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.