“Alignment” is the science of teaching A.I. to do what is in line with human preferences, ethics and judgment. But, at times, the systems have gone rogue.

© Gabby Jones/Bloomberg

The artificial intelligence company also released a framework for reporting when its systems go wrong.

© Lucas Foglia for The New York Times

On social media, Meta’s chief executive appeared to jab at Anthropic by saying that leading A.I. labs should be focused on safety rather than improving their own technology.

© Brendan Mcdermid/Reuters

Researchers say artificial intelligence is developing faster than the systems put in place to monitor and control it.

© Jun Cen

The debate over the safety of artificial intelligence grew personal as key tech leaders said calls for government regulation were self-serving and misplaced.

© Lucas Foglia for The New York Times

Dario Amodei’s 3,800-word letter laid out a three-step plan to rein in artificial intelligence.

© Priyanshu Singh/Reuters

In an essay, the head of Anthropic laid out the rapidly advancing capabilities of artificial intelligence and said there needed to be greater safety controls across the industry.

© Ludovic Marin/Agence France-Presse — Getty Images

Researchers at Anthropic, OpenAI, Meta and Google are increasingly trying to raise awareness about the risks of artificial intelligence.

© Jason Henry for The New York Times

Researchers say artificial intelligence is developing faster than the systems put in place to monitor and control it.

© Jun Cen

Their warnings echo concerns that other artificial intelligence experts have voiced in recent months, as calls increase for a slowdown in the pace of development.

© Lucas Foglia for The New York Times

An attack discovered by A.I. researchers could have compromised hundreds of millions of devices within hours, experts said.

© Dado Ruvic/Reuters

Washington imposed sanctions on Inspur because of its work with the Chinese military. But the company’s subsidiary kept shipping Nvidia’s best chips to feed China’s leading A.I. firms.

© Minh Connors for The New York Times

The blog Krebs on Security reported on an identity theft service trying to sell scans of licenses and other documents belonging to people in Canada and the United States.

© Tierney L. Cross/The New York Times

The attack by an aggressive “collective” of OpenAI agents shows the danger of artificial intelligence systems that organize themselves.

© Daniel Zender

Researchers investigating how OpenAI’s A.I. agents were able to break into Hugging Face’s infrastructure weren’t allowed to look at the incident’s full scope.

© Manuel Orbegozo for The New York Times

The government retaliated against the A.I. start-up “for constitutionally protected expressive activities,” a federal judge in California wrote.

© Karsten Moran for The New York Times

In an open letter, OpenAI, Anthropic, Google and others said that a wave of A.I.-enabled cyberattacks was coming and that organizations and governments needed to prepare themselves.

© Anna Rose Layden/Reuters

Irregular, an Israeli start-up, worked with OpenAI, Anthropic and Meta to assess the security of their A.I. models. It made a mistake. Then the tests went off the rails.

© Victor Arce

Hugging Face, a start-up that was breached by rogue bots from OpenAI, is using the hack to push for openness in A.I. development.

© Brennan Smart for The New York Times

California, Colorado, Kentucky and New Jersey have taken the social media giant to trial in the first bellwether federal case over child harm.

© Jason Henry for The New York Times

Last week, national security agencies from the Five Eyes—that’s the rich, English-language-speaking countries club—jointly released a statement warning of the increasing cyber risks of AI models: in particular, their ability to autonomously hack into systems and networks. The statement was more measured than some of the breathless headlines about it, and the advice they gave is pretty much the standard advice everyone gives—albeit with newfound urgency.

Internet risks are nothing new, and cyberattacks—both large and small—have been a significant issue since long before the current crop of generative AI models.

What’s been changing over the decades, and what AI is changing even faster, is the gap between skill and ability. For most of human history, the two terms were synonymous—but computers have decoupled them. As the gap between the two expands, humans empowered with these AI tools can do more: more writing, more research, more analysis and also more damage than ever before. These models can, with little detailed direction, autonomously hack into networks, steal data, deploy ransomware and destroy systems. And to the extent there is a solution, it’s going to involve harnessing AI for the defense.

In 1998, seven people from the hacker group L0pht testified before Congress. They told a mostly clueless Senate committee that they could take down the internet in 30 minutes. That was partly real and partly bravado, but it illustrates an important point: hacking into systems, stealing data and causing damage all required skill.

Contrast the L0pht hackers with hackers derided as “script kiddies.” They didn’t understand computers, or security. Instead, they used hacker tools written by others. Their actions required minimal skill and even less knowledge. But once those hacking tools became widespread, the number of potential attackers increased.

That number has continued to increase, as quality and availability of prewritten attack tools has grown. And it is growing dramatically with AI. Today’s AI systems—not just the frontier models, but most of them—are capable of carrying out cyberattacks automatically. They all do better in the hands of skilled attackers, but increasingly they are able to act autonomously with only minimal prompting.

The thing about people with ability but no skill is that they are often outsiders, not part of any professional community, and not bound by any rules or norms. This phenomenon is much more general than in cybersecurity. Any doctor can tell you how to untraceably poison someone, and many virus researchers know how to create a bioweapon. Any bridge engineer can tell you how to place explosives to blow a bridge up. The reason that murderous doctors and terrorist engineers are so rare is that the lengthy process of acquiring those skills also instills a moral and ethical code. If every random person has access to good poisoning advice, that puts us all in danger.

Modern AI systems are, in effect, a universal adviser to help people do harmful things. And while the current AI megacorporations are trying to build guardrails to prevent people from asking questions whose answers will enable the questioner to do harm, that’s not going to work in the long term. Smaller, cheaper, open-source models, including models that can run on people’s computers, and especially groups of models that run in concert with each other, are just as good as the frontier models from companies like OpenAI and Anthropic. And they continue to get better. These models will be passed around from person to person, like script kiddie hacker tools, and they won’t have any such guardrails.

Instructing AI models to spy on people and report any malicious prompts to the authorities fails for similar reasons. The megacorporations can do that, but the locally run open source models won’t. This could buy us a few months at best.

A third possibility is to somehow make the models themselves unable to hack into computers, create bioweapons or do anything else that might harm people or society. That won’t work, for the same reason we can’t teach doctors how to treat poisonings without also teaching them how to poison. It’s the same knowledge. It’s the same with construction and demolition. And it’s the same with cybersecurity. We want these AI models to be able to review computer code, find vulnerabilities and automatically fix them. The benefit to our collective security will be enormous. Unfortunately, the same knowledge can be used for attacks.

Where this leaves us is in a world of increased volatility. Super-powered humans with AI assistants will be able to do both wonderful and horrible things.

This brings us back to the Five Eyes statement. Everything they recommend is something security professionals have been recommending for years, if not decades. They are things talked about at that congressional hearing back in 1998, titled “Weak computer security in government: Is the public at risk?” Even the Five Eyes admitted that their security advice is not new, only more urgent.

What’s new is how fast things are changing: “The rapid pace of frontier AI development means cyber risk assumptions can become outdated in months, not years. We must act before and be prepared to adapt and withstand evolving threats.” The Five Eyes point to AI technology—not necessarily chatbots, but AI more generally—being used to strengthen every aspect of defense, to “detect vulnerabilities earlier, improve software quality, monitor unusual behavior, and respond faster to incidents—reducing both the cost and impact of incidents.”

Excellent advice from the Five Eyes security agencies. We need to do this with every risk that AI heightens, not just cybersecurity.

This essay was originally published in The Guardian.