Over the weekend Dario Amodei who is the CEO of Anthropic called for the slow down of AI development:
But like many technologies before it, AI brings risks, and because it is such a powerful technology, these risks are serious. I’ve writtena lot about them too. They include the risk of losing control of AI systems, misuse of AI for cyberattacks and bioterrorism, and serious economic disruption. A race to the bottom, spurred by commercial incentives, can make these risks more acute.
Within hours on Saturday, OpenAI chief executive Sam Altman and SpaceXAI founder Elon Musk quickly voiced their support for Amodei’s ideas. But the core issue is this: Can you believe any or all of them?
I would argue no. I’ve been record for saying that companies are deploying AI faster than guardrails can go up. More on that in a bit.
Bri Frost, Director of Product Management, Cloud Range had this to say:
“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.
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, we’d never ship anything. But the opposite extreme is just as reckless: accelerating capability while just assuming we’ll bolt the security controls on afterward and they’ll 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 yesterday’s jailbreak isn’t just a clever prompt anymore — it’s an execution path. That’s 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 wouldn’t excuse it because they were ‘innovating quickly’.
So why are we treating AI differently?
You don’t 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 – That’s not the standard.
But if you ship the product, you inherit responsibility for securing it. And continuing to secure it better!
The conversation shouldn’t 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 we’re going to keep accelerating — which I believe we will — then independent testing, adversarial evaluation, isolated testing environments, containment, continuous validation and security-by-design can’t remain optional steps we add after the innovation happens.
The faster we build the engine, the more important the brakes become.”
AI companies need to figure this out. And governments need to step is if AI companies cannot figure this out. It honestly is that simple.
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This entry was posted on September 14, 2026 at 9:13 am and is filed under Commentary with tags Anthropic. You can follow any responses to this entry through the RSS 2.0 feed.
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Anthropic CEO Calls For The Slowing Down Of AI Development…. But Can You Believe Him
Over the weekend Dario Amodei who is the CEO of Anthropic called for the slow down of AI development:
But like many technologies before it, AI brings risks, and because it is such a powerful technology, these risks are serious. I’ve writtena lot about them too. They include the risk of losing control of AI systems, misuse of AI for cyberattacks and bioterrorism, and serious economic disruption. A race to the bottom, spurred by commercial incentives, can make these risks more acute.
Within hours on Saturday, OpenAI chief executive Sam Altman and SpaceXAI founder Elon Musk quickly voiced their support for Amodei’s ideas. But the core issue is this: Can you believe any or all of them?
I would argue no. I’ve been record for saying that companies are deploying AI faster than guardrails can go up. More on that in a bit.
Bri Frost, Director of Product Management, Cloud Range had this to say:
“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.
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, we’d never ship anything. But the opposite extreme is just as reckless: accelerating capability while just assuming we’ll bolt the security controls on afterward and they’ll 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 yesterday’s jailbreak isn’t just a clever prompt anymore — it’s an execution path. That’s 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 wouldn’t excuse it because they were ‘innovating quickly’.
So why are we treating AI differently?
You don’t 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 – That’s not the standard.
But if you ship the product, you inherit responsibility for securing it. And continuing to secure it better!
The conversation shouldn’t 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 we’re going to keep accelerating — which I believe we will — then independent testing, adversarial evaluation, isolated testing environments, containment, continuous validation and security-by-design can’t remain optional steps we add after the innovation happens.
The faster we build the engine, the more important the brakes become.”
AI companies need to figure this out. And governments need to step is if AI companies cannot figure this out. It honestly is that simple.
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This entry was posted on September 14, 2026 at 9:13 am and is filed under Commentary with tags Anthropic. You can follow any responses to this entry through the RSS 2.0 feed. You can leave a response, or trackback from your own site.