Enhancing AI Transparency: Innovative Methods to Explain Complex AI Decisions to Non-Experts
Sai Krishna Manohar Cheemakurthi · International Journal for Research Publication and Seminars · 2021
This paper discusses how AI can be more transparent and outlines approaches to explaining the decisions made by AI to a layperson. This paper illustrates potential improvements in explainability by presenting simulation reports, live applications, and the ability to identify the challenges. Approaches raised include the creation of user interfaces that provide decision-making clarity, the use of real-life examples, and the use of graphs. Introducing possible strategies for the future challenges typical for creating transparency, such as the struggle between the complexity and usability of the created visualizations, is provided. The insights add to the general discourse on interpretability in AI governance and users' trust in intelligent systems.