Origin Story
This article did not begin with artificial intelligence. It began with a feeling.
Over the past few years, I have found myself thinking more and more about the technologies that have shaped my life.
I have lived through several major technological transitions. I remember personal computers becoming part of everyday life. I remember the growth of the internet. I remember learning how to navigate online spaces long before social media platforms dominated the web.
Like many people who spent years online, I also remember the conversations that came with those changes.
I remember conversations about computer literacy. I remember teachers, parents, journalists, and ordinary users trying to figure out what it meant to live with computers becoming part of everyday life.
Later, similar conversations emerged around the internet. People debated privacy, digital identity, online etiquette, trust, and responsibility. We did not always agree, but there was a widespread sense that these new technologies required more than technical skills.
There were discussions about how to evaluate information found online. Discussions about how to behave in communities. Discussions about what kind of culture we wanted to create as the internet became a larger part of our lives.
Those conversations were not always successful. Many questions remained unresolved. But the conversations themselves mattered. They reflected a recognition that technology changes more than our tools. It changes habits, relationships, expectations, and ways of thinking.
Recently, I found myself wondering where those conversations had gone. Not because technology stopped changing. If anything, technology is changing faster than ever.
Part of that reflection began while revisiting old versions of my websites through the Wayback Machine. I found pages I had not seen in decades. Looking through them felt less like browsing old websites and more like meeting earlier versions of myself. As I moved through those digital snapshots, I was reminded how often conversations about technology focused on people rather than tools. We talked about communities, communication, trust, learning, and how to navigate a changing online world. The technologies were new, but the questions were deeply human.
The question did not arrive all at once. It appeared gradually through small moments of reflection. Sometimes it emerged while watching public conversations about AI. Sometimes it surfaced while writing about technology and learning. Sometimes it appeared when I noticed how quickly AI tools were becoming ordinary.
The more I paid attention, the more I found myself asking the same question: where are the broader conversations that usually accompany major technological change?
Artificial intelligence is rapidly becoming part of everyday life. Sometimes we use it deliberately. Other times it appears quietly inside the tools we already use. It helps people learn, write, plan, create, communicate, and solve problems. Increasingly, it is becoming part of the background of everyday digital life.
Yet when I look at many discussions about AI, I often notice something missing. The conversation frequently focuses on what the technology can do. Much less attention is given to how we should live with it. How should we think when answers are always available? What responsibilities remain ours? What skills should we continue developing for ourselves? How do we remain active participants rather than passive consumers?
The more I reflected on these questions, the more I realized that they felt familiar.
Not because I had encountered AI before. But because I had encountered similar questions during earlier technological shifts. That realization became the starting point for this essay. Not a concern about AI itself. A concern that we may be normalizing the technology before we have fully explored what it means to live alongside it.
The conversation is happening. But I am not sure we are having the whole conversation yet. This essay is an attempt to explore the parts that seem to be missing.
Core Thesis
Artificial intelligence is becoming part of everyday life at remarkable speed. People use it to write, learn, plan, create, communicate, research, organize information, and solve problems. AI systems are increasingly embedded in the tools we use every day, often so seamlessly that we stop noticing them.
There is no shortage of conversation about the technology itself. We debate which models are best. We compare features, capabilities, risks, regulations, and market impacts. New tools appear almost daily, each promising to make some aspect of life faster, easier, or more efficient.
What feels missing is a broader conversation about what it means to live alongside these systems. How should they influence the way we learn? What happens to thinking when answers become effortless? Which responsibilities remain human, even when parts of a task can be delegated to a machine? What skills become more important rather than less? What habits are these systems encouraging, and are those habits helping us become the kinds of people we want to be?
These questions are not primarily technical. They are human. Yet they often receive far less attention than discussions about features, performance, or productivity. As a result, it sometimes feels as though we are normalizing the technology before we have normalized the conversation around it.
We are adopting AI into our daily lives at extraordinary speed, while many of the cultural, educational, ethical, and personal discussions that usually accompany major technological shifts remain incomplete.
This essay explores that gap. Not because AI is uniquely dangerous. Not because previous technologies were handled perfectly. But because every generation inherits the responsibility of learning how to live well with the tools it creates. The question facing us is not simply what AI can do. The deeper question is what kind of relationship we want to have with it.
