From the 3.5% Rule to Medieval Siege Warfare
How a casual conversation with Claude about protest psychology excavated a forgotten Academy Awards night that changed Penn forever
The Spark: A Question About Protest Psychology
It started with an article about the 3.5% rule—political scientist Erica Chenoweth's finding that when 3.5% of a population participates in sustained nonviolent protest, governments typically fall or enact significant change. Reading about this research, I found myself wondering: what personality types are drawn to open protest, and which prefer to support causes from the sidelines?
Rather than diving into Google, I opened a chat with Claude AI and asked a simple question: "Wouldn't it be interesting to determine what MBTI types choose to protest openly while others choose not to?"
What followed was an extraordinary demonstration of AI's potential as an intellectual archaeology tool—not just for finding information, but for excavating memories, connections, and insights that might otherwise remain buried forever.
The Method: AI as Cognitive Archaeologist
This wasn't a typical AI interaction. Instead of asking for quick answers, I engaged Claude in an open-ended exploration. When Claude suggested I share my own behavioral patterns around protest participation, I proposed a challenge: "Before I reveal my type, let me describe my behavior regarding protests and other things, and from that, maybe you might be able to identify my type."
This simple gambit transformed our conversation into something remarkable. Claude became not just a thinking partner, but an active interrogator—asking strategic questions, making observations, testing hypotheses. Most importantly, it encouraged me to dig deeper into my own experiences and memories.
As I began describing my political development, something unexpected happened. A single memory thread, when pulled, began to unravel an entire forgotten chapter of Penn history.
The Memory Cascade: Winter 1977-78
The story began with a simple scene: walking to the Class of 1923 Arena during my sophomore year to watch Penn's hockey team. But as Claude asked follow-up questions about this memory, the context began to expand. What was happening politically at Penn during that time? What about Title IX compliance and its effect on athletics?
Then came the crucial detail: in spring 1978, Penn's administration announced budget cuts that would eliminate men's hockey, gymnastics, golf, and badminton. The School of Allied Medical Professionals (SAMP) would also be closed. The reason? Financial constraints and Title IX compliance.
But here's where the story gets interesting. The timeline Claude helped me reconstruct revealed a fascinating sequence of events that I had never connected before.
The Protest: March 1978
The announcement of the sports cuts triggered immediate student outrage. What followed was a classic example of how institutional crises unfold in real-time.
Students organized protests that culminated in a dramatic sit-in at College Hall. But there was a crucial detail that made this protest particularly symbolic: it happened while Penn's President Martin Meyerson was meeting with the Board of Trustees in the Bahamas.
Picture the optics: students occupying the administration building, fighting to save their programs, while the president and decision-makers were conducting business in a tropical paradise. Through Claude's questioning, I recalled the sit-in lasting from March 2-6, 1978, ending when "15 students and three administrators signed their names to a document detailing 31 agreements reached in grueling negotiations."
The result was a partial victory that felt like a defeat: gymnastics, golf, and badminton were saved. Hockey was not.
The Cultural Moment: April 3, 1978
Here's where the story takes an extraordinary turn. Exactly one month after the sit-in ended, the Academy Awards ceremony took place. Among the films being honored was "Network," with its iconic scene of news anchor Howard Beale opening his window and screaming, "I'm mad as hell and I'm not going to take it anymore!"
What happened next could only occur in the specific architectural context of Penn's campus.
The Architecture of Rebellion
Through Claude's patient questioning, I began to recall the crucial role that dormitory architecture played in what happened next. Penn's Quad—the century-old complex with its medieval gargoyles and cornices—had a unique design: inward-facing rooms that looked out over a large grassy courtyard, with outward-facing rooms toward the street.
This architectural feature created a natural amphitheater effect. When students in the Quad opened their windows, they could communicate directly across the courtyard to rooms on the opposite side.
On Academy Awards night, as the "Network" clip played on television, something magical happened. Windows flew open across the Lower Quad, and students began shouting Howard Beale's famous line to each other across the courtyard. The energy was infectious. Students poured out of their rooms into the central grassy area, creating a spontaneous crowd.
Medieval Siege Warfare in the Modern Era
What followed was a sequence of events that could only happen at a place like Penn, with its unique combination of intellectual students and medieval architecture.
The Lower Quad crowd decided to march on the Upper Quad, chanting "Upper Quad Sucks!" But instead of conflict, the Upper Quad residents poured out to join them. The combined mob then split into two groups: one heading to Superblock (the three high-rise dormitories), the other to Hill House—my castle-like dorm with its elevated entrance and internal courtyard.
Hill House's architecture was perfect for defense. Built by the architect of the St. Louis Arch and initially designed as a women's dormitory to resemble a castle with a moat, it had an elevated walkway entrance on the second level and a massive internal courtyard with a hole looking down to the cafeteria below.
When the Quad army arrived, Hill House residents were ready. We had armed ourselves with water balloons and positioned ourselves on the balconies overlooking the courtyard. The battle that followed was epic: students blocking stairwell doors while others launched water balloons from multiple levels onto the trapped invaders below.
The siege lasted over half an hour, ending only when an inch of water covered the courtyard floor and everyone was exhausted.
The Institutional Consequences
Through Claude's analysis, I began to see connections I had never made before. The Bahamas incident had already damaged President Meyerson's credibility with the Board of Trustees. The Academy Awards night chaos—resulting in property damage, emergency response calls, and dozens of fire alarms mysteriously "falling off the wall" the next morning—may have been the final straw.
