A humanities course that hands students the analytical tools to read the technological and economic landscape they live in — and to make disciplined predictions about where it goes next. This kit gives you everything you need to build your own version at your school.
As technology and ideas progress, society evolves to take advantage of new media, economic, and technological landscapes. In a single human lifetime we went from a world where creating and distributing media was an expensive, tightly controlled endeavor to one where anyone can publish a blog, video, or podcast for almost nothing.
The central pursuit of this course is an investigation of the economies of scale and advances in technology that now make it good business to give away services for free — and an attempt, by students, to envision and create the direction (or possible directions) society will evolve next.
Using the lens of Big History, students chart how the universe — and then human society — crossed thresholds of rising complexity, from the Big Bang to collective learning to the internet.
Students learn core microeconomics — markets, supply and demand, marginal cost — then study how "free" was transformed inside a digital "bits" economy and how the big tech ecosystems exploit it.
Each student picks a domain they care about, builds a punctuated-equilibrium model of its past and present, and writes an evidence-based argument for its future.
The course's recurring analytical move is a diagram with time on the x-axis and complexity on the y-axis. Complexity doesn't rise smoothly — it sits on long plateaus broken by sudden jumps, each triggered by a new technology, a falling cost, or a new exchange network. Students use the curve to analyze the past and to structure their predictions of the future.
Whose idea this is. The punctuated-equilibrium model of technological change — and this diagram — is the course's own framework, developed by Jonathan Briggs and Matt Delaney. It shares some underlying vocabulary with the Big History Project (Goldilocks conditions, thresholds of complexity, collective learning), but Big History stops short of this synthesis. Turning those ideas into a single predictive tool for reading and forecasting technology is original to this course.
Complexity (vertical) rises over time (horizontal) not smoothly but in steps — long plateaus broken by sudden jumps. Tap any numbered point on the curve, or a button above, to read what drives each phase.
Students grow up inside technological change, but rarely get tools to think about it structurally. This course treats that as a teachable skill. It is deliberately interdisciplinary — part history, part economics, part technology, part media studies — because the forces it studies don't respect subject boundaries.
The method is consistent across every unit: study how change has happened, name the mechanisms that drove it, then use those mechanisms to reason about what happens next. Problem-solving and flexible thinking are valued over memorization. The goal is not for students to be right about the future — it's for them to build arguments about the future that are honest, evidence-based, and falsifiable.
How does the existence of almost-free digital memory in a "bits" economy change economic interaction and the spread of technological tools?
If history helps us avoid past mistakes, what happens when the landscape of the future ceases to match that of the past?
When all facts and figures are instantly retrievable, is there still value in knowing anything — and what will define a "knowledgeable" person in the future?
Would a massive increase in human longevity be sustainable under our current economic system? If not, what would have to change?
Three modules move students from the deep history of complexity, through the economics of the digital present, to a structured forecast of the future. Each carries equal weight in the gradebook.
An overview of history from the start of the universe to our modern, technological society, and an exploration of what the internet actually is — its architecture and how it works.
An introduction to core microeconomics — perfect markets, supply, demand, marginal cost — and how those concepts behave in technological development, followed by an analysis of how "free" has been transformed inside the digital "bits" economy.
A discussion of how technological innovation and the societal trends it produces are reshaping daily life — and where their long-term path leads. This module turns the analytical tools loose on the future.
A representative pacing for a ~10-week trimester. Treat it as a skeleton — the modules are modular by design, and the adaptation guide shows how to stretch or compress this.
Big History readings and the "mini-thresholds of life." Students post reflections and build their first punctuated-equilibrium diagrams.
Exchange networks, rapid acceleration, and how the internet works. Open source as a case study.
Groups produce the punctuated-equilibrium synthesis presentation — the Module 1 capstone.
Markets, marginal cost, and Anderson's Free. Students post on demonetization and "too cheap to matter."
Groups each take one tech giant, research its ecosystem, and present. Paired with the "I cut X out of my life" readings.
Articles and videos on AI, AR/VR, automation, and longevity. Students choose their prediction domain.
Domain & impact statements, outlines, peer editing, and production of the research paper and diagram.
Students present predictions, record peers' forecasts in the prediction table, and complete the final synthesis.
Long stable plateaus interrupted by rapid jumps. The course's master diagram: complexity (y) over time (x).
Humanity's unique ability to share and accumulate knowledge across generations — the driver of accelerating complexity.
The trade, communication, and information links that connect groups and speed up innovation.
The cost of producing one more unit. Near zero for digital goods — the economic root of "free."
Cross-subsidy, third-party (advertising), freemium, and non-monetary — how giving things away can be good business.
A new entrant that reshapes a market by changing its economics, not just improving the product.
You don't need a whole trimester to use the central idea. The punctuated-equilibrium concept works as a single, self-contained lesson — a way to give students a durable model of how complex systems change in one sitting. Below is the exact shape of a mock class period built around it.