Part 1: Before AI Literacy
Long before anyone talked about AI literacy, we spent decades learning how to live with other technologies.
When personal computers began appearing in homes, schools, and workplaces, many people found them intimidating. Learning to use a computer wasn’t simply a matter of buying one. People had to learn an entirely new set of skills. They learned how files worked, how software was installed, how to save documents, and how to recover from mistakes when something inevitably went wrong.
The phrase “computer literacy” became common because society recognized that technology alone was not enough. People needed knowledge, confidence, and understanding if they were going to participate in this new digital world.
The arrival of the internet introduced a different challenge. Knowing how to operate a computer did not automatically mean knowing how to navigate an online environment. Suddenly people had access to vast amounts of information, much of it unfiltered. New questions emerged.
How do you know whether a website is trustworthy? How do you find reliable information? How should you communicate with people you have never met? What responsibilities do you have when participating in an online community? These questions gave rise to conversations about internet literacy, digital citizenship, and media literacy.
What interests me now is that many of these discussions were never really about technology. At least not primarily. Computer literacy was not ultimately about computers. Internet literacy was not ultimately about the internet. They were about helping people adapt to a changing environment. They were attempts to answer practical human questions. How do we learn in this new world? How do we evaluate information? How do we communicate responsibly? How do we participate in communities? How do we make good decisions when old assumptions no longer apply?
The technologies provided the context, but the conversations were about human behavior. The goal was never simply to teach people how to use a tool. The goal was to help people live well with it.
That is why I find myself thinking about them again today. Because when I look at the current conversation around AI, I often see discussions about tools, models, prompts, and features. What I see far less often are the broader questions that accompanied earlier technological shifts. Questions about how we should think. How we should learn. How we should make decisions. And what responsibilities remain ours, even when technology becomes increasingly capable.
Part 2: When Technologies Become Invisible
One of the most interesting things about technology is that truly successful technologies eventually disappear. Not physically. They simply stop attracting our attention.
Few people spend much time thinking about electricity. Most of us do not wake up in the morning and marvel at the fact that lights turn on when we flip a switch. We rarely discuss telephone literacy. We do not gather to debate how to use refrigerators, washing machines, or indoor plumbing. These technologies have become infrastructure. They are still important, perhaps more important than ever, but they have become so deeply woven into everyday life that we mostly stop noticing them.
The same thing happened with computers. There was a time when owning a computer felt unusual. Learning how to use one felt like a skill worth mentioning. Computer literacy courses were common. Schools taught basic computer skills. Adults attended classes to learn how these new machines worked.
Today, many of those skills are simply assumed. The computer did not disappear. The conversation around it did. The internet followed a similar path. In its early years, people spent a great deal of time talking about online life itself. There were discussions about digital identity, online communities, privacy, etiquette, and how to evaluate information found online. Entire books were written about navigating the internet safely and responsibly. As the internet became part of everyday life, many of those conversations faded into the background.
People still discuss online safety and misinformation, of course. But the broader cultural conversation became quieter. The internet stopped feeling like a destination and started feeling like part of the environment. It became normal. And once something becomes normal, we often stop examining it.
That may be one of the reasons technology can shape our lives so profoundly. The moment when we are most likely to question a technology is often when it is new. Once it becomes familiar, many of the deeper questions lose visibility. We stop asking how the technology is changing us because the changes have become part of everyday life.
This is not necessarily a problem. In many cases, it is simply what happens when a technology matures. We cannot continuously debate every tool we use. Yet normalization can have a side effect. The more familiar a technology becomes, the less likely we are to notice how it is shaping our habits, expectations, and assumptions.
What happens when the conversations disappear before we have fully explored them? What happens when a technology becomes ordinary while important questions remain unresolved? Looking back at the history of computers and the internet, I sometimes wonder whether we lost some valuable conversations along the way. Not because the technologies themselves were harmful, but because familiarity made them seem less worthy of examination. The tools became invisible. The questions often became invisible with them. If that pattern holds true for AI, then this may be one of the most important moments to ask those questions while they are still visible.
