Serendipity35

Fifty years ago, a pair of college dropouts named Steve Jobs and Steve Wozniak fundamentally shifted human history. The significance of 1976 to Apple Computers cannot be overstated: it was the literal ground zero of the personal computing revolution. On April 1, 1976, Apple Computer was formed, and by July, the duo unveiled the Apple I at the Homebrew Computer Club. Selling for a diabolical $666.66, the Apple I was just a bare motherboard. But it funded Wozniak’s next masterpiece: the 1977 Apple II, a fully realized, consumer-friendly machine featuring color graphics, expansion slots, and an integrated keyboard.

Fast forward to July 14–19, 2026. While modern Apple users await iterative upgrades to sleek aluminum slabs, retrocomputing diehards are descending upon the University of Illinois Springfield for KansasFest (KFest) 2026. Now in its 38th consecutive year, KFest remains the ultimate pilgrimage for hackers, programmers, and enthusiasts keeping the 8-bit dream alive.

This year’s convention is a historic milestone, marking the 40th anniversary of the Apple IIGS, the 16-bit pinnacle of the Apple II line released in 1986.The event features a packed schedule of legendary guests, collaborative hackathons, and hardware swap meets:In-Person Keynote: Apple Employee #12, Dan Kottke, is headlining the event live to share stories from the foundational garage days of Apple. Dan Hillman, the engineer who co-led the development of the Mega II chip (which squeezed an entire Apple IIe onto a single piece of silicon), is making a rare virtual appearance.

The Global Gathering: For those unable to travel to Illinois, KFest 2026 is also hosting an official virtual-only weekend event on July 31 – August 1, 2026.

A History Born of Crisis...

KFest wasn't always an independent nonprofit. It originally launched in 1989 as an official Apple II developers' conference organized by Resource Central, a publisher of Apple II magazines. When Apple decided to completely discontinue the Apple IIGS in late 1992 and the final Apple IIe in November 1993, corporate support evaporated. The market plummeted, and Resource Central faced a severe financial crisis by 1995. This (Low-Def) video was thought to be of the last ever KFest.

 

Recent college graduates face technology conscription: the expectation to feed, train, and validate the very AI models designed to automate their future career paths.

• The Flashpoint: Intellectual extraction and job devaluation. Graduates see AI corporations scraping human creativity, engineering, and writing without equitable compensation, creating an unstable economic future.
• The Tipping Point: Instead of burning draft cards, modern graduates are engaging in digital resistance—refusing to apply to major AI firms, deploying data-poisoning tools to protect their portfolios, and organizing labor walkouts over algorithmic ethics.
• The Split: A growing contingent of young professionals is choosing to boycott corporate AI completely. They are migrating to decentralized networks, open-source communities, and localized worker-owned tech collectives.

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Direct Comparison: Two Historical Divorces

The table below breaks down how these two systemic walkouts contrast in their execution, motives, and final resolutions:

Feature	The 1969 YAF Split	The Recent College Grad / AI Split
Primary Catalyst	State conscription to fight the Vietnam War.	Economic displacement and automated exploitation.
Opposing Authority	Traditionalist, Cold War conservative leaders.	Big Tech executives and corporate venture capitalists.
Act of Defiance	Physically burning a draft card on the convention floor.	Data-poisoning, model boycotts, and refusing corporate recruitment.
Immediate Result	A literal walkout from the convention hall.	A refusal to enter the mainstream tech workforce pipeline.
Long-term Alternative	Founding the U.S. Libertarian Party and independent caucuses.	Building decentralized tech, localized cooperatives, and open-source models.

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The Fundamental Contrast: Ideology vs. Survival

The core distinction between these two historic events lies in the nature of the stakes.

The 1969 split was primarily ideological and philosophical. The libertarians in YAF revolted because they refused to compromise their purist principles regarding individual liberty, free markets, and anti-interventionism. They were willing to forfeit their political capital within the broader conservative movement to maintain their philosophical purity.

Conversely, the current split between university graduates and AI firms is born out of material and economic survival. Graduates are not merely debating abstract theories of liberty in a convention hall; they are defending their literal livelihoods, the value of their degrees, and the ownership of their intellectual labor.

