Computerization has long allowed data collectors to track our locations, collect
lists of whom we communicate with, and monitor our spending habits -- unless we
use cash. What?s new is an unprecedented fusion of each of these mechanisms,
persistent and unrelenting. AI brings an analytical ability to spy on the
contents of our communications, and to answer sophisticated questions about our
whereabouts and activities: actions that previously required human analysts are
now automated. The result will be a kind of supercharged societal level of
chilling effects where fear, self-censorship and groupthink reign, and dissent,
creativity and innovation become increasingly rare.

In this atmosphere of fear and conformity, risky ideas, social activism and
self-reinvention -- especially by disfavored groups and targeted populations --
are also chilled. This will have long-term effects on social progress.

Consider the relatively recent societal normalization of same-sex relationships
and the recreational use of marijuana. Over the decades, those ideas slowly
progressed from being both immoral and illegal, to moral but still illegal, and
finally to both moral and legal. But in order for any of that to happen, there
had to be a counterculture that was able to experiment and eventually
demonstrate to the world that morality could change over time. To the extent
that AI surveillance chills this sort of experimentation in public or in
private, social progress becomes impossible.

There are no real historical precursors to this; these technologies are too new.
Even the most notorious and large-scale domestic surveillance program in US
history, the FBI?s use of wiretapping, physical mail opening, informants and
paper index cards to track alleged communists during the 1950s and 1960s,
appears genuinely archaic in light of modern AI-enhanced surveillance. So does
East Germany?s human-centric surveillance network during the cold war. Only
science fiction, from the likes of George Orwell or Aldous Huxley, comes close.
But even Big Brother?s ?telescreen? feels decidedly mid-20th-century by
comparison.

But we need not sit idly. Now that we recognize the danger of AI-enhanced mass
surveillance, we can make the policy choices not to implement it. Bans on facial
recognition and other forms of identification tech can slow development; robust
new privacy and data protections can restrict data tracking and retention; AI
regulations can curtail its most invasive uses; and structural reforms can help
us scrutinize and break up powerful state/tech cartels that pave the way for
technological excesses like AI surveillance.

The chill of AI-powered mass surveillance will suffocate the very foundations of
healthy democratic societies. But we can still choose a different path.

This essay was written with Jon Penney, and originally appeared in The Guardian.

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AI Data Centers and the Concentration of Wealth

[2026.07.13] Opposition to AI data centers has emerged as a primary theme in US
politics, one that -- surprisingly -- doesn?t fall along party lines. We applaud
people coming together for constructive debate on any issue, and agree that
communities need to evaluate whether any economic benefits these data centers
bring is worth their costs. Still, we worry that a focus on data centers
obscures the larger impacts of AI on people?s lives: the concentration of power
of AI companies, and their widespread political and financial influence.

Local data center opposition is grounded in legitimate concerns about
misallocation of land resources when housing is at a premium, pressures on
already higher energy prices, and localized environmental impact. Unlike other
resource-consuming and polluting industrial facilities, data centers produce
very few jobs. The fact that US opposition to data centers seems to be most
fierce among lower-income communities reflects righteous indignation with an
inequitable bargain, where tech companies and developers profit from exploiting
local resources but offer little in return. On a global scale, their carbon
footprint could grow unsustainably if usage accelerates. And all this is in aid
of a technology that many fear will propagate misinformation, take their jobs,
or even cause existential risks for humanity.

For some, data center opposition may feel like the only tangible mechanism for
registering their concern, disapproval, or even anger about AI. The problem is
that this may be exactly what the AI companies are banking on. They can overcome
the protest when it matters to them, and live with a significant fraction of
proposals being defeated. More importantly, focusing political opponents on the
data center issue obscures the bigger prize they?re after.

While there is a staggering three-quarters of a trillion dollars being spent on
data center infrastructure by US companies this year alone, this investment
should be taken in perspective. The market for enterprise software, for example,
is about twice this size. And it?s small compared with what these companies
actually want.

AI companies have their eyes set on capturing all the value created by entire
industries. The technology has arguably already conquered customer service and
consumer sales. But on the horizon are bigger targets, such as enterprise
software development, creative design, management and even legal services. In AI
companies and their allies? vision of the future, AI replaces teachers and
doctors. The companies would rather spend time fighting resistance to how fast
they are building computing infrastructure than dealing with issues of how their
products should be used in those fields, or how those fields should be protected
from their products.

And while data center opposition campaigns have been successful in building
widespread appeal, their effectiveness in the US is mixed. They seem to be most
successful when organizing against speculative, early-stage data center
proposals that have a relatively low likelihood to ever see fruition. Meanwhile,
advanced-stage, well-capitalized data center projects have proven to have the
resources to overcome local opposition. An OpenAI- and Oracle-backed facility in
Saline township, Michigan, is breaking ground on construction even after local
officials voted to reject it. The developers sued the town of 3,000 and forced a
settlement that involved their project going forward. Meanwhile, the Trump
administration, a vigorous ally of corporate AI, has signaled its willingness to
advance AI infrastructure development by overriding state objections and even
using federal lands.

Also consider that rampant data center development may be a momentary spike
rather than a longstanding concern. Demand for the centralized computing that
data centers provide may well decline over time. The leading Chinese labs, such
as Z.ai, are innovating in technical mechanisms to make frontier-class models
smaller and cheaper to run. AI power users have become adept at miniaturizing
open weight models, ones published free for anyone to download and use, to run
locally on their own computers. Apple and Google both support infrastructure
stacks for running AI models directly on mobile phones. It could be that the
current mania for data centers will look like the fiber optic cable bubble from
the early 2000s, as demand shifts to smaller models and AI usage on people?s own
devices.

