Every generation faced a technology that changed everything, and the families who engaged early were glad they did. AI is no different.
Every generation has faced a technology that changed everything. Enter AI, and it’s a big one.
People everywhere are trying to figure out AI. What is it? Do I need it? Is it helpful, harmful, both? What are the environmental concerns? Is it the coolest thing ever or the downfall of mankind? Should I use it or wait and see what happens?
Here's the thing: this has happened before. Think printing press, calculator, internet. The technology is different, the implications are different, but the ultimate question is the same: engage or not?
History has a pretty consistent answer.
THE PRINTING PRESS
Let’s start with Europe in the 1400s when Gutenberg introduced the printing press. Scribes argued that mistakes would be amplified by a press, and sure enough, there were lots of errors in early printed books; in fact, there are still errors in printed materials today. Unsurprisingly, widespread access to information mattered more than perfect accuracy in every copy.
A bigger concern across scholars and knowledge gatekeepers of the time was that dangerous ideas would spread. And this concern materialized, leading to the Protestant Reformation, the Scientific Revolution, and eventually democracies. Information overload was also raised as a concern. People would be overwhelmed by too much information and not know what was worth knowing. And if everything could be printed, would we need to remember anything? What would happen to human memory?
But the printing press persevered and in just 50 years, over 20 million books were printed and spread across the continent. Those who learned to read, think critically about what they read, and develop large scale ideas shaped the next century.
Literacy and knowledge were dramatically transformed, and the world has never gone back from this advancement.
THE POWER LOOM
On to the 1780s and the introduction of power looms to the textile industry. A single power loom could do the work of 30 hand-operated looms. Entire skilled trades of artisans and textile workers lost their jobs to machines run by unskilled and underpaid workers, often women and children. Within two working generations, the textile industry displaced many workers with no safety net or transition path.
But… let’s also look at what happened to work as a result. The textile industry didn’t shrink; it exploded as the kind of work completely changed. Factory managers, loom mechanics, engineers, bookkeepers, warehouse workers, retail clerks, and more were needed. The amount of work increased multifold and within two to three generations, real wages and life expectancy had risen measurably.
Granted, many experienced real pain along the way. The highly skilled textile artisans whose craft knowledge had no corollary roles in the new system were heavily affected, while those with transferable skills and proximity to the emerging economy fared better. But again, no going back.
THE CALCULATOR
Now let’s jump to the 1970s and the calculator. Much of the debate about AI today sounds almost word-for-word the same as the calculator concerns. If kids can just use a machine to do the arithmetic, will they actually learn math? Will they stop being able to think? Will they grasp how numbers work? How will they function if the batteries die?
Over the course of the next 20 years, calculators earned their spot in modern math. They were allowed on the AP Calc exam in 1983, but then banned the following year over equity concerns. In 1994, calculators were allowed on the SAT for good. This marked the unofficial end of the calculator debate and their mainstream acceptance.
Interestingly, math education did not suffer a rapid demise. To the contrary, the scope of math in schools expanded, and academics rethought how to teach math. High school students today master math concepts previously only taught in university engineering classes. The breadth of what students understand with the assistance of a calculator has vastly expanded.
The fear was totally understandable, but the outcome ended up looking far better than many expected. Math thinking didn’t disappear, it multiplied. No going back.
THE INTERNET
In 1995, 14% of Americans had access to this thing called the internet. And that access was primarily through dial-up modems… it was unimaginably slow, it tied up your phone line, not much was available online. Most adults either hadn’t heard of it or didn’t really know what it was. Those who did use the internet were typically either academics, Silicon Valley types, or users only interested in email. E-commerce barely existed and not much valuable information could be found online.
Enter new browsers, Windows 95, AOL, real content, and the biggie… broadband. The internet was now always on and dramatically faster. From 1996 to 2000, users grew from 45 million to 400 million. In just five years.
Amazon launched in 1995 selling books. Why books? Because since our earlier invention of the printing press, there were now over 3 million different books in print worldwide. Neither locally owned bookstores nor the shopping center Barnes & Noble could stock them all. But the internet could. In month one, Amazon shipped books to all 50 US states and 45 countries. Proof of concept achieved.
