Transformative technologies are nothing new to humanity. On July 16, 1945, the world learned the meaning of being potentially destroyed. A bomb detonated in a remote desert, more than 1,000 times more powerful than any weapon used before, changed international relations forever. The nuclear age brought an entirely new level of existential risk. As we enter a new frontier of potentially civilization-ending technology, the parallel lessons from the governance of nuclear weapons are striking.

AI: An Existential Risk with the Potential to Rapidly Escalate

First, both are capable of causing existential risk. In the nuclear age, that meant the complete, immediate end of human civilization. In the AI age, the existential threat may not be limited to the risk of total annihilation. The sources of risks, such as advanced military applications of AI (autonomous weapons), deepfakes (synthetic media), or general AI (AGI), can also include massive social and economic disruption, political instability, and a rapid, uncontrollable escalation of conflict.

There is a second crucial similarity: both nuclear technology and AI have the potential to rapidly expand out of control. The same applies to nuclear weapons. 

Jason Y. Moore, “The Dangers of Artificial Intelligence”

Moore is correct that the ‘quick’ component is as important as the existence of the risks. In the nuclear age, the speed of escalation was driven by the geopolitical competition and arms race between the United States and the Soviet Union in the Cold War.. The Cuban Missile Crisis brought the world to the brink of nuclear war in just 13 days.

In today’s AI race, there are multiple competitors at once: countries, corporations, academia, research labs. Famous examples include Perplexity (company), China (country), and Sam Altman (OpenAI CEO). With little transparency and even less international coordination, the AI arms race has already started.

The AI community must therefore act to develop governance now.

Borrowing Lessons from the Nuclear Age for AI Governance

Lesson 1: Start with Transparency and Confidence-Building Measures 

The first steps toward nuclear arms control started with transparency and confidence-building measures. Confidence was gained with the introduction of bilateral and multilateral agreements, such as SALT, the later START treaties, and joint verification protocols for nuclear weapons inspections, site visits, and other data sharing and fact-checking procedures.

In the AI community, transparency could include model reporting and evaluations: developers of powerful AI systems could be asked to share safety and best practices, model capabilities, and risk evaluations before releasing their model or technology into the world. Disclosure wouldn’t need to include details of the proprietary technology of these models, as was the case with the SALT agreements, in which states agreed to report the number and type of deployed nuclear weapons but didn’t have to expose national military secrets.

Hotlines could also be established between AI powers to ensure that misinterpretation of AI behavior or inadvertent use of autonomous weapon systems don’t spark dangerous geopolitical escalation in a crisis, such as happened with Washington and Moscow back then.

Lesson 2: Establish Norms Before Crises 

Norms in the nuclear age came slowly – and often after tragedy. The first nuclear weapon test took place before the bombings of Hiroshima and Nagasaki. It would be another 23 years until the NPT was agreed.

The AI community has an opportunity to act before tragedy strikes. Norms around the non-use of autonomous lethal weapons, truthful AI-generated content, or human-in-the-loop oversight can be shaped now instead of in response to mis- or abuse cases and tragedies.

In fact, civil society, academia, and international organizations such as the United Nations have a major role to play here. The 2023 UN General Assembly resolution calling for “safe, secure and trustworthy AI” might be one of the first steps toward such pre-norm-setting that led to nuclear treaties.

Lesson 3: Institutionalize Governance 

Another key feature of the nuclear age is the institutionalization of governance: the IAEA was one of the most enduring ones.

AI could also require its own institutions: a world AI agency could coordinate global research into safety standards, manage conflict or disputes, or ensure fair access to the benefits of the technology.

Unlike the IAEA, an AI equivalent institution would have to cover a much wider range of domains, from the usual military and security concerns to economic disruption and unemployment, government surveillance and new forms of disinformation, and more.

Some of the early work is already underway. The OECD AI Policy Observatory, UNESCO’s work on AI ethics, or a proposed International AI Safety Institute are all steps in the right direction, but these efforts remain too fragmented and weak compared to the influence and reach of the technology itself.

Lesson 4: Control Proliferation Without Stifling Peaceful Use 

Another major challenge of the nuclear governance regime has been the need to balance non-proliferation with the right to access peaceful nuclear energy use. The NPT recognized the right of nations to use nuclear energy while banning proliferation.

AI is facing a similar tension between non-proliferation or control of dangerous use cases and the proliferation of open-source models, easy-to-use tools, and low-cost access to the same underlying technologies. AI technologies have, in a sense, already become “too cheap to meter.”

AI governance, therefore, needs a more nuanced and tiered approach: low-risk tools and applications can remain open, while the most powerful, cutting-edge models at the risk of misuse should be subject to export control or at least public scrutiny and safety review. This is similar to the controls on “dual-use” technologies for nuclear material, which can be used both for military and peaceful purposes.

Lesson 5: Public Engagement and Democratic Oversight Matter 

The tragic reality about nuclear governance is that most of it happened in secret, with little public or civil society engagement. Military and political elites were in the driver’s seat. It took decades and public protest and pressure for disarmament, test bans, and concern about the long-term environmental impact to take hold.

AI governance, in contrast, should be a highly democratized process. Input from the public, interdisciplinary review boards, and engagement with a wide range of underrepresented groups and communities can help ensure that decisions aren’t made just by or on behalf of the interests of the most powerful states or technology monopolies.

Citizens’ assemblies on AI, academic and ethics councils, and youth and minority engagement on AI policy are just some of the possible ways AI governance can become a more bottom-up, people-centered process.

Conclusion 

As history has shown us, humans often build safety nets after the fact. But as the parallel lessons from nuclear arms control and governance show, with some political will, foresight, and cooperation, it is possible to build a governance net before the fall.

AI governance must be built not after the Hiroshima moment of AI but before it. The stakes are too high to leave it to chance, whether those stakes are measured in human dignity, societal resilience, or, ultimately, survival.

If AI governance starts by borrowing hard-earned lessons from the nuclear age, then the AI community now has a responsibility to act and build a safer and more resilient world with norms, institutions, safeguards, and, most importantly, trust before the technology outpaces our control or ability to stop it. Just like with nuclear weapons, the choice is ours, and the clock has already started ticking.