skibbley

Posted by Bruce Schneier

https://www.schneier.com/blog/archives/2026/03/canada-needs-nationalized-public-ai.html

https://www.schneier.com/?p=71692

Canada has a choice to make about its artificial intelligence future. The Carney administration is investing $2-billion over five years in its Sovereign AI Compute Strategy. Will any value generated by “sovereign AI” be captured in Canada, making a difference in the lives of Canadians, or is this just a passthrough to investment in American Big Tech?

Forcing the question is OpenAI, the company behind ChatGPT, which has been pushing an “OpenAI for Countries” initiative. It is not the only one eyeing its share of the $2-billion, but it appears to be the most aggressive. OpenAI’s top lobbyist in the region has met with Ottawa officials, including Artificial Intelligence Minister Evan Solomon.

All the while, OpenAI was less than open. The company had flagged the Tumbler Ridge, B.C., shooter’s ChatGPT interactions, which included gun-violence chats. Employees wanted to alert law enforcement but were rebuffed. Maybe there is a discussion to be had about users’ privacy. But even after the shooting, the OpenAI representative who met with the B.C. government said nothing.

When tech billionaires and corporations steer AI development, the resultant AI reflects their interests rather than those of the general public or ordinary consumers. Only after the meeting with the B.C. government did OpenAI alert law enforcement. Had it not been for the Wall Street Journal’s reporting, the public would not have known about this at all.

Moreover, OpenAI for Countries is explicitly described by the company as an initiative “in co-ordination with the U.S. government.” And it’s not just OpenAI: all the AI giants are for-profit American companies, operating in their private interests, and subject to United States law and increasingly bowing to U.S. President Donald Trump. Moving data centres into Canada under a proposal like OpenAI’s doesn’t change that. The current geopolitical reality means Canada should not be dependent on U.S. tech firms for essential services such as cloud computing and AI.

While there are Canadian AI companies, they remain for-profit enterprises, their interests not necessarily aligned with our collective good. The only real alternative is to be bold and invest in a wholly Canadian public AI: an AI model built and funded by Canada for Canadians, as public infrastructure. This would give Canadians access to the myriad of benefits from AI without having to depend on the U.S. or other countries. It would mean Canadian universities and public agencies building and operating AI models optimized not for global scale and corporate profit, but for practical use by Canadians.

Imagine AI embedded into health care, triaging radiology scans, flagging early cancer risks and assisting doctors with paperwork. Imagine an AI tutor trained on provincial curriculums, giving personalized coaching. Imagine systems that analyze job vacancies and sectoral and wage trends, then automatically match job seekers to government programs. Imagine using AI to optimize transit schedules, energy grids and zoning analysis. Imagine court processes, corporate decisions and customer service all sped up by AI.

We are already on our way to having AI become an inextricable part of society. To ensure stability and prosperity for this country, Canadian users and developers must be able to turn to AI models built, controlled, and operated publicly in Canada instead of building on corporate platforms, American or otherwise.

Switzerland has shown this to be possible. With funding from the federal government, a consortium of academic institutions—ETH Zurich, EPFL, and the Swiss National Supercomputing Centre—released the world’s most powerful and fully realized public AI model, Apertus, last September. Apertus leveraged renewable hydropower and existing Swiss scientific computing infrastructure. It also used no illegally pirated copyrighted material or poorly paid labour extracted from the Global South during training. The model’s performance stands at roughly a year or two behind the major corporate offerings, but that is more than adequate for the vast majority of applications. And it’s free for anyone to use and build on.

The significance of Apertus is more than technical. It demonstrates an alternative ownership structure for AI technology, one that allocates both decision-making authority and value to national public institutions rather than foreign corporations. This vision represents precisely the paradigm shift Canada should embrace: AI as public infrastructure, like systems for transportation, water, or electricity, rather than private commodity.

Apertus also demonstrates a far more sustainable economic framework for AI. Switzerland spent a tiny fraction of the billions of dollars that corporate AI labs invest annually, demonstrating that the frequent training runs with astronomical price tags pursued by tech companies are not actually necessary for practical AI development. They focused on making something broadly useful rather than bleeding edge—trying dubiously to create “superintelligence,” as with Silicon Valley—so they created a smaller model at much lower cost. Apertus’s training was at a scale (70 billion parameters) perhaps two orders of magnitude lower than the largest Big Tech offerings.

An ecosystem is now being developed on top of Apertus, using the model as a public good to power chatbots for free consumer use and to provide a development platform for companies prioritizing responsible AI use, and rigorous compliance with laws like the EU AI Act. Instead of routing queries from those users to Big Tech infrastructure, Apertus is deployed to data centres across national AI and computing initiatives of Switzerland, Australia, Germany, and Singapore and other partners.

