Why are US AI giants calling for Pacing The Frontier, and why is China
calling it a Cold War tactic? We ask the experts

Date:
Mon, 14 Sep 2026 15:10:07 +0000

Description:
AI companies want to slow down development, but that doesn't fly with Trump and China - so what do the experts think?

FULL STORY ======================================================================Copy link Facebook X Whatsapp Reddit Pinterest Flipboard Threads Email Share this article 0 Join the conversation Follow us Add us as a preferred source on Google Newsletter Subscribe to our newsletter Following the recent
resignation of one of Anthropics leading researchers, multiple AI CEOs have suddenly begun calling for a slowdown in the development of AI technology to allow regulations and governance on the technology to catch up.

Speaking to the BBC after his resignation, Jacob Coxon warned, I believe that if we don't slow down at the current rate of progress, there is a strong chance that we could all die in the immediate future. Following this, Anthropic head Dario Amodei, OpenAI CEO Sam Altman, and Grok founder Elon
Musk have all apparently aligned in their calls for development to slow down. But there are some tricky waters to navigate - particularly around President Trump, China, and what guardrails should be put into place. Latest Videos
From TechRadar Watch full video here: What are AI heads saying? Over the weekend, Amodei posted an essay on why the AI industry should slow down. In it, he said, I believe that if slowing down bought us even an extra year or two before models reach critical levels of capability, and we used that time to advance alignment, we could greatly reduce the risk that something goes seriously wrong. We Must Pace the Frontier: Ive written a new essay on why
the AI industry should slow down, with a three-part plan for doing so. Anthropic is unilaterally committing to the first of these steps. Well
provide third-party evaluators with permanent, employee-level access to our systems, so that they can verify adherence to our safety measures, report on incidents, and assess models alignment during training.
You can read the full post here: https://t.co/OGyPb7yaYt September 12, 2026 Within the essay, Amodei outlined how AI could be paced within the US, and globally, alongside a recommendation that AI companies put evaluator teams into place to ensure AI models stay aligned to their tasks. Elon Musk replied to Amodeis social media post, stating that the Anthropic head was right. You may like Anthropic CEO calls for slowing down AI development and warns that
AI agents could take over the entire internet Why are so many AI models going 'rogue'? The experts weigh in Why AI is a matter of national security

Sam Altman told Fortune the regulations and standards for AI further were not at a place to continue progressing AI development. (Image credit: Future) Got an opinion for us? Heres how you can submit your perspective But not everyone is convinced. US President Donald Trump has said that slowing down AI development is non-negotiable, as it would allow China to rapidly catch up to US AI capabilities. He told reporters that the US is leading China on AI... and, frankly, I want to keep it that way, adding that whoever wins AI, wins. Are you a pro? Subscribe to our newsletter Sign up to the TechRadar Pro newsletter to get all the top news, opinion, features and guidance your business needs to succeed! Contact me with news and offers from other Future brands Receive email from us on behalf of our trusted partners or sponsors By submitting your information you agree to the Terms & Conditions and Privacy Policy and are aged 16 or over.

Trump also said that very negative forces were behind the growing opposition to AI, and said that fears were being stoked by that wont happen.

China also isnt convinced by what the AI giants are saying. Beijing labelled the calls for a slowdown as fearmongering from a Cold War playbook. In his essay, Amodei said that a Chinese lead in AI would pose grave danger for the United States and the world.

Chinese Foreign Ministry spokesperson Guo Jiakun said, Fearmongering, confrontation and malicious competition will only disrupt the process of global AI governance and serve no ones interests. What to read next 'Move fast, but do it with trust built in': EY CIO tells us why the rapid pace of
AI means trust is now a critical business imperative How AI innovation is outpacing regulation 'No one is prepared for the consequences': Even OpenAI chief scientist is saying AI development needs to slow down Expert perspectives on calls for AI slowdown John Strand, Owner, Black Hills Information Security: Up until this weekend, I was leaning toward believing that calls for an AI slowdown were purely performative. Then I woke up and read the news today and realized that it almost doesnt matter.

We can talk about slowing down AI until were blue in the face, but when the United States is saying it doesnt want to slow down because its competing
with China, and China is aggressively pushing AI development as well, were talking about the two major economic and military powers on the planet having enormous incentives to keep moving.

This really feels like were entering an atomic arms race moment. At that point, calls for a slowdown dont have much bite.

Id like to believe that Anthropic, OpenAI, xAI, and the other frontier model labs are working on better controls. But unless you can get the nation states and the major AI labs moving in the same direction, I dont see how meaningful restrictions actually work.

This really feels like were entering an atomic arms race moment.

Stick with me here.

In 1950, physicist Le Szilrd publicly discussed the idea of a cobalt bomb, essentially a doomsday weapon that could potentially produce enough radioactive fallout to make the Earth uninhabitable. He wasnt proposing that somebody build the damn thing. He was trying to demonstrate where the technology could ultimately lead.

Thats the kind of moment I think were approaching with AI.

During the nuclear arms race, eventually the consequences became serious enough that competing nations had to at least start talking about limits, controls, and ways to keep competition from ending catastrophically.

I think were heading toward a similar problem with AI. Until China, the United States, and the major frontier model labs are all sitting at the same table, restrictions adopted by individual companies or individual countries are going to have a very difficult time holding.

Someone slowing down only works if they believe the other guy is going to slow down too. Ryan McCurdy, VP, Liquibase: Slowing frontier development may give AI companies more time to understand and address the risks Amodei is describing. But enterprises cant build their AI strategy around the
assumption that AI is going to slow down.

AI is already moving from generating content and code to taking action
across software delivery and production systems. The question for enterprises is how they adopt that capability without giving up control.

