An Information-Theoretic Framework for Comparing Voice and Text Explainability
#XAI #Information Theory #Machine Learning #Voice Interface #Trust Calibration #arXiv #Explainable AI
📌 Key Takeaways
- Researchers have developed a new mathematical framework based on information theory to compare voice and text AI explanations.
- The study addresses the need for better trust calibration and user comprehension in Explainable AI (XAI) systems.
- The framework treats the delivery of an explanation as a communication channel to measure information transfer efficiency.
- Findings suggest that the modality of an explanation significantly impacts how users perceive and trust machine learning models.
📖 Full Retelling
🏷️ Themes
Artificial Intelligence, Human-Computer Interaction, Communication Theory
📚 Related People & Topics
Machine learning
Study of algorithms that improve automatically through experience
Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can learn from data and generalize to unseen data, and thus perform tasks without explicit instructions. Within a subdiscipline in machine learning, advances i...
Information theory
Scientific study of digital information
Information theory is the mathematical study of the quantification, storage, and communication of a particular type of mathematically defined information. The field was established and formalized by Claude Shannon in the 1940s, though early contributions were made in the 1920s through the works of H...
🔗 Entity Intersection Graph
Connections for Machine learning:
- 🌐 Large language model (7 shared articles)
- 🌐 Generative artificial intelligence (3 shared articles)
- 🌐 Electroencephalography (3 shared articles)
- 🌐 Computer vision (3 shared articles)
- 🌐 Natural language processing (2 shared articles)
- 🌐 Artificial intelligence (2 shared articles)
- 🌐 Graph neural network (2 shared articles)
- 🌐 Neural network (2 shared articles)
- 🌐 Transformer (1 shared articles)
- 🌐 User interface (1 shared articles)
- 👤 Stuart Russell (1 shared articles)
- 🌐 Ethics of artificial intelligence (1 shared articles)
📄 Original Source Content
arXiv:2602.07179v1 Announce Type: cross Abstract: Explainable Artificial Intelligence (XAI) aims to make machine learning models transparent and trustworthy, yet most current approaches communicate explanations visually or through text. This paper introduces an information theoretic framework for analyzing how explanation modality specifically, voice versus text affects user comprehension and trust calibration in AI systems. The proposed model treats explanation delivery as a communication chan