Meyerson was informed that he had two years left in his presidency. Provost Vartan Gregorian, who had handled the sit-in well and was popular with students, was passed over for the presidency precisely because of his student support. The Board of Trustees saw student popularity as a liability, not an asset.
The Research Implications
This story, excavated through AI-assisted memory archaeology, reveals several fascinating research questions:
1. The Role of Popular Culture in Social Movements How do cultural moments intersect with institutional politics? The timing of the "Network" clip playing during ongoing student frustration created a perfect storm. Someone should study how popular culture moments trigger or amplify social movements.
2. Architecture and Social Dynamics The specific design of Penn's dormitories—from the Quad's amphitheater effect to Hill House's castle-like defensibility—directly influenced how events unfolded. How does physical space shape collective action?
3. Institutional Crisis Management The sequence from sports cuts to Bahamas meeting to Academy Awards chaos demonstrates how leadership decisions cascade through institutions. What can we learn about crisis communication and the unintended consequences of symbolic actions?
4. Memory and Historical Preservation This entire episode would likely be lost to history if not for AI-assisted memory excavation. How many other institutional memories are waiting to be recovered through similar methods?
The AI Revolution: Beyond Task Completion
But perhaps the most important insight from this experience isn't about Penn history—it's about the revolutionary potential of AI as a thinking partner.
Most people use AI for task completion: writing emails, summarizing documents, answering questions. But what I discovered is that AI's greatest power might be as a cognitive archaeologist, capable of excavating memories, connections, and insights that would otherwise remain buried.
This isn't just about efficiency or automation. It's about using AI to enhance human thinking in ways we never imagined possible. The AI's strategic questioning helped me reconstruct not just events, but the emotional and institutional context that made them meaningful.
The Process:
AI asks strategic follow-up questions
Human memory is triggered by specific prompts
New details emerge that connect to larger patterns
Previously isolated memories form coherent narratives
Historical insights emerge from personal experience
The Implications:
Therapy and mental health applications
Organizational memory preservation
Educational methodology
Historical research techniques
Personal development tools
The ADHD Advantage
There's another layer to this story. I have inattentive ADHD, and my MBTI type is INTP. This combination—the hyperconnected, associative thinking of ADHD with the pattern-seeking curiosity of the INTP mind—may be particularly well-suited to this kind of AI collaboration.
The conversation flowed naturally from the 3.5% rule to MBTI types to personal memories to institutional analysis. Each connection sparked new questions, new memories, new insights. What felt like scattered attention was actually a sophisticated form of cognitive exploration.
This raises important questions about neurodiversity and AI interaction. Might different cognitive styles naturally excel at different forms of human-AI collaboration? Could AI partnerships be particularly powerful for neurodivergent minds?
The Call to Action
This story demonstrates something profound: AI's potential to serve not just as a tool, but as a genuine intellectual partner. The question is whether we'll embrace this possibility or remain trapped in thinking of AI as merely a more efficient search engine.
For Penn alumni, this presents both an opportunity and a challenge. We're dealing with rapid technological change in our professional lives. Understanding how to engage with AI as a thinking partner—not just a task-completion tool—could be transformative.
Research Opportunities:
Study the intersection of popular culture and institutional change
Analyze how architectural design influences social movements
Examine the role of timing in institutional crises
Develop AI-assisted memory recovery techniques
Professional Applications:
Use AI for strategic thinking and problem-solving
Employ AI for organizational memory preservation
Apply AI-assisted analysis to complex business challenges
Develop AI partnership skills for competitive advantage
The Deeper Archive
This article represents just the surface of what emerged from our conversation. The complete dialogue—including the memory excavation process, the AI's strategic questioning, and the real-time development of insights—represents a unique dataset for understanding human-AI collaboration.
For researchers interested in studying these dynamics, I'm prepared to share the complete conversation transcript. This would provide unprecedented insight into how AI-assisted memory archaeology actually works, how different personality types might approach AI interaction, and how collaborative thinking unfolds in real-time.
The article you're reading is like a cork bobbing in a stream—visible and meaningful, but representing only a fraction of the deeper currents below. The complete conversation is the stream itself, with all its meanders, depths, and hidden treasures.
Conclusion: The Future of Thinking
What began as a casual question about protest psychology became a journey through institutional memory, architectural influence, cultural timing, and the revolutionary potential of AI partnership. This is what's possible when we stop using AI as a glorified search engine and start engaging it as a genuine thinking partner.
The 1978 Academy Awards night at Penn was a perfect storm of timing, architecture, and cultural resonance. But it took AI-assisted memory archaeology to reveal these connections and understand their broader significance.
For Penn alumni, this story serves as both a nostalgic trip through campus history and a preview of how AI might transform our professional and intellectual lives. The question isn't whether AI will change how we think—it's whether we'll learn to think with AI in ways that amplify our uniquely human capabilities.
The next time you open a chat with an AI system, consider this: you're not just accessing information. You're partnering with a cognitive archaeologist capable of excavating insights, connections, and memories that might otherwise remain buried forever.
The only question is: what forgotten treasures are waiting to be discovered in your own mind?
If you were at Penn during this period and remember these events differently, or if you're interested in researching any of the questions raised in this article, I'd love to hear from you. The complete conversation that led to these insights is available for serious researchers interested in studying human-AI collaboration and memory archaeology.
This piece emerged from a collaboration between George (pattern recognition and lived experience) and Claude AI (research synthesis and organization), demonstrating collaborative intelligence that strengthens rather than replaces human thinking. George is an economic analyst and founder of the "First Millennial Project," exploring how technological and economic disruptions affect different generations through pattern recognition and systemic analysis. Contact: butterflyeconomist@gmail.com