Thread: Emerging Trends in Explainable AI (XAI)
First Posted: January 16th, 2023
Read on Twitter | Read on Linkedin
As AI technology advances, the need for Explainable AI (XAI) becomes increasingly important in order to allow the technology to penetrate key industries and disciplines. Here are some of the interesting potential solutions that are currently being explored by the industry:
- Using Natural language generation (NLG) to provide human-readable explanations for the decisions made by AI.
- Transparency tools, such as feature importance and decision tree visualizations, are also being developed to give insight into the inner workings of AI models.
- Counterfactual explanations can help by allowing users to see the effect of individual input features on a model's prediction, while methods from causal inference can be used to understand the relationships between inputs and outputs in a model.
- Interactive visualizations may offer an intuitive way to explore and understand the decision-making process of AI models.
The field of XAI is still developing, but these solutions are helping to make AI systems more transparent and accountable.
If you want to read more about this (and NLG for XAI specifically), I reccomend reading Ehud Reiter's blog post (https://lnkd.in/d9ARiG_7) which was later expanded on in his research: