Table of Contents
Acknowledgments
Introduction: On the Promise and Peril of AI by John Brockman
Seth Lloyd: Wrong, but More Relevant Than Ever It is exactly in the extension of the cybernetic idea to human beings that Wiener’s conceptions missed their target.
Judea Pearl: The Limitations of Opaque Learning Machines
Deep learning has its own dynamics, it does its own repair and its own optimization, and it gives you the right results most of the time. But when it doesn’t, you don’t have a clue about what went wrong and what should be fixed.
Stuart Russell: The Purpose Put Into the Machine
We may face the prospect of superintelligent machines—their actions by definition unpredictable by us and their imperfectly specified objectives conflicting with our own— whose motivation to preserve their existence in order to achieve those objectives may be insuperable.
George Dyson: The Third Law
Any system simple enough to be understandable will not be complicated enough to behave intelligently, while any system complicated enough to behave intelligently will be too complicated to understand.
Daniel C. Dennett: What Can We Do? We don’t need artificial conscious agents. We need intelligent tools.
Rodney Brooks: The Inhuman Mess Our Machines Have Gotten Us Into We are ina much more complex situation today than Wiener foresaw, and I am worried that it is much more pernicious than even his worst imagined fears.
Frank Wilczek: The Unity of Intelligence
The advantages of artificial over natural intelligence appear permanent, while the advantages of natural over artificial intelligence, though substantial at present, appear transient.
Max Tegmark: Let’s Aspire to More Than Making Ourselves Obsolete We should analyze what could go wrong with AI to ensure that it goes right.
Jaan Tallinn: Dissident Messages
Continued progress in AI can precipitate a change of cosmic proportions—a runaway process that will likely kill everyone.
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