SwePub - search: WFRF:(Verleysen Michel)

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1.	van den Elzen, Stef, et al. (author) The Flow of Trust : A Visualization Framework to Externalize, Explore, and Explain Trust in ML Applications 2023 In: IEEE Computer Graphics and Applications. - : IEEE Computer Society. - 0272-1716 .- 1558-1756. ; 43:2, s. 78-88 Journal article (peer-reviewed)abstract We present a conceptual framework for the development of visual interactive techniques to formalize and externalize trust in machine learning (ML) workflows. Currently, trust in ML applications is an implicit process that takes place in the user-s mind. As such, there is no method of feedback or communication of trust that can be acted upon. Our framework will be instrumental in developing interactive visualization approaches that will help users to efficiently and effectively build and communicate trust in ways that fit each of the ML process stages. We formulate several research questions and directions that include: 1) a typology/taxonomy of trust objects, trust issues, and possible reasons for (mis)trust; 2) formalisms to represent trust in machine-readable form; 3) means by which users can express their state of trust by interacting with a computer system (e.g., text, drawing, marking); 4) ways in which a system can facilitate users- expression and communication of the state of trust; and 5) creation of visual interactive techniques for representation and exploration of trust over all stages of an ML pipeline.

van den Elzen, Stef, et al. (author)
The Flow of Trust : A Visualization Framework to Externalize, Explore, and Explain Trust in ML Applications
2023
In: IEEE Computer Graphics and Applications. - : IEEE Computer Society. - 0272-1716 .- 1558-1756. ; 43:2, s. 78-88
Journal article (peer-reviewed)abstract
- We present a conceptual framework for the development of visual interactive techniques to formalize and externalize trust in machine learning (ML) workflows. Currently, trust in ML applications is an implicit process that takes place in the user-s mind. As such, there is no method of feedback or communication of trust that can be acted upon. Our framework will be instrumental in developing interactive visualization approaches that will help users to efficiently and effectively build and communicate trust in ways that fit each of the ML process stages. We formulate several research questions and directions that include: 1) a typology/taxonomy of trust objects, trust issues, and possible reasons for (mis)trust; 2) formalisms to represent trust in machine-readable form; 3) means by which users can express their state of trust by interacting with a computer system (e.g., text, drawing, marking); 4) ways in which a system can facilitate users- expression and communication of the state of trust; and 5) creation of visual interactive techniques for representation and exploration of trust over all stages of an ML pipeline.

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