Dissertation Summary
Translation
Original address:
Recommended Reading
- The Interpretability of Artificial Intelligence and the Impact of Outcome Feedback on Trust: A Comparative Study
- The researchers found that although it is generally believed that the interpretability of the model can help improve the user's trust in the AI system, in the actual experiment, the global and local interpretability does not lead to a stable and significant trust improvement. Conversely, feedback (i.e., the output of the results) has a more significant effect on increasing user trust in the AI. However, this increased trust does not directly translate into an equivalent improvement in performance.
- User experience
- Xue Zhirong's knowledge base
- tool
- The content is made up of:
- blog
- Robots and digital humans
- To assess trust more accurately, the researchers used behavioral trust (WoA), a measure that takes into account the difference between the user's predictions and the AI's recommendations, and is independent of the model's accuracy. By comparing WoA under different conditions, researchers can analyze the relationship between trust and performance.