TY - JOUR
T1 - The Flow of Trust
T2 - A Visualization Framework to Externalize, Explore, and Explain Trust in ML Applications
AU - van der Elzen, Stef
AU - Andrienko, Gennady L.
AU - Andrienko, Natalia
AU - Fisher, Brian
AU - Martins, Rafael
AU - Peltonen, Jaakko
AU - Telea, Alex
AU - Verleysen, Michel
N1 - Publisher Copyright:
© 1981-2012 IEEE.
PY - 2023/3/1
Y1 - 2023/3/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85151377641&partnerID=8YFLogxK
U2 - 10.1109/MCG.2023.3237286
DO - 10.1109/MCG.2023.3237286
M3 - Article
SN - 0272-1716
VL - 43
SP - 78
EP - 88
JO - IEEE Computer Graphics and Applications
JF - IEEE Computer Graphics and Applications
IS - 2
ER -