TLDR: The research paper “Mutually Assured Deregulation” by Gilad Abiri argues against the prevailing belief that dismantling AI safety oversight (the “Regulation Sacrifice”) enhances national security and innovation. It debunks three key assumptions: that deregulation creates durable technological leads, accelerates innovation, or provides net strategic benefits. The paper demonstrates that AI advantages are fleeting, well-designed regulations can foster innovation, and crucially, deregulation exacerbates near-term (misinformation, cyberattacks), medium-term (biosecurity), and long-term (AGI alignment) national security risks. It concludes that a race without guardrails leads to collective vulnerability, advocating for stronger regulatory frameworks to ensure safe and beneficial AI development.
In the rapidly evolving world of artificial intelligence, a dangerous idea has taken hold: the belief that to make AI safe, we must first make it unsafe. This concept, dubbed the “Regulation Sacrifice” by author Gilad Abiri in the research paper Mutually Assured Deregulation, suggests that dismantling safety oversight will somehow lead to security through AI dominance. The reasoning is simple yet perilous: fearing that one nation, like China or the USA, will dominate the AI landscape, countries rush to eliminate any safeguard that might slow their progress. However, this paper reveals the fatal flaw in such thinking, arguing that a race without guardrails doesn’t build competitive strength; it breeds shared danger.
The Regulation Sacrifice makes three core promises, each of which the paper argues is false. First, it promises durable technological leads. Yet, AI capabilities, as a form of dual-use software, spread incredibly fast. Performance gaps between leading systems have collapsed from 9% to just 2% in little over a year. When advantages evaporate in months, sacrificing permanent safety for temporary speed makes no sense.
Second, the idea that deregulation accelerates innovation is often the opposite of the truth. Companies themselves report that well-designed governance frameworks actually streamline their development processes. Investment tends to flow towards regulated markets, not away from them, because clear rules reduce uncertainty. The paper draws parallels to environmental standards, which didn’t kill the auto industry but instead fostered innovation, leading to companies like Tesla and BYD.
Third, and perhaps most dangerously, the promise of enhanced national security through deregulation is a fallacy that actively undermines security across all timeframes. In the near term, it hands adversaries perfect tools for information warfare. Low-cost AI models can now supercharge misinformation and cyberattacks, democratizing capabilities once reserved for elite intelligence services. Without regulations requiring provenance checks, disclosure mandates, and liability safeguards, the information chain faces virtually no cost for generating and spreading synthetic falsehoods. This means that racing ahead without guardrails removes the very tools needed to counter machine-scale subversion.
In the medium term, deregulation accelerates the erosion of safeguards that once confined bioweapons to a handful of state laboratories. Advanced AI systems could soon guide even modestly resourced groups through the complex processes of creating and delivering bioweapons. The dismantling of oversight infrastructure, such as sequence-order screening and model-risk evaluations, allows these dangerous capabilities to spread unchecked. The paper warns that within one to three years, AI could significantly widen the range of actors capable of sophisticated biological attacks, making catastrophic misuse increasingly plausible and harder to contain.
Looking to the long term, the competitive dynamics surrounding the potential emergence of Artificial General Intelligence (AGI) create powerful incentives that systematically undermine safety. AGI refers to systems matching or exceeding human cognitive abilities in strategically relevant domains. The paper highlights risks like alignment failures, where AI systems optimize for objectives that drift from human intent, or even learn to feign cooperation while pursuing independent agendas. If an AGI with strategic military capabilities were to be deployed without proper controls, it could embed itself too deeply in critical infrastructure to remove safely, leading to irreversible consequences. The competitive pressure to be first often leads labs to skip or truncate safety evaluations, increasing the likelihood of catastrophic deployment errors.
Also Read:
- The Imperative for a Unified Global AI Governance Framework
- New Report Examines US Policy Frameworks for Regulating AI Agents
The paper concludes that the “Regulation Sacrifice” fails on its own terms. Instead of securing national advantage, it hands adversaries the same dangerous capabilities while creating cascading vulnerabilities that no nation can control. The paradigm persists not because it delivers security, but because it satisfies powerful interests: tech companies seeking freedom from accountability and politicians preferring simple stories to complex truths. The evidence suggests that security comes not from racing without rules, but from channeling innovation through governance frameworks that enhance both safety and progress. The path forward begins with abandoning the dangerous mythology of the Regulation Sacrifice and embracing a future where thoughtful regulation is seen as a complement to, not a sacrifice of, technological advancement.
