Fabulating Machine Learning Systems Design

This workshop draws on feminist and other critical methodologies to construct interdisciplinary interventions in the design of machine learning systems. Theoretical concepts of “figuration”, “situating/situated knowledge”, “critical fabulation/speculation,” and “diffraction” are explored through hands-on experimentation to imagine and design machine learning systems in a more situated, inclusive, contextualize and accountable way. Through this “theory turned practice” approach the workshop aims to address systemic socio-cultural biases and develop more socially responsible frameworks of design. The workshop provides space for building a network for future research on interdisciplinary machine learning systems design.