With a partner, identify a time when something — in your life or that you observed — evolved or changed rapidly, becoming more complex. Students share their "paradigm shift" as they introduce themselves.
The teacher frames the day: we're going to build one model — punctuated equilibrium — for how complex systems evolve, and then test it on a real story.
The class reads a short common text (here, the rapid shift to remote learning during the 2020–21 pandemic) that everyone will analyze through the model.
Students receive definition cards for the core terms — Goldilocks conditions, threshold moments, acceleration, old & new paradigms / plateaus, feedback loops.
In groups of ~4, each group makes sure everyone understands their assigned definition, then hunts for places in the shared text where that concept appears.
Each group teaches the rest of the class where they found their concept at work — building the full diagram collectively.
The class connects the pieces into one punctuated-equilibrium curve and debates where the next threshold might be.
Students make a prediction about what comes next — and note what evidence would tell them whether they were right.
The lesson uses one accessible story to make the abstract model concrete. Remote learning didn't appear overnight in 2020 — it crossed a series of thresholds, each enabled by a new technology, with long plateaus in between.
The expanding postal service made "learning at a distance" possible — assignments mailed to professors, feedback mailed back. By the late 1800s many universities had correspondence departments.
Broadcast brought lectures to scale; coursework was still mailed in. (In many ways, the TED talk is a short-form descendant of this format.)
Virtual colleges, then learning-management systems, then online video converge: massively open online courses can enroll thousands at once.
Video-conferencing adoption skyrockets in weeks. The share of people comfortable in an online meeting jumps from very few to most of the connected world — a textbook punctuated jump after a century of plateaus.
Each module carries the same weight, with a small final synthesis at the end. This keeps students engaged across the whole term rather than betting everything on a final.
| Component | Weight | What it captures |
|---|---|---|
| Module 1 — Big Bang to the Internet | 30% | Diagrams, posts, and the synthesis presentation |
| Module 2 — The Economy of Free | 30% | Economics work, the Big 5 research & presentation |
| Module 3 — The Tech Landscape | 30% | The "Future of…" paper, diagram, and prediction |
| Final Synthesis | 10% | Final exchange and reflection across the term |
Module 1 capstone. In groups, students build a punctuated-equilibrium diagram with at least three steps — time on the x-axis, complexity on the y — that models either an analogy or a real progression toward complexity. Each member contributes one step, all key terms are labeled and connected to the scenario, and a final slide combines the three steps into one global diagram.
The intellectual heart of Module 3. A short single-spaced paper in which students select 3–4 articles as foundation, analyze each with quotations, in-text citations, and commentary, and make a clear argument for a specific future trend in a domain of their choosing — accompanied by a labeled punctuated-equilibrium diagram capturing the past, present, and predicted future.
Module 2's culminating group work. Each group takes one of Amazon, Apple, Facebook/Meta, Google/Alphabet, or Microsoft, researches its ecosystem and business model, and presents how it captures value — often in the digital economy through "free." Paired with the firsthand "I cut X out of my life" readings.
The course's closing ritual. Students present their forecasts and record every classmate's topic and prediction in a shared prediction table — turning individual research into a collective map of where the class thinks the world is headed.
A real inventory of recurring assignments behind the major assessments. Use it as a menu — adopt what fits, retitle the rest.
Publicly available resources that anchor the course, each with a short note on what it is and how it earns its place. Swap in fresher examples as the landscape moves — the frameworks are what's durable.
What it is: the book that gives the course its spine — the four models of "free," "too cheap to matter," and the economics of abundance in a digital world. How it's useful: read in sections across Module 2, it gives students a shared vocabulary for why so much of the internet is given away, and a framework they then apply to real companies. Anderson released it for free, which makes the book its own case study.
Full text on the Internet Archive →What it is: a firsthand journalism series in which a reporter tries to cut each of the big five tech companies — and then all of them — out of daily life. How it's useful: it turns abstract talk about "ecosystems" into something visceral, exposing how deeply the giants are woven into infrastructure (payments, hosting, logins). Pairs directly with the Big 5 group presentations.
Amazon · Facebook · Google · Microsoft · All FiveWhat it is: a talk on exponential technological change — paradigm shifts, Moore's law, and the acceleration of acceleration. How it's useful: students harvest Kurzweil's vocabulary and map it directly onto the course's own threshold-and-complexity model, then critique which of his predictions have held up. A bridge from the historical lens of Module 1 to the forward-looking work of Module 3.
Watch on YouTube →What it is: reporting on how AI can generate photorealistic faces and media of people and events that never existed (e.g., GAN-generated faces). How it's useful: it grounds one of the course's sharpest essential questions — what happens to "the truth" and collective narratives when anyone can manufacture convincing reality? A frequent springboard for student prediction papers.
