A Comprehensive Guide to
Contemporary AI Safety
Safer Agentic AI
Principles and Responsible Practices
A practical guide to governing, aligning, and securing autonomous AI systems. Written for policymakers, developers, and leaders responsible for AI that acts on its own.
What Experts Are Saying
Reviews from researchers and practitioners in AI, ethics, and technology governance
What Is Agentic AI?
Agentic AI systems pursue goals, adapt to situations, and make decisions without human input. Unlike AI that recommends, these systems act—breaking down tasks, running experiments, adjusting to feedback. Because they operate autonomously, errors compound before humans can notice or intervene.
Look Inside the Book
From AI fundamentals through governance frameworks ready to implement
Table of Contents
From the Foreword
"This timely volume addresses one of our field's most daunting challenges: ensuring the safe and beneficial development of increasingly autonomous AI systems. The authors combine technical expertise and ethical insight in a comprehensive framework... This book is invaluable for AI researchers, developers, policymakers, business leaders and anyone invested in the responsible future of artificial intelligence."
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Key Focus Areas
Nine dimensions determine whether an agentic AI system remains safe under real-world conditions.
Goal Alignment
Verifying that an AI system pursues the objectives its operators actually intended, not a distorted proxy.
Value Alignment
Embedding ethical values into AI behaviour and verifying they persist across updates and new contexts.
Safe Operations
Maintaining safe behaviour from development through deployment, including under degraded or adversarial conditions.
Epistemic Hygiene
Preventing AI systems from acting on false, stale, or poorly calibrated information.
Transparency
Making AI decision-making auditable so that operators can trace how a conclusion was reached and why.
Goal Termination
Reliable task completion, graceful shutdown, and orderly decommissioning when a system is no longer needed.
Security
Protecting AI systems against adversarial attacks, prompt injection, data poisoning, and other threat vectors.
Contextual Understanding
Verifying that an AI system accurately models its operating environment, including the boundaries and constraints that apply.
Responsible Governance
Clear lines of accountability, compliance structures, and oversight mechanisms throughout the deployment lifecycle.
Built on Structured Expert Analysis
The book expands on a framework developed by our Community of Practice of international experts in AI, ethics, law, and safety engineering, using the Weighted Factors Analysis (WeFA) expert-elicitation process.
Read the Recommended PracticesAbout the Authors
Leaders in AI safety, ethics, and governance
Our Working Group
Experts from AI, ethics, law, social sciences, and safety engineering have contributed their time and domain knowledge to develop this framework.
Regular Contributors
- Ali Hessami
- Matthew Newman
- Sara El-Deeb
- Farhad Fassihi
- Mert Cuhadaroglu
- Scott David
- Hamid Jahankhani
- Nell Watson
- Sean Moriarty
- Isabel Caetano
- Roland Pihlakas
- Vassil Tashev
- Keeley Crockett
- Safae Essafi
- Zvikomborero Murahwi
- Lubna Dajani
- Salma Abbasi
Occasional Contributors
- Aisha Gurung
- Leonie Koessler
- Pramod Misra
- Aleksander Jevtic
- McKenna Fitzgerald
- Pranav Gade
- Alina Holcroft
- Michael O'Grady
- Rebecca Hawkins
- Md Atiqur R. Ahad
- Mrinal Karvir
- Sai Joseph
- Chantell Murphy
- Nikita Tiwari
- Tim Schreier
- Katherine Evans
- Patricia Shaw
Additional Contributors
- Fadi Arab
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The Safer Agentic AI Community of Practice is a global network of practitioners developing safety guidelines for autonomous AI systems.
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