How to Measure Anything in AI: Quantitative Techniques for Decision-Making

Course details

Artificial intelligence is the most impactful technological advancement since the internet itself. Organizations in every field need to figure out how to use it or risk being left behind by competitors. In this course, Douglas Hubbard, the best-selling author of How to Measure Anything: Finding the Value of Intangibles in Business, provides a clear blueprint for measuring success of AI products and services.

Learning objectives
Identify key AI trends and their quantifiable impacts on businesses and society.
Describe the challenges and flaws in current attempts to measure AI value.
Compare different methods for measuring AI and explain their applications.
Analyze the monetary value of information in AI projects using Monte Carlo simulations.
Evaluate the growth rate of AI technologies and their implications for future developments.

Concepts

Introduction

Measure anything in AI with Doug Hubbard

Trends and Challenges in AI Measurement

Treating AI as knowledge work

Principles of Measurement Applied to AI

The concept of measurement
Object of measurement
AI measurement methods

Examples of Approaches to Measuring AI and Its Applications

Quantifying AI performance
Measuring the current state to measure AI performance
Calibrated probability assessments
An example of AI in decision-making

AI Adoption and the Future

Diffusion and adoption of AI
The future of AI
Quantifying and decomposing risk in AI implementation
Anything, including AI, is measurable