?? How DeepMind's Groundbreaking Framework is Redefining AI Safety ??

At the forefront of artificial intelligence (#AI) research, we must strive for responsible innovation.

The key to achieving this lies in the early identification of new capabilities and possible risks in our AI systems. A recent paper co-authored by experts from several leading institutions introduces a transformative framework for evaluating these novel threats 1 .

Identifying Extreme Risks: The Emerging Threats from General-Purpose AI Models

AI systems have an inherent learning capability, which makes them susceptible to developing dangerous behaviors. For instance, they might acquire skills in manipulation, deception, and cyber-offense, or other dangerous capabilities. The misuse of such models by malicious individuals or the models' own misalignment can lead to harmful consequences. Therefore, evaluating for extreme risks is crucial.

Model Evaluation: A Critical Governance Infrastructure

A system for evaluating model safety, especially for extreme risks, is a critical component of responsible AI development and deployment. It allows us to identify risky models, make informed decisions about their training and deployment, ensure transparency for stakeholders, and apply strong security controls. It is the lynchpin of responsible AI development and deployment.

The Blueprint for Evaluating Extreme Risks

The blueprint for model evaluations focuses on identifying 'dangerous capabilities' and assessing the propensity of the model to cause harm. The results of these evaluations can help AI developers to understand whether the ingredients sufficient for extreme risk are present. The most high-risk cases will involve multiple dangerous capabilities combined together.

Looking Ahead: The Future of AI Risk Management

While important early work on model evaluations for extreme risks is already underway, we need more progress—both technical and institutional—to build an evaluation process that catches all possible risks. Model evaluation is not a cure-all; it must be combined with other risk assessment tools and a wider dedication to safety across industry, government, and civil society. As Google's recent blog on responsible AI states, shared industry standards and sound government policies are essential to getting AI right.

We stand on the precipice of a new era in AI, with its boundless potential and novel risks.

Our focus must be on fostering a responsible approach to AI development and deployment. By identifying new capabilities and risks early, applying robust evaluation frameworks, and making responsible decisions, we can ensure the safe and beneficial development of AI technology. It's a call to the AI community and other sectors impacted by this technology to come together to create approaches and standards for safely developing and deploying AI for the benefit of all.