Part 3: AI Became Normal Too Fast
Every major technology begins as something new. At first, only a small number of people use it. Early adopters experiment with it. Experts debate its potential. Journalists speculate about how it might change the world. Then, gradually, it spreads. Personal computers, the internet, and smartphones all followed this pattern.
But AI feels different. Not because it is necessarily more important than those technologies, but because of how quickly it has moved from novelty to normality. Just a few years ago, most people rarely interacted with AI directly. Today, millions of people use it every day, often multiple times a day.
Students use it while studying. Professionals use it at work. Writers use it while drafting. Creators use it while brainstorming. Increasingly, AI is appearing wherever information, communication, or creative work takes place.
It is appearing inside search engines, office software, phones, customer service systems, and countless other digital tools that people already use every day. Even people who never intentionally open an AI chatbot may encounter AI-generated summaries, recommendations, suggestions, or responses throughout their day.
In a remarkably short period of time, AI has gone from a specialized technology to an everyday presence. What makes this transition particularly interesting is that many people do not even think of themselves as AI users.
When we sit down at a computer, we know we are using a computer. When we browse a website, we know we are using the internet. Unlike early computers or the early internet, AI does not always announce itself as a new place to go. Increasingly, it appears inside systems people already use. It is becoming woven into existing tools rather than standing apart from them. That may be one reason its adoption feels so rapid. People are not always choosing a new technology. Sometimes the technology is simply appearing inside familiar environments.
As a result, AI is becoming integrated into daily life at a speed that few technologies have experienced. And while adoption has accelerated, the broader cultural conversation seems to be struggling to keep pace.
Much of the public discussion focuses on capabilities. What can AI do? Which model performs best? Which tool saves the most time? Which features are worth using? These are understandable questions. But they are not the only questions. In fact, they may not even be the most important ones.
Because while we are busy evaluating what AI can do, we are spending far less time discussing how widespread AI use might influence the way we learn, think, create, communicate, and make decisions.
The technology is becoming normal. The habits are forming. The workflows are being established. The expectations are changing. All of this is happening in real time.
Yet many of the deeper conversations that accompanied earlier technological shifts remain surprisingly underdeveloped. That is what makes this moment feel unusual to me. It is not simply that AI is becoming part of everyday life. It is that AI may be becoming part of everyday life before society has fully explored what that means.
The technology is arriving first. The conversation is trying to catch up.
Part 4: The Conversation We Haven’t Had
Spend a few minutes browsing discussions about AI and certain topics appear again and again. Which model is best? Which tool is most accurate? Which prompts produce the best results? Which workflow saves the most time? How can AI make us more productive?
These are reasonable questions. Whenever a new technology emerges, people naturally focus on its capabilities. We want to know what it can do, how well it performs, and how it compares to competing alternatives.
But the more time I spend observing conversations about AI, the more I find myself wondering about the questions that receive far less attention. Not technical questions. Human questions. Questions that are harder to measure and harder to answer. For example: What skills should we still learn ourselves? What skills are safe to outsource? What happens when convenience and understanding are no longer the same thing? What does it mean to truly know something when information is available instantly? How much thinking should we delegate? How much thinking should remain our own?
These questions are not new. In one form or another, every generation faces them. But AI places them in a new context.
For the first time, many people have access to systems that can explain, summarize, brainstorm, draft, analyze, and answer questions in ways that resemble human reasoning. That creates opportunities. It also creates temptations. When an answer appears instantly, it becomes easy to mistake access for understanding. When an explanation sounds convincing, it becomes easy to mistake clarity for truth. When a task becomes easier, it becomes easy to stop asking what part of the process was actually valuable.
None of this means people should avoid AI. It simply means we may need better questions than “Can AI do this for me?” Perhaps we should also ask: What am I gaining by using AI here? What might I be losing? What skills am I strengthening? What skills am I allowing to weaken? Am I using this system to expand my thinking, or to replace it?
These are not questions that can be answered by benchmarks, model comparisons, or product reviews. They are questions about habits. About judgment. About responsibility. About what kind of relationship we want to have with increasingly capable tools.
And these are precisely the kinds of conversations that seem surprisingly absent from much of the public discussion. We spend enormous amounts of time discussing what AI can do. We spend far less time discussing what we should do with it. That difference may be more important than it first appears.
