About this Session
Entrepreneurs, Designers, Product Managers, Consultants, and Data Scientists. Especially relevant if you synthesize data with AI, are just starting to use AI in your work, or are accountable for AI-assisted work and want to make it traceable and defensible.
This talk presents Data Mise en Place, an AI framework for making AI-assisted research traceable, defensible, and usable. If you are in a comfort zone of using AI synthesis because of its speed and ease of use, and interested in remembering why the details shape the success of our products, this talk is for you.
You will learn:
- Why speed without traceability is a liability
- How to reduce hallucinations and assumptions from generative AI-assisted research
- The Data Mise en Place framework that supports data quality, accuracy, and traceability, with evidence for every insight
- The importance of having a human in the loop in data synthesis
- How our past and current human experience helps us shape the products of today
