There's a lot of good info in this essay:
AI WEAPONS <https://youtu.be/A0X4O49cY4o?si=sZebG1guOT0bcqIg>
Because it's so long and most of us prefer reading to watching, I asked Claude
to summarize the transcript Whisper gave me. I don't use HTML format very
often. So hopefully this works.
Notes on “AI WEAPONS” Video Essay
*Historical Foundations of Computing & Military Connection*
* Computing origins tied to military applications from the beginning
* Lewis Fry Richardson (1881) - Quaker pacifist who developed mathematical
weather prediction during WWI
* Vannevar Bush built first analog computer at MIT (1931), later oversaw
Manhattan Project
* ENIAC (1945) - first general purpose digital computer, used exclusively for
developing thermonuclear bombs
* John von Neumann’s vision: “All processes that are stable we shall predict.
All processes that are unstable we shall control”
*Cold War Era Development*
* William Goodell and ARPA’s Project Agile in Vietnam - combined surveillance
with social science research
* Project Camelot (1964) - “methods for predicting and influencing social
change and internal war potential”
* Early neural networks: Mark One Perceptron (1958) for US Navy
* SAGE system - Semi-Automatic Ground Environment for NORAD, had serious bugs
but became foundation for commercial air travel (SABRE)
*AI Winter and Economic Philosophy*
* First AI winter (1974-1980) due to lack of advancement
* Friedrich Hayek’s influence on connectionism and free market ideology
* Hayek’s theory: mind emerges from neural connections, similar to market
“spontaneous order”
* Connection between AI black boxes and market logic - both operate beyond
human comprehension
*Modern AI Weapons Era*
* Three catalysts for 2010s acceleration:
1. 9/11 and Authorization of Use of Military Force (AUMF) enabling
preemptive strikes
2. 2008 financial crisis leading to zero interest rates and venture capital
influx
3. AlexNet paper (2011) proving neural networks were viable with massive
data
*“Startup War” Phenomenon*
* Military shifted from R&D to venture capital investor role
* CIA’s In-Q-Tel (1999) - first military VC firm
* Tech platforms and military collaboration for mass surveillance
* Signature strikes vs personality strikes - algorithmic target selection
based on metadata
*Palantir Technologies*
* Founded by Peter Thiel and Alex Karp (2002), CIA-backed from start
* Specializes in data analytics infrastructure and visualization for
government/military
* Products: Gotham (police/military), Foundry (business), Apollo (backend)
* Contracts with ICE for immigrant deportations, police departments for
“predictive policing”
* Free trials to collect data and train AI systems
*Israel as AI Weapons Laboratory*
* Weapons industry central to Israeli economy since 1950s
* “Battle-tested” as key selling point for Israeli military technology
* West Bank as surveillance testing ground:
o Wolfpack database profiling Palestinians
o Blue Wolf app for real-time identification
o Red Wolf autonomous facial recognition cameras
*Gaza AI Systems*
* Operation Guardian of the Walls (2021) - “first AI war”
* Lavender: Algorithm ranking Palestinians as potential targets
* Gospel (Habsora): Algorithm selecting buildings to destroy
* “Where’s Daddy”: Algorithm timing strikes when targets are home with families
* Fire Factory: Logistics and ammunition allocation
* 100 targets per day vs previous 50 per year
*Surveillance Infrastructure*
* Hebron H2: 2 cameras per 5 meters, some inside homes
* Israeli startups: Anyvision, Coresight AI, Smart Shooter
* Unit 8200 - Israel’s cyber warfare division, source of many startup founders
* NSO Group’s Pegasus spyware as example of Unit 8200 alumni work
*Technology Failures and Biases*
* Garbage in, garbage out principle
* Racial bias in facial recognition (HP webcams, Google Vision, etc.)
* October 7th intelligence failure - AI systems ignored human intelligence
warnings
* High civilian casualty rates despite claims of precision
*Broader Implications*
* AI requires constant data collection, turning everything into training data
* Platforms hitting data bottlenecks, moving from content to behavioral data
* “Code spaces” - physical spaces dependent on technology
* Technology glitches reveal underlying logic and biases
* Question: Is the technology failing or working as designed to perpetuate
conflict?
*Economic Drivers*
* Big Tech’s need to monetize massive data collections
* Venture capital seeking monopolistic “unicorn” investments
* Military-industrial complex adopting startup methodologies
* Israel’s arms export economy dependent on continuous testing opportunities
--
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