Design of an intelligible mobile context-aware application

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Manipulating and Measuring Model Interpretability (2018, background): “tion [55, 56]. We build on decision-making research on human trust in algorithmic (also called actuarial or mechanical) decision making [19–21, 49, 58, 60, 73] and similar efforts in computer science [8, 26, 30, 41, 44, 45, 62, 63] and present a sequence of pre-registered experiments (N = 3;800) in ”
Explainable Agents and Robots: Results from a Systematic Literature Review (2019, background): “, [65]), to facilitate context-aware explanations in human-robot teaming (e.”
Designing Theory-Driven User-Centric Explainable AI (2019, background): “Key insight: this is contrary to first showing system uncertainty as a shallow level of explanation and more transparent Inputs or mechanism as details on demand (e.g., [15, 68]).”
Trends and Trajectories for Explainable, Accountable and Intelligible Systems: An HCI Research Agenda (2018, background): “Finally, HCI researchers can perform empirical studies to evaluate the efficacy of the novel explanation interfaces in various settings (e.g., [114, 116]).”