The Furlong and Eliasmith (2023) method is classified as having low explainability because, although it uses logical symbolic methods to process features, the logical reasoning operations occur within an implicit space dependent on the neural network's output, failing to fully overcome the black box effect.

Authors

• Person: Not available Organization: arXiv
  Neuro-Symbolic AI: Explainability, Challenges, and Future Trends

Sources

• Neuro-Symbolic AI: Explainability, Challenges, and Future Trends arxiv.org arXiv via serper

Referenced by nodes (1)

• artificial neural networks concept