A No Code XAI Framework for Policy Making
Author
Abstract

Explainable AI (XAI) techniques are used for understanding the internals of the AI algorithms and how they produce a particular result. Several software packages are available implementing XAI techniques however, their use requires a deep knowledge of the AI algorithms and their output is not intuitive for non-experts. In this paper we present a framework, (XAI4PublicPolicy), that provides customizable and reusable dashboards for XAI ready to be used both for data scientists and general users with no code. The models, and data sets are selected dragging and dropping from repositories While dashboards are generated selecting the type of charts. The framework can work with structured data and images in different formats. This XAI framework was developed and is being used in the context of the AI4PublicPolicy European project for explaining the decisions made by machine learning models applied to the implementation of public policies.

Year of Publication
2023
Date Published
jun
Publisher
IEEE
Conference Location
Pafos, Cyprus
ISBN Number
9798350346497
URL
https://ieeexplore.ieee.org/document/10257291/
DOI
10.1109/DCOSS-IoT58021.2023.00091
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