When the 1969 libertarians walked out under the St. Louis Gateway Arch, they did so to build a new political vehicle. When today's graduates walk away from AI tech corporations, they do so to build an alternative economy before the old one automates them out entirely.

Some months ago, when I was testing some LLMs in Amazon Bedrock in my own personal account console, I prompted Bedrock to produce a framework for collectively organizing Amazon Web Service employees.  Using a notoriously anti-union company's commercial resources to source a collective bargaining strategy for worker rights seemed like an interesting experiment.  Combining those results into learning objects and creating an interactive mini-course yielded the result below. Beware

40 years ago, when physically absent social interactions first began to invade our lives with unseen, unheard people sending us messages, services like CompuServe’s CB  supported the clamoring digital hoi polloi.  The fascination of exchanging unspoken ideas with strangers, imposters and (sometimes) fools was so compelling, participants would spend hours interacting, oblivious to the ever-running connect-time charges meter.

Groups of online users would form, chat rooms were created where these users could share their thoughts and ideas with users that wanted to contribute to, debunk or annihilate the discussions.  Flame-wars would break out over impossibly trivial matters ('Clara Peller was NOT Wendy’s mother in the “Where’s the Beef?” ad!’ What’s wrong with you??). I posted “Don’t drink and type!” to those belligerents which, of course, only enraged them further. By the time CompuServe CB died, these groups had all backed into their own corners and waited for the next-round conflict bell to ring. There was no external source, no online referee that defined the groups or their behaviors. Cooperation and opposition were organic functions.

I own up to my cyber-dyslexia. Every time I see or hear the phrase “social media,” my brain immediately translates it to “anti-social” media, but I’m not sure the “Anti-“ part is a result of the way the media is crafted or whether it is part of our individual identity.

Are social media algorithms truly to blame for online polarization, or do our own choices play a bigger role?

Social media algorithms collect and analyze vast amounts of user data, such as browsing history, interests, and interactions. This information is used to tailor content feeds to individual preferences, ensuring that users see posts most relevant to them. Algorithms heavily weigh engagement signals like likes, shares, comments, and watch time. Content that receives higher engagement is more likely to be promoted and shown to a wider audience. Once user data and engagement signals are collected, algorithms rank content based on predicted relevance and interest. Posts that score higher are surfaced at the top of users’ feeds, while less relevant content is shown less frequently or not at all. Ranking is continuous.  Updates happen as soon as new data arrives.

Like the Wendy’s commercial back in the mid-1980s, algorithms can amplify divisive content, but that isn’t their design.  They function by interaction.  They are more like the force that kept the connect-time clock running in the CompuServe CB.  They are engines of profit.  These back-end processes do not create the groups.  People follow the subjects and experiences that reinforce their own perspectives and join with the like-minded.

Understanding the human element in all of this cyber-selected content is key to understanding and abandoning algorithmic polarization. Not all engagement signals are beneficial; negative interactions, such as outrage or controversy, can also boost content visibility. Algorithms do not distinguish between positive and negative engagement, focusing instead on overall activity levels.  What starts as a personal action on social media can escalate into widespread influence, affecting conversations and shaping public opinion. Recognizing this path will highlight the importance of mindful engagement online.

We are all curious, it is part of who we are.  When we click around on the internet looking for some tidbit of information —“Was Clara Peller really a vegetarian?”  [No - Following her, popularity, she was presented with a 25-pound hamburger by the cattle industry and was gifted an apron that read "Beef Gives Strength”.]  And while a search like that may spawn hamburgers ads all over your chosen media, be aware that the engine that sends the content back to us is not trying to raise your cholesterol or shorten your lifespan or drive you to some nutrition-oriented political party.  It is only there to make money by offering you what you have already looked for.

If you are careful selecting how content is accessed, you can change the choices presented by the algorithms. If you use a browser like DuckDuckGo to access content instead of proprietary apps, your tracks are more difficult to follow.  And if you want to see a sudden and startling change in the content that is offered to you, open a browser and type Happiness in the Search bar, you may be surprised at what begins to follow you around.

That result is not in their algorithm, but in ourselves.