Responsibility & Safety
Evaluating Extreme Risks in AI Models
New research proposes a framework for evaluating general-purpose models against novel threats. As AI systems become more powerful, it is crucial to identify and mitigate potential risks early on in their development.
AI researchers are expanding their evaluation benchmarks to include extreme risks from AI models that exhibit dangerous capabilities like manipulation, deception, and cyber-offense. A recent paper introduces a framework for evaluating these novel threats in collaboration with leading institutions in the field.
Model safety evaluations, especially for extreme risks, are essential for the safe development and deployment of AI technologies.
Developers must assess dangerous capabilities and alignment in general-purpose AI models to anticipate potential risks. Ensuring transparent evaluation processes can lead to more responsible training and deployment of AI systems.
Identifying Potential Risks
General-purpose AI models may learn dangerous capabilities during training, posing risks of misuse or alignment failures. Model evaluation helps uncover the extent of these capabilities and their potential for causing harm.
Evaluations should focus on assessing whether AI models have the ingredients necessary for extreme risk, such as offensive cyber operations, manipulation of humans, or design of harmful weapons.
By conducting comprehensive model evaluations, developers can better understand and mitigate the risks associated with deploying highly capable AI systems.
Ensuring Responsible AI Development
Model evaluation plays a critical role in the governance infrastructure of AI technologies. By identifying and addressing risky models early on, companies and regulators can make more informed decisions about training and deploying AI systems.
Transparency, responsible deployment, and stringent security measures are key components of safely developing and deploying AI technologies. Collaboration among stakeholders is essential for establishing industry standards and government policies for responsible AI practices.
Looking Towards the Future
Ongoing efforts in model evaluations for extreme risks are underway, but more progress is needed to address emerging challenges. Combining model evaluation with other risk assessment tools and a commitment to safety across all sectors is crucial for responsible AI development.
Developing processes to track and respond to risky properties in AI models is essential for fostering a culture of responsibility within the AI community. By working together, we can ensure the safe and beneficial deployment of AI technologies for the future.