Part 5: The Return of Human Questions
When I think back to the early years of the internet, one question appears again and again. How should we behave here? People asked it in different ways. What counts as respectful communication? How should online communities be moderated? What responsibilities do we have toward one another? How much privacy should we expect? What kind of culture are we trying to create?
If earlier forms of literacy helped people navigate information, communities, and digital environments, then AI literacy may increasingly involve navigating our relationship with thinking itself. Perhaps the AI era requires a similar conversation. Not exactly the same conversation, but one built around a different question. How should we think here?
That question feels both simple and surprisingly difficult. AI is not merely a new source of information. It is increasingly becoming a participant in activities that were once considered deeply human. Learning. Writing. Planning. Problem-solving. Brainstorming. Decision-making.
As a result, many of the questions we face are not really technical. They are questions about judgment. When should we trust an AI-generated answer? When should we verify it? When should we rely on our own experience instead? They are questions about learning.
If AI can explain a concept in seconds, what does genuine understanding look like? How do we distinguish between having access to an explanation and actually knowing something? They are questions about curiosity.
Can AI help us explore ideas we might never have encountered on our own? Can it encourage deeper thinking? Or does convenience sometimes tempt us to stop exploring too soon? They are questions about responsibility. If an AI system helps us make a decision, who remains accountable for the outcome? Who bears responsibility when something goes wrong? And perhaps most importantly, they are questions about agency.
As AI systems become more capable, how do we ensure that they remain tools rather than substitutes for our own judgment? How do we remain active participants instead of passive recipients? These are not questions that can be answered once and for all.
Different people will arrive at different conclusions. The answers may evolve as the technology evolves. But the questions themselves matter. In fact, asking them may be one of the most important parts of AI literacy. Because literacy has never been solely about understanding a tool. It has also been about understanding ourselves in relation to that tool.
The early internet eventually forced us to ask how we should behave online. Perhaps AI is asking us something equally important. Not how we should behave. But how we should think.
Part 6: AI Literacy Is Not Really About AI
When people talk about AI literacy, they often focus on understanding AI itself. How do these systems work? What are their strengths and limitations? How do you write effective prompts? How can you identify errors or hallucinations?
These are valuable skills. Anyone using AI regularly should develop a basic understanding of the tools they are working with. But the more I think about AI literacy, the more I wonder if we are focusing on the wrong part of the phrase.
Perhaps the most important word is not AI. Perhaps it is literacy. Historically, literacy has never been simply about mastering a tool. Reading literacy is not merely the ability to decode words on a page. Media literacy is not merely the ability to consume media. Digital literacy is not merely the ability to operate a device. At their deepest level, these literacies are about helping people navigate a changing environment thoughtfully and responsibly.
They are about participation. Judgment. Understanding. Adaptation. In that sense, AI literacy may not primarily be about understanding artificial intelligence. It may be about understanding what it means to remain fully human in a world where artificial intelligence is increasingly present.
The skills that matter most may not be technical skills. Prompt writing will change. Models will improve. Interfaces will evolve. Specific tools will come and go.
The history of technology suggests that many of today’s technical skills will eventually become obsolete. The deeper skills are more likely to endure. Judgment. The ability to evaluate information rather than simply accept it. Skepticism. The willingness to question answers that sound convincing. Reflection. The habit of thinking about how tools influence our decisions and behavior. Curiosity. The desire to continue exploring rather than settling for the first available answer. Adaptability. The capacity to learn as technologies change. Responsibility. The recognition that accountability remains human, even when machines participate in the process.
None of these skills are unique to AI. In fact, that may be the point. The technologies change. The underlying human challenge remains surprisingly familiar. Every generation encounters new tools that promise greater convenience, greater efficiency, or greater capability. And every generation must decide how those tools fit into a meaningful human life. AI may simply be the latest version of that challenge.
This is why I find myself increasingly skeptical of definitions of AI literacy that focus exclusively on technical knowledge. Understanding how AI works is important. But understanding how AI affects our thinking may be even more important. Knowing how to use a tool matters. Knowing when to use it, when to question it, and when to rely on your own judgment may matter even more.
Perhaps the ultimate purpose of AI literacy is not to help us become better users of AI. Perhaps its purpose is to help us remain thoughtful participants in a world where AI is becoming impossible to avoid. That is a very different goal. And it may be the one that matters most.