Yet many business experts continued to predict failure. Major corporations like Sears and Whirlpool avoided the internet. Blockbuster later became the defining cautionary tale of the same mistake. In 1995, a highly regarded expert called it a fad. Five years later, a major newspaper headline was still declaring it a passing trend, even as Amazon expanded well beyond books.
I was an early Amazon adopter for books, but never thought they’d succeed with other products. Oops. My Prime account reminds me I was wrong daily.
A key mistake in judging the durability and future of the internet was to assume that computers would stay the same as they were at the time, even though a PC in 1995 was far more powerful than one just five years older. Skeptics saw the internet as it was, not as what it would become.
By 2005, companies who had been wary about the web and its business impact were spending billions trying to catch up; some never did. The ones who engaged early didn't just adapt, they wrote the rules and ultimately changed the game entirely.
Once again, there’s no going back.
Which brings us to the advent of AI. Which was not in 2022, although that’s when many first became aware of artificial intelligence.
In 1950, Alan Turing asked the key question: Can machines think? Then in 1956, the term artificial intelligence was coined at the Dartmouth Conference. Over the next forty or so years, programmers tried to use rules to replicate human knowledge. It worked for some tasks, but couldn’t scale, and often reality didn’t live up to the promises.
In high school, I became fascinated with artificial intelligence after reading The Mind’s I, a book somewhat above my head at the time. I remember reading and rereading passages about consciousness, intelligence, and whether machines could truly think. Crazy how many of those decades-old questions are front and center again.
For many of us, the first time AI really felt tangible was in 1997 when IBM’s Deep Blue beat world chess champion Garry Kasparov, marking the first time a machine beat a reigning champion under tournament rules. A huge moment, certainly, but one tempered by the fact that Deep Blue couldn’t do anything but play chess.
AI seemed to fade from public view in the following years, but behind the scenes, researchers were moving from rules-based systems to machine learning. Instead of setting up concrete rules for a computer to follow, they had computers learn patterns from mass amounts of data. Rules are limited to what is explicitly programmed; patterns are not.
We were all introduced to AI without really realizing it through Google search results, Netflix suggestions, and text autocorrections.
Then along came two more big moments that grabbed public attention. In 2011, IBM’s Watson beat two of the greatest Jeopardy champions ever, Ken Jennings and Brad Rutter, by predicting answers based on patterns learned from massive amounts of data. And then in 2016, Google’s AlphaGo beat the world’s best Go player. Go has more than 10,000,000,000,000,000,000,000,000,000… [add more 0s until there are 170]… positions; it’s not possible to create enough rules to brute-force a Go win. AlphaGo learned to play so successfully that even its creators were surprised.
Now we go to 2017 when a Google research paper introduced the transformer architecture (more on that here). What started as an academic paper became the underlying structure for ChatGPT, Claude, and nearly every major AI model in existence today. But not many of us read academic tech papers, so this went largely unnoticed.
Until…
OpenAI released ChatGPT to the public in November of 2022. Anyone with a browser could now directly interact with AI. Within two months, ChatGPT hit 100 million monthly active users. For comparison, the internet took years to reach the same milestone, TikTok needed nine months, and Instagram took over two years.
Researchers had been working toward this for decades, but with ChatGPT’s launch, AI suddenly became real to the rest of us. Since then, the pace has only picked up and model improvements are now measured in months, not years.
Many of us don’t remember life without a calculator, much less one integrated with a phone that fits in your pocket. And kids today won’t remember life without AI. But in many ways, AI looks more like the internet or the printing press than the calculator. It’s not augmenting one skill like math, but changing how entire industries function. Yes, jobs will be eliminated and skills made obsolete, but new ones will emerge and we need to be ready.
AI isn’t coming. It’s here. There is no going back.
And that’s the answer to the questions we started with: there is no going back.
Ultimately, everyone gets to make their own decision on AI adoption and usage.
We’ll delve more into environmental concerns separately as they are significant and need to be addressed. But as we learned earlier, it’s important not to judge the future by what exists today.
From a usage standpoint, those who learn and adopt AI smartly will have an edge in whatever is coming our way.
AI will be part of our future, and even more so, our kids’ futures. The goal now is to enable them to shape what comes next.
weya Learn is AI literacy for kids and families who'd rather be ahead.