Introduction

This is a third-time workshop that is happening in conjunction with the IEEE Visualization Conference, scheduled to take place in Oklahoma City, USA in October 2022. We will share all the relevant news and updates about the workshop on this website.

This workshop invites contributions that provide a user-centered perspective on how human-machine trust, domain expert knowledge, and familiarity with data science methods influence the use and adoption of visual analytics techniques and systems. The goal is to discuss and discover challenges and future directions regarding these issues by proposing design guidelines, empirical findings, and visual analytic techniques.

Sponsor Type:1

Committee

Mahsan Nourani
University of Florida

Eric Ragan
University of Florida

Alireza Karduni
Northwestern University

Cindy Xiong
University of Massachusetts Amherst

Brittany Davis
Pacific Northwest National Lab

Call for paper

Important date

2022-07-22
Draft paper submission deadline

Submission Topics

Trust considerations based on different areas of domain expertise (e.g., medical, security, scientific, financial domains).
Trust and bias considerations based on different levels of user familiarity with machine learning and visual analytics systems.
Detecting and preventing cognitive biases in visual analytics and machine learning for users.
User trust in machine learning models and visual explanations of model decisions in visual analytics systems.
The correlation between trust, domain knowledge, and potential cognitive biases.
The relationship between domain expertise and trust with model transparency, human interpretability.
The relationship between model interpretability, domain expertise, and trust.
Human-centered considerations in Human-in-the-loop visualization tools and interpretable models.

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Important Date

  • Oct 16

    2022

    Conference Date

  • Jul 22 2022

    Draft paper submission deadline

  • Oct 16 2022

    Registration deadline

Sponsored By
IEEE Computer Society
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