Explaining Explainable Artificial Intelligence: An integrative model of objective and subjective influences on XAI
Explaining Explainable Artificial Intelligence: An integrative model of objective and subjective influences on XAI
Files
Date
2023-01-03
Authors
Alarcon, Gene
Willis, Sasha
Contributor
Advisor
Department
Instructor
Depositor
Speaker
Researcher
Consultant
Interviewer
Annotator
Journal Title
Journal ISSN
Volume Title
Publisher
Volume
Number/Issue
Starting Page
1095
Ending Page
Alternative Title
Abstract
Explainable artificial intelligence (XAI) is a new field within artificial intelligence (AI) and machine learning (ML). XAI offers a transparency of AI and ML that can bridge the gap in information that has been absent from “black-box” ML models. Given its nascency, there are several taxonomies of XAI in the literature. The current paper incorporates the taxonomies in the literature into one unifying framework, which defines the types of explanations, types of transparency, and model methods that together inform the user’s processes towards developing trust in AI and ML systems.
Description
Keywords
Explainable Artificial Intelligence (XAI),
xai; trust; ai; reliance
Citation
Extent
10
Format
Geographic Location
Time Period
Related To
Proceedings of the 56th Hawaii International Conference on System Sciences
Table of Contents
Rights
Attribution-NonCommercial-NoDerivatives 4.0 International
Rights Holder
Local Contexts
Collections
Email libraryada-l@lists.hawaii.edu if you need this content in ADA-compliant format.