An Early Warning System for Novel AI Risks: A Framework for Evaluating General-Purpose Models

Google DeepMind has proposed a framework for evaluating general-purpose models against novel threats. The research paper titled “An early warning system for novel AI risks”1 discusses the need for an early warning system to identify potential risks associated with the development of AI models. The paper highlights the importance of evaluating models for dangerous capabilities and alignment to inform decisions about their deployment.

The Need for an Early Warning System

As AI models become increasingly capable, there is a growing need for an early warning system to identify potential risks associated with their development. The paper argues that the evaluation of AI models must expand to include the possibility of extreme risks from novel capabilities. The authors propose a framework for evaluating general-purpose models against novel threats, which includes the following components:

• Model Capabilities: The framework evaluates the capabilities of the model and identifies potential risks associated with its development.
• Model Alignment: The framework evaluates the alignment of the model with human values and goals.
• Model Robustness: The framework evaluates the robustness of the model against adversarial attacks and other forms of manipulation.

The Proposed Framework

The proposed framework is designed to evaluate general-purpose models against novel threats. The framework includes the following components:

Model Capabilities

The evaluation of model capabilities involves identifying potential risks associated with the development of the model. The authors propose the following steps for evaluating model capabilities:

• Identify Novel Capabilities: The first step is to identify novel capabilities that could pose a risk. This involves identifying capabilities that are not present in existing models.
• Evaluate Novel Capabilities: The second step is to evaluate the potential risks associated with the novel capabilities. This involves assessing the potential impact of the capabilities on society and the environment.
• Develop Countermeasures: The final step is to develop countermeasures to mitigate the risks associated with the novel capabilities.

Model Alignment

The evaluation of model alignment involves assessing the alignment of the model with human values and goals. The authors propose the following steps for evaluating model alignment:

• Identify Human Values and Goals: The first step is to identify the human values and goals that the model should align with.
• Evaluate Model Alignment: The second step is to evaluate the alignment of the model with human values and goals. This involves assessing the model’s ability to achieve the desired outcomes.
• Develop Alignment Mechanisms: The final step is to develop alignment mechanisms to ensure that the model remains aligned with human values and goals.

Model Robustness

The evaluation of model robustness involves assessing the robustness of the model against adversarial attacks and other forms of manipulation. The authors propose the following steps for evaluating model robustness:

• Identify Threat Models: The first step is to identify the threat models that the model should be robust against. This involves identifying the types of attacks that the model could be vulnerable to.
• Evaluate Model Robustness: The second step is to evaluate the robustness of the model against the identified threat models. This involves assessing the model’s ability to resist attacks.
• Develop Robustness Mechanisms: The final step is to develop robustness mechanisms to ensure that the model remains secure against attacks.

Conclusion

The proposed framework provides a comprehensive approach to evaluating general-purpose models against novel threats. The framework includes components for evaluating model capabilities, model alignment, and model robustness. The authors argue that the evaluation of AI models must expand to include the possibility of extreme risks from novel capabilities. The proposed framework provides a starting point for developing an early warning system to identify potential risks associated with the development of AI models.Links:

1. https://www.deepmind.com/blog/an-early-warning-system-for-novel-ai-risks
2. https://www.deepmind.com/blog
3. https://www.reddit.com/r/singularity/comments/13rx127/an_early_warning_system_for_novel_ai_risks_google/
4. https://twitter.com/SmokeAwayyy/status/1661774359005134850
5. https://twitter.com/Manderljung/status/1661577426751864835
6. https://news.ycombinator.com/from?site=deepmind.com