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Ai governance framework

As explained in Introduction to Generative AI, Second Edition

An AI governance framework is an organized structure of rules, principles, responsibilities, and oversight processes for governing artificial-intelligence systems.

An AI governance framework organizes rules, principles, responsibilities, and oversight for developing and using artificial-intelligence systems. It aims to ensure that productivity benefits and agentic capabilities are matched by safeguards against misuse, concentrated power, social harm, and unsafe delegation of decisions. section 10.33

A responsible framework brings together:

  • Standards, guidance, protocols, and principles for conscientious design. section 10.33
  • Regulation of AI development, effects, and surrounding safeguards. section 10.33
  • A balance between technological enthusiasm, human expertise, and concerns about unequal gains or existential risk. section 10.33

How Introduction to Generative AI, Second Edition covers it

How deep it goes
Defines the governance rationale and names voluntary practices, but stops short of procedural implementation details.
Examples
Uses voluntary protocols, principles, standards, guidance, and regulation as governance examples.
What it assumes
Assumes only a basic understanding of AI’s potential benefits, limitations, misuse, and effects on work and society.
What you can do after
Evaluate how governance can balance AI’s promised benefits against misuse, inequality, unsafe delegation, and broader social risks.
How it connects
Connects responsible AI with generative AI, AI regulation, AI risks, standards, and safeguards.

Related concepts

This explainer was generated by Manning's knowledge graph from the text of Introduction to Generative AI, Second Edition. The section links point to the parts of the book it draws on.