Maury Nichols found this one.
Maybe I can buy one used?
https://www.thedrive.com/news/how-texas-police-spent-4-5-million-on-four-chevy-tahoes
How
Texas Police Spent $4.5 Million on Four Chevy Tahoes
Ominous Israeli
surveillance tech is now being deployed on American roads.
FalcoNet,
brought to you by a company called Cognyte (Israel’s Palantir
rival), secretly tracks people by intercepting the connection between
your phone and the nearest cell tower. The idea is that you can
strap this bad boy to a helicopter, backpack, or Chevy Tahoe and
gobble up everybody’s data as you cruise around. It’s already in
use in Florida. This year, Texas State Police bought a little fleet
of FalcoNet-equipped SUVs for just under $4.5 million. I found the
purchase receipt and FalcoNet user guide to learn a little more about
it.
In March of
2026, the Texas Department of Public Safety (DPS) Criminal
Investigations Division asked for approval to spend $4,487,500 on a
Cognyte surveillance setup. Actually, what they requested was
“approval for emergency purchase necessary to protect the safety
and welfare of state personnel and property. Delaying the
procurement process could result in unacceptable safety risks to
personnel and compromise operational readiness.”
The
request memo is chock-full of urgency and dramatic
language—peppered with terms like “emergency” and “immediate.”
But no specifics are mentioned. “Any delay in procuring would
compromise employee safety, public safety, operational readiness, and
overall mission success,” the memo states, without saying how or
why this brand-new, very expensive technology is suddenly essential
to operations.
“Forgetting”
might be a mistake. Perhaps we should keep all data but flag that
which is in dispute or clearly erroneous. How can we identify “new”
copies of forgotten data?
https://journals.sagepub.com/doi/full/10.1177/18479790261468434
Can
artificial intelligence forget? Reflections on the right to disappear
in a world where algorithms remember everything
The
development of artificial intelligence has profoundly reshaped the
ways in which personal data are generated, processed, and retained,
placing intelligent systems at the heart of debates on privacy and
fundamental rights. This article examines, from a European Union
legal perspective, the application of the General Data Protection
Regulation (GDPR) to AI and assesses whether the principles and
rights enshrined in European law—particularly the rights to
erasure, to be forgotten, and to rectification—can be effectively
exercised once information has been absorbed by machine learning
models. The study examines the main legal and technical challenges
arising from the nature of AI, which does not store data in a static
form but transforms it into knowledge, thereby complicating its
localisation, alteration, or deletion. It also analyses the
relationship between the GDPR and the Artificial Intelligence Act
(AIA), emphasising their complementary roles and the need to ensure
coherence between the two regulatory frameworks. From a legal and
ethical standpoint, the paper considers phenomena inherent to AI
systems—such as hallucinations, algorithmic bias, and neurodata—to
illustrate how they challenge essential principles such as accuracy,
minimisation, and purpose limitation, and how they test the rights of
individuals in contexts where information cannot truly be
“forgotten”. Finally, it proposes alternative mechanisms,
mitigation strategies, and emerging solutions aimed at preserving
individuals’ effective control over their data in the algorithmic
age, thereby reinforcing privacy protection and public trust in the
responsible use of new technologies.