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Extended Reality (XR) Immersive Visualisation: Identifying AI project member 'needs' in order to design for a more effective Low-Code Machine Learning Model Development experience

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posted on 2022-12-02, 14:36 authored by Richard Wheeler, Fiona CarrollFiona Carroll

 With organisations making machine learning projects more of a priority, issues have been found regarding the presentation of these types of projects and in particular, in explaining how the models that are produced work, not only internally but also to the final user. The following paper discusses the design and development of a novel Extended Reality (XR) solution that enables rapid development, experimentation and clear presentation of complex machine learning models using eXplainable AI (XAI) principles. The paper documents the findings from a short initial feasibility questionnaire study which probed participant's opinions around their current use of XR environments, low-code development platforms, and their experience of working on machine learning model development projects. The findings of that study showed that the proposed solution could be deemed novel especially regarding its use of extended reality, as none of the participants had used this technology for machine learning development productivity or collaboration. The aim of the paper is to highlight the development of a system that uses a low-code development platform for the development of machine learning models and then uses an extended reality environment to not only enable collaboration within development teams but also as a system for presenting a model's output. This paper documents the early phases of the research process (i.e. identifying the need) whilst also sharing ideas on how the issue can be solved. 

History

Presented at

Computer Graphics & Visual Computing (CGVC) 2022, Leeds Trinity University, UK, held virtually, during 15 – 16 September 2022

Link to Conference Website

Published in

Computer Graphics and Visual Computing (CGVC)

Publisher

The Eurographics Association

Publication Year

2022

Version

  • VoR (Version of Record)

Citation

Wheeler, R. & Carroll, F, (2022) 'Extended Reality (XR) Immersive Visualisation: Identifying AI project member 'needs' in order to design for a more effective Low-Code Machine Learning Model Development experience', In: Vangorp, P. & Turner, M, ed.s Computer Graphics and Visual Computing (CGVC) https://doi.org/10.2312/cgvc.20221170

ISBN

978-3-03868-188-5

Cardiff Met Affiliation

  • Cardiff School of Technologies

Cardiff Met Authors

Fiona Carroll

Copyright Holder

  • © The Authors

Language

  • en

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