Leveraging Knowledge Graphs for AI System Auditing and Transparency
Auditing complex Artificial Intelligence (AI) systems is gaining importance in light of new regulations and is particularly challenging in terms of system complexity, knowledge integration, and differing transparency needs. Current AI auditing tools however, lack semantic context, resulting in diffi...
Saved in:
Main Authors: | Laura Waltersdorfer, Marta Sabou |
---|---|
Format: | Article |
Language: | English |
Published: |
Elsevier
2025-01-01
|
Series: | Web Semantics |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S1570826824000350 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Constructing a metadata knowledge graph as an atlas for demystifying AI pipeline optimization
by: Revathy Venkataramanan, et al.
Published: (2025-01-01) -
A systematic review of regulatory strategies and transparency mandates in AI regulation in Europe, the United States, and Canada
by: Mona Sloane, et al.
Published: (2025-01-01) -
Automated Audit and Self-Correction Algorithm for Seg-Hallucination Using MeshCNN-Based On-Demand Generative AI
by: Sihwan Kim, et al.
Published: (2025-01-01) -
Towards leveraging explicit negative statements in knowledge graph embeddings
by: Rita T. Sousa, et al.
Published: (2025-01-01) -
Explainable AI chatbots towards XAI ChatGPT: A review
by: Attila Kovari
Published: (2025-01-01)