AI Regulation

Frontier artificial intelligence (AI) systems pose increasing risks to society, making it essential for developers to provide assurances about their safety. One approach to offering such assurances is through a safety case...

As frontier artificial intelligence (AI) systems become more capable, it becomes more important that developers can explain why their systems are sufficiently safe. One way to do so is via safety cases: reports that...

Over the past year, artificial intelligence (AI) companies have been increasingly adopting AI safety frameworks. These frameworks outline how companies intend to keep the potential risks associated with developing and deploying...

Regulators in the US and EU are using thresholds based on training compute--the number of computational operations used in training--to identify general-purpose artificial intelligence (GPAI) models that may pose risks of...

Several jurisdictions are starting to regulate frontier artificial intelligence (AI) systems, i.e. general-purpose AI systems that match or exceed the capabilities present in the most advanced systems. To reduce risks...

Frontier artificial intelligence (AI) systems could pose increasing risks to public safety and security. But what level of risk is acceptable? One increasingly popular approach is to...

Existing strategies for managing risks from advanced AI systems often focus on affecting what AI systems are developed and how they diffuse. This approach becomes less feasible as the number of developers of advanced AI grows.

Compute providers can play an essential role in a regulatory ecosystem via four key capacities: as securers, safeguarding AI systems and critical infrastructure; as record keepers, enhancing visibility for policymakers...

Recent AI progress has largely been driven by increases in the amount of computing power used to train new models. Governing compute could be an effective way to achieve AI policy goals, but could also introduce new risks.

Training advanced AI models requires large investments in computational resources, or compute. Yet, as hardware innovation reduces the price of compute and algorithmic advances make its use more efficient, the cost of training...

To deal with the risks of these high-compute frontier AI systems, we must govern not only how they can be used but also how they are developed and made available to people in the first place.

We welcome the opportunity to respond to the OSTP Request for Information on National Priorities for Artificial Intelligence and look forward to future opportunities to provide additional input. We offer the following...

Advanced AI models hold the promise of tremendous benefits for humanity, but society needs to proactively manage the accompanying risks. In this paper, we focus on what we term “frontier AI” models — highly capable...

We welcome the opportunity to respond to the NTIA’s AI Accountability Policy Request for Comment and look forward to future opportunities to provide additional input. We offer the following...

We are pleased to see the publication of the UK’s Future of Compute Review. However, we also believe there is a significant missed opportunity: the review does not address how to ensure that compute is used responsibly or how...

Artificial intelligence (AI) systems will increasingly be used to cause harm as they grow more capable. In fact, AI systems are already starting to be used to automate fraudulent activities, violate human rights, create...

The proposed EU AI Act is the first comprehensive attempt to regulate AI in a major jurisdiction. This article analyses Article 9, the key risk management provision in the AI Act. It gives an overview of the regulatory...

The world appears to be entering an era of heightened great power technological competition in areas such as artificial intelligence. This is concerning because deploying new technologies often involves private benefits and...