The Verge: AI-generated faces →What it is: a primer on the "uncanny valley," the unease we feel as synthetic humans get almost-but-not-quite real. How it's useful: it gives students a concept and concrete examples for discussing AR/VR, avatars, and synthetic media — why believability matters, and where it breaks down.
10 examples of the uncanny valley →What it is: the interdisciplinary "Big History" framing — the universe and humanity crossing successive thresholds of increasing complexity, with collective learning as humanity's accelerant. How it's useful: it supplies vocabulary and conceptual scaffolding for Module 1 and the one-period mini-lesson. Acknowledgment: the Big History Project's free curriculum shaped this course's vocabulary and is gratefully credited — though the punctuated-equilibrium model applied to technology is the course's own synthesis. Adopters should carry both credits.
Big History Project →Anonymized, lightly trimmed excerpts from student discussion posts and prediction statements across past offerings. Names, sections, and other identifying details have been removed. They're here to show the texture of the thinking — disciplined speculation, concept transfer, and economic reasoning — that the course is designed to surface.
“Advertisers will know more about you in a few decades than you know yourself — and will use that knowledge to acquire vast sums of money.”
— Prediction · the future of online advertising“He predicted solar panels will become the sole provider of energy — lighter and more efficient. I think something of that sort comes to fruition; I just don't know when.”
— Reflection · holding a prediction and its uncertainty together“I'm looking at the demand for corporate digital security, and how it will have to change and adapt as the future unfolds.”
— Domain & impact statement“People trust other people far more than brands now; advertising goes wherever the attention goes.”
— Synthesis · shifting media economics“Non-petrol commuter vehicles will hold the majority of the commuter-car market within a few decades — the cost curves are already bending.”
— Prediction · transportation“I want to trace experiential technology in education — and its impact on hands-on learning in the classroom.”
— Domain & impact statement“His terms map onto ours: exponential growth, paradigm shifts, acceleration. It's the same threshold idea, just pointed at the future instead of the past.”
— Reflection · transferring a concept across units“Smart farming, automated mining, investing apps that put the stock market in everyone's pocket — different domains, same pattern of a sudden jump in what's possible.”
— Final exchange · spotting the shared shape across forecastsWhatever you change, preserve the three-part arc — deep history of complexity, the economics of the present, a forecast of the future — and the punctuated-equilibrium diagram as the connective tool. That structure is what makes the course coherent.
Module 1 → complexity, ending in the synthesis diagram. Module 2 → the economics of free, ending in the Big 5 study. Module 3 → the landscape, ending in the "Future of…" paper. Pick the single deliverable that proves the module, then build backward to it.
Swap dated readings and companies for current ones. The framework is durable; the examples are disposable. Updating them is a yearly ritual, not a one-time fix.
The original pairs a short read-and-post for homework with a hands-on activity in class. Scale the volume up or down, and lean on videos and annotated excerpts where a full text is too heavy.
Create a class notebook or shared drive for readings, partnered notes, and final papers. Adopt the CW / HW / MA + bracketed-action naming so students always know the mode and the task at a glance.
Close on the Final Exchange: students present forecasts and record each other's predictions in a shared table. It converts individual work into a collective artifact and gives the term a memorable ending.
| Original element | Why refresh | Swap-in direction |
|---|---|---|
| The "big five" tech companies | Rankings, names, and business models shift | Re-pick the dominant platforms for your year; consider adding a chip-maker, an AI lab, or a non-US giant |
| State of AI / "future of work" readings | Predate the generative-AI wave | Add current pieces on LLMs, agents, and labor-market effects; revisit the longevity question with new data |
| AR/VR video set | The hardware and hype cycle moved | Update with current mixed-reality, wearables, or ambient-computing demos |
| Free examples | Some "free" services added paywalls / subscriptions | Keep the four models; refresh with current freemium, ad-funded, and subscription cases |
| "I cut X out of my life" series | Specific articles age | Use the latest digital-dependence reporting, or have students attempt their own week-long experiment |
~10 weeks, three modules of equal weight, one major deliverable each, closing in the Final Exchange.
Add depth: a second economics unit, a primary-source history strand, or individual research checkpoints across Module 3. Add a midterm synthesis.
Run Module 2 alone as an "Economics of Free" unit, or Module 3 as a "Forecasting the Future" capstone in an existing course.
Emphasize the Big History framing, media studies, and the argumentative paper. Lighten the microeconomics.
Deepen markets, marginal cost, and platform economics; use the tech landscape as applied case studies.
Expand "how the internet works" and open source; pair the forecasting paper with a build or prototype.
Evolution of Society: Economics & Technology was co-developed and co-taught at Eastside Preparatory School (Kirkland, WA), where it ran for many years and evolved each time it was offered. This kit distills that accumulated practice into something other educators can adopt.