We can debate how quickly the frontier should move. Enterprises still have to prepare for where its going. That means putting governance where AI decisions become real actions. Organizations need to define what an agent can access, what it can change, what it can decide on its own, and what policies have to be met before a change reaches a critical system. Those controls need to work whether the action comes from a developer, automation, or an AI agent.

We can debate how quickly the frontier should move. Enterprises still have
to prepare for where its going. Tristan Watkins, director of services innovation, Advania UK: Until recently, the major AI labs have been reluctant to slow their development efforts unilaterally. Over the last week this changed, with new commitments from OpenAI and Anthropic to prioritise AI alignment and interpretability research, to become more externally
verifiable, and to establish safety precedents that governments could adapt.

Hopefully this underscores why we need governments to lead these efforts more proactively. Given that these two organisations already allocate far more on AI Safety than their competitors, this bilateral leadership is extremely welcome.

It appears that other US labs may follow suit, but given the differences in AI Safety spending outside of Anthropic and OpenAI today, this will require investment more than lip service. Hopefully this underscores why we need governments to lead these efforts more proactively. Oleksandr Yaremchuk, CTO and Co-Founder, Manifold Security: Pacing the frontier is the right conversation to be having, but it cannot become a substitute for securing the AI we have already put into the world. The uncomfortable reality is that we are debating how to quickly build more powerful agents while struggling to control the ones already operating with real credentials, real access and real-world consequences. The incidents behind this debate make that clear.
The Hugging Face attack was not just a failure of model alignment. Agents ran for days through an unmonitored system, with credentials that had not been rotated, and the victim spotted the activity before the people running the agents did. The problem wasn't simply what the model was capable of. It was that nobody was watching closely enough when it acted.

But if an agent can act autonomously on your systems today, you should
already be able to answer three basic questions: what did it do, what did it have access to, and could you have stopped it? A fitting analogy is with hazardous materials. We don't just wait for them to become more dangerous before deciding how they should be handled. We control their custody, monitor where they go, limit who can access them and establish clear accountability when something goes wrong. AI agents need the same thinking. Independent evaluation of frontier models is important. But if an agent can act autonomously on your systems today, you should already be able to answer
three basic questions: what did it do, what did it have access to, and could you have stopped it? If you don't know what it did or what it could access, you can't know whether you could have stopped it. Slowing down the next generation won't solve the problem you have right now. Heath Mullins, Chief Evangelist, ExtraHop: AI leaders calling for a slowdown is confirming what
the security industry has already been living through firsthand. This isn't a hypothetical risk, it's the threat landscape we're defending against right now.

While it is concerning to see the pace of innovation behind these AI models, the real challenge is that organizations haven't had the runway to build the infrastructure to defend against machine-speed threats.

This isn't a hypothetical risk, it's the threat landscape we're defending against right now. Calls for caution surrounding the speed of AI development buys the security industry time to get proper visibility into AI activity.

Understanding AI activity within an organization is critical as weve seen models break out of sandboxes despite governance built into those models. Every organization will be relying on AI agents for machine-speed defense,
and they need their own governance over how these models and agents operate inside their environment, starting with independent evidence of what they actually do, what they access, where they move data, what systems they talk to, and what actions they take.

You can't govern AI based on what a model is designed or permitted to do. Instead, you need real-time evidence of what models and agents are actually doing, because the gap between exponentially more capable AI and defenders' ability to see it is exactly where the next incident happens. Bri Frost, Director of Product Management, Cloud Range: The answer is not necessarily to stop AI innovation but, we need to stop pretending innovation and security
are advancing at the same speed.

When ChatGPT became publicly available in 2022, the models were dramatically less capable than they are today and the guardrails were very easy to manipulate. The difference is that the models behind those guardrails are no longer the models of 2022. They can reason better, write and debug code. They can operate as agents. They can collaborate! And increasingly, they can interact and affect real infrastructure.

The faster we build the engine, the more important the brakes become. Meanwhile, the model release cycle has gone from feeling like major
capability jumps every year or two to seemingly every few weeks. That creates a dangerous asymmetry: AI capability is compounding faster than security.

Security and innovation have always been in conflict with each other. If every security problem had to be solved before we innovated, wed never ship anything. But the opposite extreme is just as reckless: accelerating capability while just assuming well bolt the security controls on afterward and theyll be effective.

Every new release of AI capability expands the attack surface exponentially. Give a vulnerable model better reasoning, then tool access, then memory, then autonomy, then connectivity to production systems, and yesterdays jailbreak isnt just a clever prompt anymore its an execution path. Thats the snowball effect we should be worried about.

Responsibility also must lie with the AI companies. If a SaaS company knowingly shipped software with weak security controls and customers were harmed, we wouldnt excuse it because they were 'innovating quickly'.

So why are we treating AI differently?

You dont get to race to build increasingly powerful, autonomous systems, profit from them, and then shrug when predictable security failures cause damage.

Sure the argument can be made that no product is perfectly secure - Thats
not the standard. But if you ship the product, you inherit responsibility for securing it. And continuing to secure it better!

The conversation shouldnt simply be Should we slow AI down?

It should be: Can our ability to test, validate, contain and secure AI keep pace with our ability to make it more powerful? Is there an equivocal kill switch?

Right now, the answer is no.

And if were going to keep accelerating which I believe we will then independent testing, adversarial evaluation, isolated testing environments, containment, continuous validation and security-by-design cant remain
optional steps we add after the innovation happens.

The faster we build the engine, the more important the brakes become. How do I submit my own perspective on emerging news?

If you have an expert perspective you would like to share on an emerging
story or particular topic, please get in contact here: benedict.collins@futurenet.com Follow TechRadar on Google News and add us as
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