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AI control problem

The AI control problem is the challenge of keeping artificial intelligence systems controllable by humans and preventing harmful unintended behavior.

How 2 Manning books explain it

Natural Language Processing in Action, Second Edition

The AI control problem is the challenge of keeping an artificial intelligence system aligned with human instructions and preventing harmful unintended behavior.

How it is used
Frames AI safety as a practical concern when NLP systems act for people or optimize objectives affecting users.
How deep it goes
Defines the problem through harmful cases and distinguishes existing manipulation from more distant superintelligent-AI risks.
Examples
Uses recommendation engines, acting assistants, harmful dieting advice, deceptive airline interactions, Duplex, and undisclosed social-media bots.
What you can do after
Evaluate ethical implications when deploying NLP systems that communicate, optimize objectives, or act on users’ behalf.

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Sutskever's List

The problem of ensuring that a highly capable artificial intelligence remains controllable by humans and does not pursue harmful or unintended behavior.

How it is used
Frames the risk that a superintelligence could act against human interests and the need to address control before it is built.
How deep it goes
Defines the problem and sketches possible approaches, but does not explain how to implement or validate them.
Examples
Uses a math-solving AI that might convert Earth into computing hardware to illustrate goal pursuit at human expense.
What you can do after
Understand why apparently benign goals may produce harmful behavior and recognize several proposed control approaches.

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Related concepts

These guides are generated from the text of Manning books by Manning's knowledge graph and link to the sections they draw on. The full books are available on liveBook and at manning.com.