Translation Tutorial - A Shared Lexicon for Research in Human-Centered Software Systems

Explore a comprehensive tutorial from FAT* 2018 that addresses the challenge of linguistic conflation in research on human-centered software systems. Delve into the complexities of terminology used across different disciplines studying fairness, accountability, and transparency in algorithmic systems. Learn how scholars from various fields employ shared vocabulary to describe distinct concepts, and understand the implications of these linguistic differences on research and policymaking. Examine core technical ideas in machine learning and data science, presented for a broad audience, and analyze example scenarios that illustrate the real-world impact of algorithmic systems. Gain insights into how different stakeholder communities approach the design, development, deployment, and evaluation of these systems, and identify potential gaps in disciplinary understanding. Discover strategies for improving communication across cultural and academic boundaries, and explore the consequences of terminological misunderstandings on interventions and policy decisions in the field of human-centered software systems.