Developing Intuition For AI As A Leader: Path To Data Literacy
summary
Claims that narrow AI mainly reduces prediction costs and will spawn new business sectors, with specifics: training machine learning models on historical data (house-price toy with random weights then iterative retrain), handling data drift by continuous retraining, and tracing bias to historical hiring data. Uses natural language processing and deep learning to link CRM SharePoint ERP docs so a live untribe-style product surfaces repair steps and spare-part numbers for a ticket. Examples: managers’ “five years and 10 million dollars” vs a simple geographic lookup, and scaling from 5,000 to 500,000 contracts.
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chapters (10)
- 0:00AI intuition for leaders
- 3:08Why AI feels unintuitive
- 11:18Defining AI for business
- 14:27Build ML model from scratch
- 21:56AI bias and training data
- 25:49Data literacy as new oil
- 27:12AI as augmented intelligence
- 33:56Human-in-the-loop AI
- 38:13Summary: AI-driven business
- 40:00Q&A: AI volatility
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