Part 7: The Risk of Silence
One of the things that concerns me most about AI is not the technology itself. It is the possibility that some of the most important conversations may never happen.
With earlier technologies, society often had time to debate, argue, and reflect before those technologies became fully embedded in everyday life. The discussions were imperfect. Many questions remained unresolved. But there was at least a period during which people actively wrestled with the implications of the changes taking place around them.
AI feels different. The technology is spreading so quickly that many of the habits, expectations, and norms surrounding its use are being established before broader public discussions have had time to develop. People are already using AI to learn. To write. To make decisions. To communicate. To solve problems. To create. These practices are no longer hypothetical. They are becoming part of everyday life.
And while they continue to expand, many of the deeper questions remain surprisingly easy to avoid. What are we gaining? What are we losing? What kinds of thinking should remain ours? What responsibilities cannot be delegated? What happens when convenience becomes the default answer to every challenge? What parts of learning are worth preserving even when technology can make them easier?
These questions do not have simple answers. But unanswered questions do not disappear. Sometimes they simply fade from view.
History suggests that once a technology becomes part of everyday infrastructure, people stop examining it as closely. What once felt novel becomes normal. What once felt worthy of discussion becomes background noise.
That may be happening faster with AI than with many previous technologies. The habits are forming now. The expectations are forming now. The norms are forming now. Long before society reaches agreement about what those norms should be.
That is what makes this moment feel significant. Not because we must arrive at a single correct answer. Not because technological progress can be paused until every concern has been resolved. But because we still have an opportunity to examine these questions while they remain visible.
If we fail to ask them now, we may gradually accept assumptions that were never consciously chosen. We may drift into habits without ever examining them. We may allow efficiency to define success without considering what other values matter. We may focus so heavily on what technology can do that we neglect to ask what kind of people we want to become while using it.
Silence does not prevent change. Technology will continue to evolve whether we discuss it or not. New systems will appear. New capabilities will emerge. New habits will form.
The question is whether those habits will be examined while they are forming or only after they have become difficult to notice. The answers may remain uncertain. The questions do not have to disappear.
Part 8: Maybe Literacy Is Never Finished
As I have worked through these ideas, I keep returning to a simple thought. Perhaps literacy is not something we achieve once and for all. Perhaps it is something we keep practicing throughout our lives.
When computers became common, people talked about computer literacy. When the internet transformed communication, people talked about internet literacy. As digital media became increasingly influential, conversations about digital literacy and media literacy emerged.
Now we are talking about AI literacy. At first glance, these may seem like separate challenges. But I am no longer convinced that they are. The technologies are different. The questions are remarkably similar. How do we evaluate information? How do we make good decisions? How do we communicate responsibly? How do we remain curious? How do we adapt to change without surrendering our judgment? How do we use powerful tools without allowing them to make all of our choices for us?
The answers evolve as technology evolves. But the underlying challenge remains. Perhaps every major technological shift asks us to revisit the same human questions in a new form. Not because we failed to learn them the first time. But because each new environment reveals different aspects of them.
That realization has changed how I think about AI literacy. I no longer see it as a destination. I do not believe there will come a moment when society finally becomes “AI literate” and the conversation is complete.
The technology will continue to change. New tools will appear. Old assumptions will become outdated. New opportunities and new concerns will emerge.
The conversation will need to continue. At first, that can feel unsatisfying. We often want literacy to be something we achieve, a destination we eventually reach. Maybe that is not a weakness. Maybe that is exactly what literacy has always been. Not a certificate. Not a checklist. Not a fixed body of knowledge. A practice. A habit of paying attention. A willingness to question, learn, adapt, and reflect as the world changes around us.
Seen from that perspective, AI literacy may not be a completely new challenge at all. It may simply be the latest chapter in a much older human story. A story about our relationship with tools. A story about learning how to live alongside technologies that continually reshape our world.
And perhaps most importantly, a story about how we remain thoughtful, capable, responsible human beings as those tools become increasingly powerful.
The conversation about AI is often framed as a conversation about machines. I suspect it is really a conversation about us. And unlike the technologies themselves, that conversation is never finished.