Location
Online
Event Website
https://hicss.hawaii.edu/
Start Date
3-1-2023 12:00 AM
End Date
7-1-2023 12:00 AM
Description
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.
Recommended Citation
Alarcon, Gene and Willis, Sasha, "Explaining Explainable Artificial Intelligence: An integrative model of objective and subjective influences on XAI" (2023). Hawaii International Conference on System Sciences 2023 (HICSS-56). 4.
https://aisel.aisnet.org/hicss-56/da/xai/4
Explaining Explainable Artificial Intelligence: An integrative model of objective and subjective influences on XAI
Online
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.
https://aisel.aisnet.org/hicss-56/da/xai/4