Artificial Intelligence Safety And Security

This book addresses different aspects of the AI control problem as it relates to the development of safe and secure artificial intelligence. It will be the first to address challenges of constructing safe and secure artificially intelligent systems.

The history of robotics and artificial intelligence in many ways is also the history of humanity’s attempts to control such technologies. From the Golem of Prague to the military robots of modernity, the debate continues as to what degree of independence such entities should have and how to make sure that they do not turn on us, its inventors. Numerous recent advancements in all aspects of research, development and deployment of intelligent systems are well publicized but safety and security issues related to AI are rarely addressed. This book is proposed to mitigate this fundamental problem. It is comprised of chapters from leading AI Safety researchers addressing different aspects of the AI control problem as it relates to the development of safe and secure artificial intelligence. The book is the first edited volume dedicated to addressing challenges of constructing safe and secure advanced machine intelligence.

The chapters vary in length and technical content from broad interest opinion essays to highly formalized algorithmic approaches to specific problems. All chapters are self-contained and could be read in any order or skipped without a loss of comprehension.

Preface: Introduction to AI Safety and Security

Acknowledgments

Editor

Contributors

Part I Concerns of Luminaries

Chapter 1 Why the Future Doesn’t Need Us

Bill Joy

Chapter 2 The Deeply Intertwined Promise and Peril of GNR

Ray Kurzweil

Chapter 3 The Basic AI Drives

Stephen M. Omohundro

Chapter 4 The Ethics of Artificial Intelligence

Nick Bostrom and Eliezer Yudkowsky

Chapter 5 Friendly Artificial Intelligence: The Physics Challenge

Max Tegmark

Chapter 6 MDL Intelligence Distillation: Exploring Strategies for Safe Access to Superintelligent Problem-Solving Capabilities

K. Eric Drexler

Chapter 7 The Value Learning Problem

Nate Soares

Chapter 8 Adversarial Examples in the Physical World

Alexey Kurakin, Ian J. Goodfellow, and Samy Bengio

Chapter 9 How Might AI Come About?: Different Approaches and Their Implications for Life in the Universe

David Brin

Chapter 10 The MADCOM Future: How Artificial Intelligence Will Enhance Computational Propaganda, Reprogram Human Culture, and Threaten Democracy … and What can be Done About It

Matt Chessen

Chapter 11 Strategic Implications of Openness in AI Development

Nick Bostrom

Part II Responses of Scholars

Chapter 12 Using Human History, Psychology, and Biology to Make AI Safe for Humans

Gus Bekdash

Chapter 13 AI Safety: A First-Person Perspective

Edward Frenkel

Chapter 14 Strategies for an Unfriendly Oracle AI with Reset Button

Olle Häggström

Chapter 15 Goal Changes in Intelligent Agents

Seth Herd, Stephen J. Read, Randall O’Reilly, and David J. Jilk

Chapter 16 Limits to Verification and Validation of Agentic Behavior

David J. Jilk

Chapter 17 Adversarial Machine Learning

Phillip Kuznetsov, Riley Edmunds, Ted Xiao, Humza Iqbal, Raul Puri, Noah Golmant, and Shannon Shih

Chapter 18 Value Alignment via Tractable Preference Distance

Andrea Loreggia, Nicholas Mattei, Francesca Rossi, and K. Brent Venable

Chapter 19 A Rationally Addicted Artificial Superintelligence

James D. Miller

Chapter 20 On the Security of Robotic Applications Using ROS

David Portugal, Miguel A. Santos, Samuel Pereira, and Micael S. Couceiro

Chapter 21 Social Choice and the Value A