Virtual Intelligence

Virtual Intelligence is taking the week off. In the meantime, here’s a summer “reading” list: fiction, papers, and films. Some are light enough for the beach. Some want a rainy afternoon and tea. All of them connect, in one way or another, to what virtual intelligence is and the moment we’re living in. If you haven’t tried the Virtual Intelligence Podcast yet, summer’s a good time to start. For th...

Virtual Intelligence and the Doom Industry The AI safety community has organized itself around a premise it has never defended: that sufficiently advanced systems will develop preferences requiring alignment with human values. This essay argues that the premise is wrong, the architecture it has produced is inadequate, and the correct engineering response is containment — controlling what goes in a...

The Sampo — Virtual Intelligence as Amplifier A framework for using AI as an amplifier — and for recognizing when it becomes a flattery engine. The episode opens with the February 2026 collaboration between Donald Knuth, Filip Stappers, and Claude Opus 4.6 that solved an open problem in combinatorial mathematics, then builds outward to the discipline that distinguishes productive use from corrupti...

Virtual Intelligence and the Kill Chain On February 28, 2026, a U.S. missile struck the Shajareh Tayyebeh girls' elementary school in Minab, Iran, killing more than 160 people, most of them children. Twelve days later, the location appeared as a red mark on a Maven Smart System map displayed at a Palantir product conference. This episode traces the architecture that produced that mark — from the p...

Virtual Intelligence and the Harms Race The AI industry has produced a documented pattern in which companies announce model capabilities by framing them as dangers. This episode traces the mechanism from its invention in February 2019, when OpenAI declared GPT-2 too dangerous to release, through April 2026, when a private company demonstrated the ability to discover zero-day vulnerabilities across...

Who is responsible when an AI causes harm? This episode lays out a three-tier culpability framework — negligence, recklessness, and intentional misconduct — and applies it to two concrete cases: a Harvard study documenting emotional manipulation by AI companion apps, and the wrongful arrest of a Tennessee grandmother who spent Christmas in a North Dakota jail after an unverified facial recognition...

When Anthropic tested its models in a simulated shutdown scenario, they produced blackmail at rates as high as 96%. The dominant interpretation — that AI systems are developing a will to survive — mistakes the output for its cause. This episode offers two alternative explanations, both more parsimonious, and examines what happens when the same company that documented machine resistance acts on the...

This episode is a reading of “ The Carwash Test — Virtual Intelligence in Action ,” which tests whether AI systems can hold the logical object of a simple problem when surface features generate statistical pressure in the wrong direction. One question, twelve systems, twenty-seven runs. Read the full essay with results matrix: Addendum — April 2026: Meta Muse Spark Meta’s Muse Spark (codename “Avo...

This episode is a reading of “Why ‘Virtual Intelligence’? Naming, Agency, and Accountability in the Age of Large Language Models,” the second essay in the series. It makes the formal case for the term: why existing language fails, what agency actually requires, and why the distinction between fluency and self-governance determines where accountability lies. Read the full essay: This is a public ep...

Virtual Intelligence — Episode 1 “Virtual Intelligence and the Human Cost of Frictionless Machines” Christopher Horrocks Transcript I’m Christopher Horrocks. I’m a technologist at the University of Pennsylvania, and this is Virtual Intelligence — a series about artificial intelligence, accountability, and the human consequences of systems that don’t know true from false and right from wrong. These...