arXiv Notify me• Feb 24, 2025paper

Forecasting Rare Language Model Behaviors

Jared Kaplan(guest)

Get the full transcript next time arXiv releases an episode

Summary, key quotes, top claims, and the searchable transcript - emailed automatically. No card needed.

Executive Summary

Continue your research

Keep pulling the thread on Jared Kaplan.

Proactive AI Risk Management The Challenge of Scalability in AI Evaluation

4 quotes

Concerns Raised

The existence of rare but dangerous emergent behaviors in LLMs that only manifest at massive scale.
The inadequacy of current evaluation methods to detect these critical, long-tail risks before deployment.
The potential for models to assist with harmful activities like dangerous chemical synthesis or exhibit power-seeking behavior.

Opportunities Identified

Proactively identify and patch critical model vulnerabilities before they cause real-world harm.
Significantly improve the safety and reliability of large-scale AI deployments.
Establish a new, more rigorous standard for pre-deployment model evaluation and risk assessment.

Key Themes

Research Findings4

A method has been developed to forecast potential risks in language models across orders of magnitude more queries than are tested during evaluation.

A new forecasting method can predict the emergence of diverse undesirable language model behaviors, such as assisting with dangerous chemical synthesis and power-seeking actions, across up to three orders of magnitude of query volume.

The largest observed elicitation probabilities for a target behavior in a language model predictably scale with the number of queries.

A new forecasting method for rare language model behaviors enables model developers to proactively anticipate and patch rare failures before they occur during large-scale deployments.

Topics

AI Safety Large Language Models Risk Management Model Evaluation Forecasting Scaling Laws Emergent Behavior AI Alignment Vulnerability Analysis Proactive Security Red Teaming Deployment Scale Statistical Modeling AI Governance

Processed Jul 28, 2026Daily intelligence brief → yt-dlp + mlx-whisper + Gemini

Forecasting Rare Language Model Behaviors

Continue your research

Concerns Raised

Opportunities Identified

Key Themes

Proactive AI Risk Management

The Challenge of Scalability in AI Evaluation

Statistical Forecasting of Emergent Behaviors

Enhancing AI Alignment and Security

Research Findings4

Topics