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

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Re-imagining Algorithmic Fairness in India and Beyond (2021, background): “, how do we hold deployers of systems accountable for unfair outcomes? Is it fair to deploy a system that lacks in accountability? Accountability is fundamentally about answerability for actions [114], and central to these are three phases by which an actor is”
Towards Accountability for Machine Learning Datasets: Practices from Software Engineering and Infrastructure (2020, methodology): “1 Our analysis and proposals follow [147] and [83] in using temporal situatedness as a key organizing factor.”
Closing the AI accountability gap: defining an end-to-end framework for internal algorithmic auditing (2020, methodology): “We use accountability to mean the state of being responsible or answerable for a system, its behavior and its potential impacts [38].”
A Broader View on Bias in Automated Decision-Making: Reflecting on Epistemology and Dynamics (2018, unknown): “(Kohli et al., 2018).”