History of Technology

ColdFusion opens with Henry Ford's warning that if people understood the banking system 'there would be a revolution before tomorrow morning' and then delivers a tightly edited history that connects directly to the course's recurring theme: technology is never neutral, and the systems we build encode the interests of their builders. The video traces how a secret 1910 meeting at Jekyll Island led to the creation of the Federal Reserve, how the six men in attendance represented a quarter of the world's wealth, and how they used disinformation in newspapers to trick both Congress and the public into supporting a system designed to benefit its architects. While this is ostensibly about banking, it is really about the politics of infrastructure -- the same question Unit 7 asks about electrification and Unit 13 asks about the internet. Who designs the system? Who benefits? Who is excluded? ColdFusion's visual storytelling makes these questions accessible in 21 minutes, and Alan Greenspan's on-camera admission that 'there is no other agency of government which can overrule actions that we take' is the kind of primary-source moment that sticks with students.

This is the centerpiece documentary for this course. FRONTLINE traces the global AI revolution across two hours, moving from China's mass deployment of facial recognition and social credit scoring to Silicon Valley's automation of white-collar work to the Uighur surveillance apparatus in Xinjiang. The documentary interviews Kai-Fu Lee, who describes the moment he realized that AI would displace 40 percent of the world's jobs within fifteen years, and visits a factory in Guangdong where robots have replaced 90 percent of the workforce. It profiles Shoshana Zuboff explaining surveillance capitalism, follows truck drivers confronting autonomous vehicle technology, and examines how algorithmic hiring systems reproduce racial bias at industrial scale. For a course that asks 'who decides what technology gets built and for whom,' this documentary provides two hours of case studies spanning Units 8 through 18 -- from assembly line automation to AI governance. When your student reads about existential risk in Unit 9 and surveillance capitalism in Unit 15 and the attention economy in Unit 17, they will already have FRONTLINE's reporting in their heads: real people, real consequences, real choices still being made.

This VPRO documentary follows Shoshana Zuboff as she explains surveillance capitalism with the precision of a scholar and the urgency of a whistleblower. She opens by insisting that the term 'surveillance capitalism' is not arbitrary -- the surveillance must be 'engineered as undetectable, indecipherable, cloaked in rhetoric that aims to misdirect.' The documentary then traces how Google discovered that the 'behavioral surplus' -- data beyond what was needed to improve search -- could predict human behavior with extraordinary accuracy, and how that discovery created a new economic logic. Zuboff explains how a supermarket's algorithm detected a teenager's pregnancy before her father knew, simply by tracking her switch from fragrant to neutral shampoos. She describes how facial recognition software trained on family photos uploaded to Facebook is deployed for purposes users never consented to. This is the definitive companion for Unit 15 because Zuboff's framework -- that surveillance capitalism 'unilaterally claims human experience as free raw material' -- is the unit's central concept, and hearing her explain it with specific examples gives students a visceral understanding that reading alone cannot provide.

This Intelligence Squared debate at Union Chapel pits a former Greek finance minister against the Financial Times' chair in a structured argument about whether capitalism is reformable or already dying -- and the answer hinges on technology. Varoufakis opens with a genuinely original thesis: we are living through a moment analogous to the 1790s, when feudalism was still dominant but pockets of capitalism were emerging beneath it. He argues that capitalism is 'overthrowing itself' as profit ceases to be the primary engine of accumulation, replaced by what he calls 'technofeudalism' -- a system where platform owners extract rent from everyone who must use their infrastructure, much as feudal lords extracted rent from everyone who worked their land. Gillian Tett counters with a pragmatic defense of market reform. For a course that traces technology from the printing press through platform capitalism, Varoufakis provides the most provocative end-state argument: that the platforms examined in Units 14 and 15 have created not merely a new form of capitalism but a new mode of production entirely. The debate format, with audience votes before and after, models the kind of structured argumentation the course demands.

FRONTLINE's investigation of Elon Musk's Twitter acquisition is a real-time case study in everything this course teaches about the politics of technology. The documentary traces how one man's purchase of a global communications platform -- justified by free speech rhetoric -- produced measurable increases in harassment, foreign disinformation, and the erosion of content moderation infrastructure that took years to build. It interviews former Twitter employees who describe being fired by email at midnight, researchers who document the platform's shift toward amplifying outrage, and First Amendment scholars who distinguish between free speech as a constitutional protection and free speech as a billionaire's personal brand. For Units 14 and 18, this documentary is essential because it shows enshittification happening in real time: a platform that once functioned as a 'global town square' being reshaped to serve the interests of a single owner. Langdon Winner's question from Unit 18 -- 'do artifacts have politics?' -- is answered here with devastating specificity: when one person controls the architecture of public discourse, that architecture reflects his politics.

Grant Sanderson's visualization of transformer architecture is the single best explanation of the technology behind ChatGPT, Claude, and every other large language model reshaping the world this course examines. He traces how transformers differ from earlier approaches: instead of processing text one word at a time, they 'soak it all in at once in parallel,' which is why they can be trained on the enormous datasets that made modern AI possible. His animation of the attention mechanism -- showing how the numbers encoding the word 'bank' are refined based on surrounding context to encode 'river bank' rather than 'financial bank' -- makes visible the process that Unit 16 describes abstractly when it says AI 'pattern-matches on data that humans collected, labeled, and curated.' Sanderson's observation that 'researchers design the framework for how each of these steps work' but 'the specific behavior is an emergent phenomenon based on how hundreds of billions of parameters are tuned during training' captures the central epistemic problem of AI governance: we built these systems, but we do not fully understand why they work. For a course that asks 'who teaches the machines,' this video provides the honest answer: we designed the architecture, but what emerged from training surprises even us.

Kurzgesagt traces intelligence from flatworm brains 500 million years ago through hominins, the agricultural revolution, and the information age to arrive at the question Unit 16 poses: what happens when we build machines better at the thing that gave us dominion over the planet? The video's evolutionary framing is essential because it places AI in the deepest possible historical context -- not as a product of Silicon Valley but as the latest chapter in a story that began when neural structures first proved worth their metabolic cost. The animation showing how chess AI progressed from narrow specialized systems to self-learning models that mastered the game in four hours by playing against themselves visualizes the leap from narrow to general intelligence that the unit describes. Kurzgesagt does not shy from the existential dimension: the video's final section asks what happens when AI systems become 'better than humans at the very thing that gave us power over the planet,' directly connecting to Unit 9's treatment of existential technological risk. At 16 minutes and with Kurzgesagt's signature animation quality, this is the ideal low-commitment entry point for students encountering AI for the first time.

Hank Green sits down and works through his entire catalogue of AI concerns in real time, and the result is the most honest, least performative assessment of artificial intelligence available on YouTube. He opens by acknowledging the epistemic problem that haunts this course: every potential AI impact has both a severity and a likelihood, and reasonable people disagree about both dimensions. He then catalogues specific harms already happening -- algorithmic cruelty in sentencing and credit decisions, the 'creative vampirism' of training models on unconsented intellectual property, AI-induced psychosis from chatbot relationships, deepfake pornography, the energy costs of data centers, and the concentration of power in a handful of companies. What makes this essential for Unit 16 is Green's refusal to rank these concerns into a neat hierarchy. He models exactly the kind of thinking the course demands: holding multiple concerns simultaneously, resisting the urge to collapse complexity into a single narrative, and being honest about what you do not know. His disclosure that he is receiving settlement money from Anthropic for training on his books while knowing YouTube creators will never see equivalent compensation is the kind of specific, personal detail that makes abstract policy debates real.