For those concerned primarily with affordability and environmental protection,
singling out data center construction is misplaced. Energy rates and inflation
today seem to be most visibly affected by the US-Iran war. The US is
disinvesting in long-term energy security by ceding the renewable energy
industry to China and actively cancelling climate commitments. Consider that 10%
of global carbon emissions stem from heating buildings, which dwarfs energy use
by AI and could be cut fivefold by using heat pumps powered by renewable energy.
With respect to housing affordability, federal housing subsidies have changed
little over three decades, in inflation-adjusted terms, even as housing costs
have spiked and homeowners have enjoyed robust tax incentives.

As for AI itself, the concentration of power and wealth in these tech companies
is the greatest existential risk facing society today. This means we must limit
corporate power, especially corporations? ability to exploit the public and
manipulate our political system.

Opposing data centers should be just a starting point. We can advocate for
states to regulate AI, to reject irresponsible uses of the technology, and shape
corporate behavior. We can fight for AI computation to be taxed, so that the
public can capture some of the profit of AI use while also forcing AI companies
to internalize more of the energy and environmental consequences associated with
its use. And we all can join the global movement for Public AI, an alternative
ecosystem for AI that is developed under public control with an incentive
structure to create public benefit rather than private profit.

The US midterm elections present ample opportunity for those seeking to control
the AI political agenda. In the recent New York congressional Democratic
primary, PACs linked to the dueling AI companies Anthropic and OpenAI spent
millions of dollars lobbying for or against ?AI safety?, the idea that we must
urgently monitor and prevent people from using AI to cause catastrophic harms.
We?re already seeing a similar dynamic play out in races in Massachusetts and
other states.

Why would Anthropic and OpenAI -- bitter industry rivals but fundamentally on
the same side politically -- support opposing viewpoints? Because they both
ultimately profit from the mystique: the idea that their products are so
powerful that controlling those products is the world?s most important
challenge. Here?s the typical read on the dynamic. To one side (backed by OpenAI
affiliates), ?safety? comes from the appearance of US industry dominating AI
innovation, under the slow-moving control of federal lawmakers (and without
pesky state regulators in the way). To the other side (backed by Anthropic),
?safety? means a heavier regulatory framework that plays to Anthropic?s
posturing as the ethics- and compliance-focused AI vendor. In both cases, it?s
more marketing than principled concern about safety.

Political organizers should call out and reject the AI companies? framing of the
debate, and reorient campaign agendas around populist resistance to corporate
concentration of wealth and power. When AI companies pump millions into
legislative races, the result should not be hyperbolic discussion of AI
superintelligence. And when a plot of land in a small town is pitched as a data
center site, the debate should be about more than the local costs and benefits.
It should include out-of-control money in politics, and Citizens United-proof
solutions to limit corporate influence like public financing and state
regulation.

We all have a vested interest in what?s on the policy agenda, and what the
outcomes are. Today, the greatest risk AI poses to society is the exacerbation
of inequality and the concentration of wealth. The real problem is
trillion-dollar AI companies and their trillionaire oligarchs cozying up to
political power in Washington and governments worldwide, and using their money
to enact their agenda over the popular will of the people. This is the issue
we?d like to see put front and center, and it requires solutions much more
extensive than slowing data center development.

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

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Vulnerability in FIFA?s Network

[2026.07.14] FIFA?s network was vulnerable to anyone with even minimal access.

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Upcoming Speaking Engagements

[2026.07.14] This is a current list of where and when I am scheduled to speak:

    I?m speaking (virtually) at the Policy-Relevant Privacy Research Workshop
in Calgary, Canada, on Monday, July 20, 2026.
    I?m speaking at Boston Leadership Exchange in Boston, Massachusetts, USA,
on Wednesday, July 22, 2026.
    I?m speaking at Cognitive Security Conference in Las Vegas, Nevada, USA.
The conference runs August 6-7, 2026; my speaking time is TBD.
    I?m speaking at DEF CON 34 in Las Vegas, Nevada, USA. The conventions runs
August 6-9, 2026; my speaking time is TBD.
    I?m speaking at LAcon V in Anaheim, California, USA. The convention runs
August 27-31, 2026, and my speaking time is TBD.
    I?m speaking at CanSecWest 2026 in Vancouver, Canada. The conference runs
September 30-October 1, 2026; the time of my talk is TBD.

The list is maintained on this page.

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Since 1998, CRYPTO-GRAM has been a free monthly newsletter providing summaries,
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Bruce Schneier is an internationally renowned security technologist, called a
security guru by the Economist. He is the author of over one dozen books --
including his latest, Rewiring Democracy -- as well as hundreds of articles,
essays, and academic papers. His newsletter and blog are read by over 250,000
people. Schneier is a fellow at the Berkman Klein Center for Internet & Society
at Harvard University; a Lecturer in Public Policy at the Harvard Kennedy
School; a board member of the Electronic Frontier Foundation, AccessNow, and the
Tor Project; and an Advisory Board Member of the Electronic Privacy Information
Center and VerifiedVoting.org. He is the Chief of Security Architecture at
Inrupt, Inc.

Copyright ? 2026 by Bruce Schneier.

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