Gartner Research

Maverick* Research: Resolving the Google Steering Wheel Dilemma in Smart Machine Design

Published: 03 October 2016

ID: G00306050

Analyst(s): David Groombridge , Brian Prentice


Balancing control versus benefit is key for autonomous smart machines. Google's Car project shows full autonomy is not yet possible, so CIOs need radical ideas to maximize benefits. (Maverick research deliberately exposes unconventional thinking and may not agree with Gartner's official positions.)

Table Of Contents


  • *Maverick Research
  • Introduction
    • The Steering Wheel Dilemma
    • Google's Steering Wheel Dilemma Applies to All Smart Machines
  • The Google Self-Driving Car Project Analyzed
    • Technology Issues
    • Societal Issues
    • Commercial Issues
    • Ethical Issues in Machine Learning
  • Finding a Wedge in Public Road Infrastructure
  • How to Avoid Your Own Steering Wheel Dilemma
    • Step 1 — Understand What Is Possible With a Learning Model
    • Step 2 — Understand How Controllable the Environment Is That Will Be Modeled
    • Step 3 — Interchangeably Apply Systems Thinking, Game and Constraints Theory to Smart Machine Projects, Depending on the Environment
    • Step 4 — Factor In the Three General Smart Machine Constraints
    • Recap — Putting It All Together

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