An Overview Of Our Current Governance Efforts
The governance team at Apollo Research conducts technical governance research, develops tailored policy recommendations, and communicates our organisation’s learnings to key stakeholders across industry, civil society and governments.
Our goal is to ensure that future governance mechanisms concerned with loss of control, scheming*, and dangerous capability evaluations are functional, scientifically validated, and effective. We therefore focus on both the development of foundational research and the translation thereof into practical policy levers ready for implementation by industry and governments.
Our recent portfolio of workstreams included**:
1. Specifying and contextualising how dangerous capability evaluations can serve governance frameworks.
As part of this workstream, we focused on researching, developing and communicating on, e.g., best practices, access levels for dangerous capability evaluations, safe harbors, the limitations of evaluations, incentives for a healthy evaluation ecosystem, and on connecting evaluation results to broader governance mechanisms.
This work informed our input into the E.U.’s General-Purpose AI Code of Practice and multiple U.S. bills, as well as several research publications:
‘Pre-Deployment Information Sharing: A Zoning Taxonomy for Precursory Capabilities’. In this paper, presented at UK AISI’s Conference on Frontier AI Safety Frameworks, we built on the Frontier AI Safety Commitments and explained how a zoning taxonomy of precursory capabilities (i.e., smaller preliminary components to high-impact capabilities) could provide select government actors—such as U.K. AISI and U.S. CAISI—with situational awareness on frontier AI capabilities, while preserving information security.
‘Capturing and Countering Threats to National Security: a Blueprint for an Agile AI Incident Regime’. In this paper, we proposed a no-regrets blueprint for an AI incident regime that would allow nation-states to track and swiftly counter national security threats posed by AI systems, with each component of our proposal reflecting best practices in existing incident regimes in nuclear power, aviation, and biosafety.
‘Towards Frontier Safety Policies Plus’. In this paper, presented at the inaugural International Association for Safe and Ethical AI Conference, we built on our earlier work and explained how precursory capabilities could also serve as more granular tripwires in Frontier Safety Policies (FSPs).
2. Bespoke science-communication, ‘demo’ development, and policy recommendations on AI scheming.
Our second workstream has informed decision makers about our organisation’s core technical and governance research, and research results. As part of this workstream, we have developed multiple privately held demonstrations and specialized briefing materials, and provided verbal and written advice and briefings upon request, on topics such as evaluation-based policy frameworks, scheming and loss of control, internal deployment, and incident monitoring frameworks.
Over the last few months, we have met and engaged with an array of international stakeholders representing multiple governments, government-adjacent bodies and multilateral organizations. This includes, for example, members of the E.U. AI Office; the U.S. Center for AI Standards and Innovation; the U.K. AI Security Institute; the Korean AI Safety Institute; Singapore’s Infocomm Media Development Authority; the French AI Safety Institute; officers from multiple agencies within the U.S. intelligence community; staffers at the Senate Subcommittee on Emerging Threats and Spending Oversight, the House Select Committee on the Chinese Communist Party, and the Senate Commerce Committee; the offices of Members of the U.S. Congress; the U.S. Department of State; and U.K. Parliamentarians and members of the House of Lords.
As part of our public facing engagements, we were invited to present our work at events including the French AI Action Summit and the United Nations ITU AI for Good Summit, participated in the inaugural AI Safety Institute network meeting, and attended the Singapore Consensus on Global AI Safety Research.
3. Framing the need for a ‘governance of internal deployment’ from a governance, risk and legal perspective.
Our third workstream focused on conducting research and raising awareness on a timely, neglected and important area: the internal deployment of highly advanced AI systems. As part of this workstream, we published a landmark report on the governance, or lack thereof, of internal deployment and usage of highly advanced AI systems.
In ‘AI Behind Closed Doors: A Primer on The Governance of Internal Deployment’ we conceptualised and reflected on internal deployment, the relevant threat models, learnings from internal deployment in other safety-critical industries, the legal landscape, and effective solutions.
We are in the process of sharing this research with a range of governmental stakeholders, civil society and industry.
Until the end of the year, we plan to go into more depth on some of the aforementioned workstreams and research areas, including through collaboration with other organisations in the field. This will support our future engagements and, where appropriate, result in bespoke policy advice, reports and other publications.
Please contact us if you are interested in learning more: info@apolloresearch.ai
* We define scheming to describe an AI system secretly and systematically pursuing objectives that are not shared by the user or developer. You can learn more about our work on scheming here and here.
** You can find a previous update on our policy positions here.