Issue 1 Explainable Artificial Intelligence

A Deep Dive Into XAI

Table of Contents

  1. Summary
  2. What is XAI?
    1. How We Got Here
    2. The Argument for XAI
    3. The Difficulties of XAI
    4. The Argument Against XAI
  3. Does AI Need to be Explainable?
    1. What is an Explanation?
    2. Are Human Decisions Explainable?
    3. Types of Explanations
    4. Attributes of a Good Explanation
    5. Places Where Explanations are Most Important
  4. Methods to Achieve Explainability
    1. Possibility 1 – “It’s a black box, trust us.”
    2. Possibility 2 – “We can’t explain it, but here are stats about how well it works.”
    3. Possibility 3 – Surrogate Models
    4. Possibility 4 – “Here are the inputs we use.”
    5. Possibility 5 – Partial Explanation
    6. Possibility 6 – Sensitivity Analysis
    7. Possibility 7 – Interpretive Explainability
    8. Possibility 8 – Certification of Models
    9. Possibility 9 – Or Some Partial Combination of the Factors Above
  5. Alternatives to Explainability
    1. Alternative 1 – Keep Models Simple
    2. Alternative 2 – Only Use AI in Unimportant Arenas
    3. Alternative 3 – Give Up
  6. Analysis: Will Consumers Demand XAI?
  7. Regulation of AI

Summary

Not ready to subscribe? Learn more about Deep Dive Into AI.