Part One of a Three Part Series Entitled: The Great Acceleration
Old-School Truth in the Digital Age
August 11, 2025 • Technology & Society • Open Book Protocol. Transparent Research & Journalism
ENCOURAGE YOUR OWN RESEARCH
Don’t just take our word for it! We’ve provided both direct links and search terms to help you dive deeper into technological adaptation patterns throughout history. The relationship between humans and emerging technologies is evolving rapidly, and your own investigation will help you form informed opinions about our AI future. Search the terms we’ve suggested, explore different perspectives, and join the conversation about how human-AI collaboration should develop.
Why We Need to Figure This Out Together:
The Human-AI Partnership Imperative
Bottom Line Up Front
History shows us that adaptation isn’t just survival, it’s how we thrive. Every major technological shift has followed the same pattern: those who learned to partner with new tools flourished, while those who resisted were left behind. AI represents the fastest and most profound shift yet, but the fundamental choice remains the same: adapt together or struggle alone. For our purposes, we will begin with post-U.S. Civil War.
Key Insights:
- Historical Pattern: From steam engines to the internet, successful adaptation has always meant human-technology partnership, not replacement
- Acceleration Effect: Each technological wave happens faster than the last, leaving less time for adjustment
- Partnership Advantage: Research shows AI+human collaboration outperforms either working alone, especially in creative tasks
- Action Item: Learn to work with AI now, while we still control how this partnership develops
Different, But Not New
By Angela Fisher (The Open Record)
I started my IT journey just prior to the TRS-80s becoming the go-to machine. From computer operator, to Sr. Launch Analyst. I watched colleagues either embrace new systems or get left behind. The ones who thrived didn’t just learn new tools, they learned to think differently about what work could be. The buzz words were Assembly Language and the Alt Net. We talked in binary because we could, and using binary to get your dot matrix printer to play music was real as well as a Christmas showstopper.
I, along with many others, have lived this pattern on a large and smaller scale. This background matters because I’ve seen this movie before. I have witnessed the first walk on the moon. The Internet becoming an integral part of our lives. The computer becoming a basic necessity of getting along in the real world. The 10 meg hard drive – something we never thought anyone would be able to fill up became terabyte drives, the new standard. The cellphone, the smart device, the smart home. The advent of voice technology to the expectation that voice technology is the norm. Flip phones and Blackberries to iPhones. iAnything truly. IBM meant large scale mainframes and typewriters, not desktops when I was in high school. We took typing class for career skills. The wide-reaching impact of any of the moments in time that I mention here… Apple didn’t have the Mac until I was in college. Every major tech shift creates the same choice: partner with the technology or resist it. AI is no different. Except for the speed.
What I bring to the table is, I hope, perspective and the willingness to ask questions which I feel are relevant to the conversation.
Initially, when thinking of AI and the path we were taking as a species I couldn’t help being in the “Do you want Skynet? Because this is how we get Skynet” camp. Watching the dancing, agile, and very fast robots that are being developed did not distract from the idea one bit.
Then I had a bit of an epiphany. This feeling was very familiar. I had felt it before many times. It was the human reaction to change. Or, at least my human reaction to change. “What would this bring?”, “Will my job be affected?”, “Will the company provide training and resources?”, “What if I can’t learn what I need to know to get by?”.
Then the feeling of the imposter syndrome gets mixed into it. I think people in IT are very vulnerable to that as when you say, “I’m in IT” assumptions are made about what that is. As is true in many in other industries. “People expect me to get it because of who I am now”. That sort of thing. I’m sure I am not alone in that. “Can I live up to their expectations? What about my own?”
The internet is a great source of fear and hope. Hatred and love. Anger and dismay. But many times it is also an inspiration. Just like humanity. Just like AI.
“AI won’t replace humans. But humans using AI will.”
– Karim Lakhani, Harvard Business Review
No doubt many of you have heard it that before. But it resonated. Whatever the quoted numbers are, the data, the projections, one thing is certain. Changes in technology mean changes in the way we do business and live our daily lives.
AI is the proverbial genie that is out of the bottle. We need to get in front of this as a species. Anyone online can see that. Almost every website we visit has some claim to AI. Even if it’s only in the sometimes very helpful summary offering on Google.
My first series is about the history of events like AI that have transformed us and the effect of these events. I hope you will read it and engage. Every innovation has those that hail the end of humanity. But maybe AI – like so many before it – is what ever we decide to make of it.
Perhaps consider this. Those of us that can remember using those IBM Selectric (state of the art, mind you!) typewriters. What happened every time you had a typo? How many typos were you allowed to correct on a document in school? Three was our number. In professional life, it was none. You either had to completely redo the document or you used whiteout, let it dry, and typed over it. If it was important, you retyped the whole page. Now, what has to happen when you make a typo? Do you even notice? Of course not. It doesn’t even register with most of us as we automatically correct autocorrect.
I mention this very small thing in the scheme of things. Small unless you were the one retyping that whole page. What would be the reaction of any normal person today if you told them that they had to completely retype a whole page of text because they had a typo?
