Intelligibility and Accountability: Human Considerations in Context-Aware Systems

By Victoria Bellotti, Keith J. Edwards. 2001

566 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Information Systems, Information Systems and Management

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Citations in the corpus

Manipulating and Measuring Model Interpretability (2018, background): “[9] Victoria Bellotti and Keith Edwards.”
Predicting human interruptibility with sensors: a Wizard of Oz feasibility study (2003, background): “Bellotti defines the components of context, design guidelines and human-salient details for realizing them [2].”
Context as a Dynamic Construct (2001, background): “Consequently, context-aware systems should be fairly conservative in the actions they take, should make these actions highly visible, and should leave “risky” actions to user control (Bellotti & Edwards, 2001 [this special issue], take a similar point of view in their essay).”
Learning from a learning thermostat: lessons for intelligent systems for the home (2013, background): “been done into how to design interfaces that render system behavior more intelligible [1,12,24], such research has yet”
Interpreting Interpretability: Understanding Data Scientists' Use of Interpretability Tools for Machine Learning (2020, background): “Bellotti and Edwards [6] were the ﬁrst to consider intelligibility and accountability, providing guidelines for system designers.”
Questioning the AI: Informing Design Practices for Explainable AI User Experiences (2020, background): “[4] shows, before this wave of work on ML systems, the HCI community have studied explainable systems in various contexts, most notably context-aware applications [12, 56, 57], recommender systems [42], debugging tools [53] and algorithmic transparency [28, 80].”
Learning Situation Models in a Smart Home (2009, background): “Intelligibility [3] of the employed context model and the reasoning process is essential in order to permit the users to trust the system.”
Why and why not explanations improve the intelligibility of context-aware intelligent systems (2009, background): “Thus users of context-aware applications can have great difficulty reasoning about system behavior [ 6 ,7].”
Working with Machines: The Impact of Algorithmic and Data-Driven Management on Human Workers (2015, background): “Interaction with intelligent machines Much research has investigated how people respond to intelligent machines such as automated manufacturing technologies [23, 36, 44], recommender systems [6], context-aware systems [3, 43], agents [35], and robots [30].”
Crossing the bridge over Norman's Gulf of Execution: revealing feedforward's true identity (2013, background): “Bellotti and Edwards [3] argue that context-aware systems should be intelligible and inform end-users of their capabilities and current understanding.”
Trends and Trajectories for Explainable, Accountable and Intelligible Systems: An HCI Research Agenda (2018, background): “Notably, Bellotti and Edwards proposed that context-aware systems should be made intelligible by informing users about “what they know, how they know it, and what they are doing with that information” [13].”