Practical AI: Machine Learning, Data Science
Technology
Explainable AI that is accessible for all humans
We are seeing an explosion of AI apps that are (at their core) a thin UI on top of calls to OpenAI generative models. What risks are associated with this sort of approach to AI integration, and is explainability and accountability something that can be achieved in chat-based assistants?
Beth Rudden of Bast.ai has been thinking about this topic for some time and has developed an ontological approach to creating conversational AI. We hear more about that approach and related work in this episode.
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Show Notes:
Something missing or broken? PRs welcome!
Timestamps:
(00:00) - Welcome to Practical AI
(00:42) - Beth Rudden
(07:30) - Bringing in ontology
(16:27) - Don't infer consciousness
(22:18) - Dealing with bias
(25:59) - How to create access
(31:35) - Using AI responsibly
(38:31) - Implementing NLG to more modalities
(42:14) - Will AI make you learn better?
(44:19) - Wrap up
(44:50) - Outro
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