The case for public AI rests on both democratic principles and practical benefits. Public AI systems can incorporate mechanisms for genuine public input and democratic oversight on critical ethical questions: how to handle copyrighted works in training data, how to mitigate bias, how to distribute access when demand outstrips capacity, and how to license use for sensitive applications like policing or medicine. Or how to handle a situation such as that of the Tumbler Ridge shooter. These decisions will profoundly shape society as AI becomes more pervasive, yet corporate AI makes them in secret.

By contrast, public AI developed by transparent, accountable agencies would allow democratic processes and political oversight to govern how these powerful systems function.

Canada already has many of the building blocks for public AI. The country has world-class AI research institutions, including the Vector Institute, Mila, and CIFAR, which pioneered much of the deep learning revolution. Canada’s $2-billion Sovereign AI Compute Strategy provides substantial funding.

What’s needed now is a reorientation away from viewing this as an opportunity to attract private capital, and toward a fully open public AI model.

This essay was written with Nathan E. Sanders, and originally appeared in The Globe and Mail.

https://www.schneier.com/blog/archives/2026/03/canada-needs-nationalized-public-ai.html

https://www.schneier.com/?p=71692

Posted by Bruce Schneier

https://www.schneier.com/blog/archives/2026/03/new-attack-against-wi-fi.html

https://www.schneier.com/?p=71711

It’s called AirSnitch:

Unlike previous Wi-Fi attacks, AirSnitch exploits core features in Layers 1 and 2 and the failure to bind and synchronize a client across these and higher layers, other nodes, and other network names such as SSIDs (Service Set Identifiers). This cross-layer identity desynchronization is the key driver of AirSnitch attacks.

The most powerful such attack is a full, bidirectional machine-in-the-middle (MitM) attack, meaning the attacker can view and modify data before it makes its way to the intended recipient. The attacker can be on the same SSID, a separate one, or even a separate network segment tied to the same AP. It works against small Wi-Fi networks in both homes and offices and large networks in enterprises.

With the ability to intercept all link-layer traffic (that is, the traffic as it passes between Layers 1 and 2), an attacker can perform other attacks on higher layers. The most dire consequence occurs when an Internet connection isn’t encrypted­—something that Google recently estimated occurred when as much as 6 percent and 20 percent of pages loaded on Windows and Linux, respectively. In these cases, the attacker can view and modify all traffic in the clear and steal authentication cookies, passwords, payment card details, and any other sensitive data. Since many company intranets are sent in plaintext, traffic from them can also be intercepted.

Even when HTTPS is in place, an attacker can still intercept domain look-up traffic and use DNS cache poisoning to corrupt tables stored by the target’s operating system. The AirSnitch MitM also puts the attacker in the position to wage attacks against vulnerabilities that may not be patched. Attackers can also see the external IP addresses hosting webpages being visited and often correlate them with the precise URL.

Here’s the paper.

https://www.schneier.com/blog/archives/2026/03/new-attack-against-wi-fi.html

https://www.schneier.com/?p=71711

Posted by Bruce Schneier

https://www.schneier.com/blog/archives/2026/03/anthropic-and-the-pentagon.html

https://www.schneier.com/?p=71742

OpenAI is in and Anthropic is out as a supplier of AI technology for the US defense department. This news caps a week of bluster by the highest officials in the US government towards some of the wealthiest titans of the big tech industry, and the overhanging specter of the existential risks posed by a new technology powerful enough that the Pentagon claims it is essential to national security. At issue is Anthropic’s insistence that the US Department of Defense (DoD) could not use its models to facilitate “mass surveillance” or “fully autonomous weapons,” provisions the defense secretary Pete Hegseth derided as “woke.”

It all came to a head on Friday evening when Donald Trump issued an order for federal government agencies to discontinue use of Anthropic models. Within hours, OpenAI had swooped in, potentially seizing hundreds of millions of dollars in government contracts by striking an agreement with the administration to provide classified government systems with AI.

Despite the histrionics, this is probably the best outcome for Anthropic—and for the Pentagon. In our free-market economy, both are, and should be, free to sell and buy what they want with whom they want, subject to longstanding federal rules on contracting, acquisitions, and blacklisting. The only factor out of place here are the Pentagon’s vindictive threats.

AI models are increasingly commodified. The top-tier offerings have about the same performance, and there is little to differentiate one from the other. The latest models from Anthropic, OpenAI and Google, in particular, tend to leapfrog each other with minor hops forward in quality every few months. The best models from one provider tend to be preferred by users to the second, or third, or 10th best models at a rate of only about six times out of 10, a virtual tie.

