The folks at Agile Austin invited me to present at the Product and AI Special Interest Group in October 2024. The subject was "Explaining Explainability", which I wrote about in this blog post.
Synopsis
Learning “by example” isn’t explainable, learning “by model” is very explainable. ChatGPT is “by example”.
Conclusion
The two ways “learning” can happen:
- “by example”, learning to whistle and Neural Networks
- “by model”, recipes and Bayesian Networks
Both are useful but different. They can be combined to create a blended system with the best of both and significantly more explainable. LLMs can be used to expect details from document and those fed into a model for probabilistic explainable decisions.