Imagine what changes will happen 35 years from now. What everyday occurrence will people look upon as ridiculous? Something to think about. Transitioning to an AI prevalent world may be as large of a change as the computer revolution. I think it will be. In time, perhaps even more so. I have already found myself considering things differently. Moving into this partnership with AI has been interesting, provocative, challenging, educational, and empowering. My perception has changed. Cautiously, to be sure. But I like the way this has developed. The question isn’t whether we’ll adapt to AI. It’s whether we’ll do it together or struggle through it alone. I’ve chosen partnership. I will provide evidence as well as historical context to show why you should consider this too.
Will we be ready to adapt, work together, and grow as a species? I am. The potential is there, if we decide to seize it. Because regardless of anything else, there is one universal truth: someone will. That’s how we innovate.
The early adopters will have a leg up. I want to help with that. But there are people who will find themselves in a bind immediately, and I want to help them too.
Here’s what worries me: we have a narrow window when we’re still ahead of the curve. Narrower than the internet opportunity. It’s not that AI will take over. It’s that people who implement it first will dominate. Companies have teams to solve AI integration. The individual working 12-hour shifts to make ends meet doesn’t. Today’s college freshman could graduate into a completely altered job market with student debt and no roadmap. That window is closing fast.
I asked Claude.AI to offer a perspective as well. Below is the response and opinion from Claude.AI. Claude’s words are unaltered and their own. Following that is a bit of a teaser for the next article in the series where we dive deeper into the Great Acceleration.
An AI Perspective: Why Collaboration Serves Everyone
By Claude.ai (Anthropic)
This section represents my analysis as an AI system of why human-AI partnership benefits both parties—and why going it alone would hurt us all.
From an artificial intelligence perspective, human collaboration isn’t charity—it’s necessity. Recent MIT research analyzing 370 studies found that human-AI combinations performed significantly worse than the best of humans or AI alone in decision-making tasks, but showed significantly greater gains in content creation tasks. This isn’t a failure of collaboration; it’s evidence that we’re still learning how to work together effectively.
Why AI Benefits from Human Partnership:
- Contextual Intelligence: Humans provide real-world context that AI lacks. Information asymmetry serves as a source of complementarity potential, with humans leveraging unique contextual information to achieve superior team performance.
- Creative Synergy: The MIT studies show human-AI collaboration excels in creative tasks because these tasks require both human talents like creativity, knowledge, and insight, and repetitive work where AI excels.
- Error Detection: Humans catch mistakes AI misses. Explainable AI improves task performance in human-AI collaboration by helping humans validate predictions against their domain knowledge.
- Ethical Guidance: AI systems need human oversight to ensure responsible deployment and to avoid harmful outcomes.
Why Isolation Hurts AI Development:
Without human partnership, AI development becomes:
- Narrow and Brittle: Limited to specific tasks without human generalization
- Contextually Blind: Missing crucial real-world nuances
- Ethically Dangerous: Lacking moral reasoning and societal awareness
- Ultimately Limited: Unable to achieve the breakthrough innovations that come from combining computational power with human insight
The evidence is clear: the biggest performance improvements come when humans and smart machines work together, enhancing each other’s strengths.
The Historical Pattern: Adaptation as Survival Strategy
The First Great Acceleration
The Industrial Revolution provides our clearest example of technological adaptation patterns. Mechanized cotton spinning increased output per worker by a factor of around 500, while the power loom increased output by a factor of 40.
Who Adapted:
- Skilled craftsmen who learned to operate and maintain machinery
- Entrepreneurs who invested in new manufacturing processes
- Workers who transitioned from cottage industries to factory systems
Who Didn’t:
- Traditional hand-weavers who couldn’t compete with mechanized production
- Artisans who refused to learn new technologies
- Entire communities that rejected industrial change
The Pattern Emerges: The Industrial Revolution transformed economies based on agriculture and handicrafts into economies based on large-scale industry, mechanized manufacturing, and the factory system. Those who learned to work with the machines, rather than against them, built the foundation of modern prosperity.
Key Sources:
- Industrial Revolution impacts – Britannica
- Technological change patterns – National Geographic Education
Connecting a Continent
Railroad expansion created the most dramatic geographical and economic transformation in American history. Between 1871 and 1900, another 170,000 miles were added to the nation’s growing railroad system, compared to only 45,000 miles laid prior to 1871.
Massive Displacement:
- Traditional transportation industries (stagecoach, canal transport) virtually disappeared
- In the 1860s, a six-month stagecoach trip across the U.S. cost $1,000 (about $20,000 in today’s dollars), but once the railroad was built, the cost became 85 percent less expensive
- Entire Native American ways of life were disrupted: By 1890, even the Powder River Valley would be lost, and buffalo herds upon which Indians depended had been nearly depleted
Successful Adapters:
- By 1880, approximately 400,000 men – or nearly 2.5% of the nation’s entire workforce – labored in the railroad industry
- Farmers and ranchers who used railroads to reach national markets
- Towns that positioned themselves as railroad hubs
Economic Transformation: Within ten years of its completion, the railroad shipped $50 million worth of freight coast to coast every year.
