🎲 Agentic AI safety series: Introduction to AI alignment challenges in agentic systems
AI data and trends for business leaders | AI systems series
Hello,
This new ten-part series, “Data and Trends,” addresses a critical and rapidly evolving challenge: ensuring the safety and security of AI systems, particularly those with autonomous decision-making capabilities known as "agentic AI."
As this publication widely explores, agentic AI, powered by LLMs, transforms how we interact with technology.
These AI agents can independently perceive their environment, reason about it, make decisions, and act to achieve specific objectives.
While this autonomy offers immense potential for increased efficiency and innovation, it also introduces new and complex safety challenges.
I believe this series will make a significant contribution to the ongoing development of robust AI safety practices.—Yael.
You can read here the purpose of the series and explore the curriculum.
Part 1: Introduction to AI alignment challenges in agentic systems
Welcome to the first week of our course on Data & Trends in AI Safety and Alignment, focusing on the unique challenges presented by agentic systems.
This week lays the groundwork for understanding why ensuring the safety and alignment of increasingly autonomous AI is a critical and evolving field so you will be able to:
Define the key characteristics of AI agents and differentiate them from other AI systems.
Explain why increasing autonomy in AI agents introduces unique safety and alignment challenges.
Describe the potential for unintended consequences and emergent behaviors in agentic AI.
Analyze initial risks associated with real-world examples of agentic AI, such as enterprise copilots.
Distinguish the alignment challenges of agentic AI from traditional LLM vulnerabilities and cybersecurity threats.