In this sort of market, branding matters a lot. Anthropic and its CEO, Dario Amodei, are positioning themselves as the moral and trustworthy AI provider. That has market value for both consumers and enterprise clients. In taking Anthropic’s place in government contracting, OpenAI’s CEO, Sam Altman, vowed to somehow uphold the same safety principles Anthropic had just been pilloried for. How that is possible given the rhetoric of Hegseth and Trump is entirely unclear, but seems certain to further politicize OpenAI and its products in the minds of consumers and corporate buyers.

Posturing publicly against the Pentagon and as a hero to civil libertarians is quite possibly worth the cost of the lost contracts to Anthropic, and associating themselves with the same contracts could be a trap for OpenAI. The Pentagon, meanwhile, has plenty of options. Even if no big tech company was willing to supply it with AI, the department has already deployed dozens of open weight models—whose parameters are public and are often licensed permissively for government use.

We can admire Amodei’s stance, but, to be sure, it is primarily posturing. Anthropic knew what they were getting into when they agreed to a defense department partnership for $200m last year. And when they signed a partnership with the surveillance company Palantir in 2024.

Read Amodei’s statement about the issue. Or his January essay on AIs and risk, where he repeatedly uses the words “democracy” and “autocracy” while evading precisely how collaboration with US federal agencies should be viewed in this moment. Amodei has bought into the idea of using “AI to achieve robust military superiority” on behalf of the democracies of the world in response to the threats from autocracies. It’s a heady vision. But it is a vision that likewise supposes that the world’s nominal democracies are committed to a common vision of public wellbeing, peace-seeking and democratic control.

Regardless, the defense department can also reasonably demand that the AI products it purchases meet its needs. The Pentagon is not a normal customer; it buys products that kill people all the time. Tanks, artillery pieces, and hand grenades are not products with ethical guard rails. The Pentagon’s needs reasonably involve weapons of lethal force, and those weapons are continuing on a steady, if potentially catastrophic, path of increasing automation.

So, at the surface, this dispute is a normal market give and take. The Pentagon has unique requirements for the products it uses. Companies can decide whether or not to meet them, and at what price. And then the Pentagon can decide from whom to acquire those products. Sounds like a normal day at the procurement office.

But, of course, this is the Trump administration, so it doesn’t stop there. Hegseth has threatened Anthropic not just with loss of government contracts. The administration has, at least until the inevitable lawsuits force the courts to sort things out, designated the company as “a supply-chain risk to national security,” a designation previously only ever applied to foreign companies. This prevents not only government agencies, but also their own contractors and suppliers, from contracting with Anthropic.

The government has incompatibly also threatened to invoke the Defense Production Act, which could force Anthropic to remove contractual provisions the department had previously agreed to, or perhaps to fundamentally modify its AI models to remove in-built safety guardrails. The government’s demands, Anthropic’s response, and the legal context in which they are acting will undoubtedly all change over the coming weeks.

But, alarmingly, autonomous weapons systems are here to stay. Primitive pit traps evolved to mechanical bear traps. The world is still debating the ethical use of, and dealing with the legacy of, land mines. The US Phalanx CIWS is a 1980s-era shipboard anti-missile system with a fully autonomous, radar-guided cannon. Today’s military drones can search, identify and engage targets without direct human intervention. AI will be used for military purposes, just as every other technology our species has invented has.

The lesson here should not be that one company in our rapacious capitalist system is more moral than another, or that one corporate hero can stand in the way of government’s adopting AI as technologies of war, or surveillance, or repression. Unfortunately, we don’t live in a world where such barriers are permanent or even particularly sturdy.

Instead, the lesson is about the importance of democratic structures and the urgent need for their renovation in the US. If the defense department is demanding the use of AI for mass surveillance or autonomous warfare that we, the public, find unacceptable, that should tell us we need to pass new legal restrictions on those military activities. If we are uncomfortable with the force of government being applied to dictate how and when companies yield to unsafe applications of their products, we should strengthen the legal protections around government procurement.

The Pentagon should maximize its warfighting capabilities, subject to the law. And private companies like Anthropic should posture to gain consumer and buyer confidence. But we should not rest on our laurels, thinking that either is doing so in the public’s interest.

This essay was written with Nathan E. Sanders, and originally appeared in The Guardian.

https://www.schneier.com/blog/archives/2026/03/anthropic-and-the-pentagon.html

https://www.schneier.com/?p=71742