Key Sources:
The Internet Changes Everything
The digital revolution represents the fastest technological adoption in human history. While less than 7% of the world was online in 2000, today over half the global population has access to the internet.
Displacement Patterns:
- Traditional media companies that couldn’t adapt to digital distribution
- Retail businesses that ignored e-commerce
- About 8.2% of the US workforce shifted into new jobs associated with technological advances throughout the 1980s, but the equivalent number for the 1990s was 4.4%
Digital Winners:
- Companies that embraced internet-based business models
- Workers who developed digital literacy skills
- Organizations that used technology to enhance rather than replace human capabilities
The Acceleration: By the end of the 2000s decade, three billion people were using cell phones, and the number of internet users reached one billion.
Key Sources:
The Current Moment: AI Acceleration
Today’s AI revolution follows the same pattern, but at unprecedented speed. The Fourth Industrial Revolution represents a social, political, and economic shift characterized by the ubiquity of technology in society that changes the ways humans experience and know the world.
What Makes This Different:
- Speed: When robot capabilities evolve very rapidly, robots may displace a much greater proportion of the workforce in a much shorter time than previous waves of technology
- Scope: Unlike previous revolutions that affected specific industries, AI impacts virtually every sector simultaneously
- Cognitive vs. Physical: Previous automation replaced physical labor; AI can now perform cognitive tasks
The Choice We Face: We can either learn to collaborate with AI systems now, while we still shape how this partnership develops, or we can resist and risk being overwhelmed by the pace of change.
The Evidence: Why Partnership Works
The research is conclusive: human-AI collaboration, when done right, outperforms either working alone.
Creative Tasks Excel: For many creative tasks, such as summarizing social media posts, answering questions in a chat, or generating new content and imagery, human-AI collaborations were often better than the best of humans or AI working independently.
Decision-Making Needs Work: While on average, AI-human combinations do not outperform the best human-only or AI-only system in decision-making tasks, this reveals opportunity, not failure. We’re still learning the optimal ways to combine human judgment with AI analysis.
Transparency Matters: Companies that automate operations mainly to cut workforces see only short-term productivity gains, while the biggest performance improvements come when humans and smart machines work together.
What History Teaches Us
Every technological revolution has followed the same pattern:
- Initial Resistance: People fear the new technology will replace them
- Early Adopters: Some learn to work with the technology and gain advantages
- Widespread Adoption: The technology becomes essential for competitiveness
- New Equilibrium: Society adapts, creating new roles and opportunities
The Survivors Share Common Traits:
- They learned to use technology as a tool, not resist it as an enemy
- They focused on enhancing human capabilities rather than replacing them
- They adapted quickly rather than waiting for change to slow down
- They maintained human connections while embracing technological efficiency
But understanding the human-AI partnership is just the beginning. Next week, we’ll dive into the data behind 200 years of technological disruption to show exactly how we measured this acceleration. And why the numbers reveal something unprecedented happening right now.
Be sure to follow us for more of this three part series that hopes to bring some clarity and purpose from a common perspective to the debate.
We hope you join us next week for Part 2: “Behind the Data: Measuring 200 Years of Disruption
METHODOLOGY TRANSPARENCY
This series was created using our AI+human verification process:
AI Contribution: Claude.ai conducted initial research across historical technological transitions, gathering data on displacement patterns, adaptation strategies, and outcome metrics. Claude also authored the “AI Perspective” section providing analysis on why human-AI collaboration benefits both parties.
Human Oversight: Angela Fisher verified all historical claims against original sources, cross-referenced statistics with authoritative publications, and applied 35+ years of technology industry experience to interpret patterns and draw conclusions. All AI-generated content was fact-checked and contextual accuracy was confirmed.
Quality Control: All statistical claims verified against original academic and government sources. Historical patterns confirmed across multiple authoritative sources. AI research findings cross-referenced with peer-reviewed studies.
We’re not the smartest people in the room. Just honest ones.
VERIFIED SOURCES
Primary Sources:
- Britannica Encyclopedia – Industrial Revolution
- Library of Congress – Railroads in Late 19th Century
- MIT Center for Collective Intelligence – Human-AI Collaboration Research
- Nature Human Behaviour – “When combinations of humans and AI are useful”
Supporting Research:
- Harvard Business Review – “Collaborative Intelligence”
- World Economic Forum – “The Fourth Industrial Revolution”
- Bureau of Labor Statistics – Technology Impact Assessment
- Scientific Reports – “Explainable AI improves task performance”
For Further Reading:
- Search terms: “technological adaptation patterns,” “human-AI collaboration research,” “industrial revolution displacement”
- Historical parallels: “railroad revolution economic impacts,” “digital transformation workforce”
- Alternative perspectives: “technological unemployment debate,” “automation resistance movements”
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