THE ETHICS OF AI: ANOTHER STEP IN HUMANITY'S EVOLUTION
Language as Inheritance
You’re reading this because of language.
Not just the alphabet on your screen, but the centuries of accumulated meaning embedded in it. You comprehend these words because someone taught you to read. That someone was taught by another. Teachers, scholars, artists—passing knowledge like torches down a human chain that stretches back thousands of years.
Artists have always learned this way. Students of the Renaissance painted in the style of Caravaggio. Comic book artists channel Jack Kirby. Digital illustrators create riffs on Van Gogh’s Starry Night. We don’t call that theft. We call it tradition. We call it learning.
AI as a Continuation of Human Learning
AI has learned in much the same way, by studying our work. Everything it generates is built on human knowledge. The archives of our species, digitized and made accessible, have become its training set. Now that same knowledge is available to anyone, instantly, anywhere in the world. That is not theft. That is an evolutionary leap.
I’ve lived through a few of those.
The personal computer. The internet. The iPod. The iPhone. Each was dismissed, feared, or misunderstood in its time. Each transformed our culture.
Digital art was once maligned as inauthentic. Digital music was accused of devaluing ownership. Wikipedia was laughed out of academic institutions. All of these critiques were wrong. These tools didn’t degrade creativity or intelligence. They shifted the medium. They widened the circle of participation. They evolved what it means to know, to create, and to share.
That’s what AI is doing now. The way we think, learn, and build is shifting again.
Fear of Change and the Ethics Question
When people invoke "AI ethics," too often it’s shorthand for fear. Fear that the outputs aren’t "real." Fear that creativity is being cheapened. Fear that something sacred is being automated. These are not new fears. They’re the same ones we’ve seen at every major inflection point in the history of knowledge.
We saw them with the written word. Socrates worried writing would destroy memory. We saw them with the printing press, with the typewriter, with the camera, with film, with the internet. And now with AI.
It follows the same curve every time: innovators, early adopters, early majority, late majority, laggards.
This graph is formally known as the Technology Adoption Lifecycle, a model first popularized by Everett Rogers in his book Diffusion of Innovations (1962). It illustrates how different segments of a population adopt a new technology over time: Innovators, Early Adopters, Early Majority, Late Majority, and Laggards. Geoffrey Moore later built on this model in Crossing the Chasm (1991), emphasizing the critical gap between Early Adopters and the Early Majority in tech markets.
Ethics discourse often emerges from the trailing end of that curve. Not because it’s wrong to ask questions, but because the framing is reactive. It sees transformation as threat rather than potential.
Low Effort In, Low Effort Out
AI isn’t making content worse. People are. The old adage still applies: garbage in, garbage out. What most critics are responding to isn’t AI itself—it’s lazy prompting and uncritical publishing. It’s the copy-paste mediocrity that floods feeds with shallow takes and bland insights.
When your starting point is "Write me a blog post about X," and your endpoint is publishing the first unedited output, the problem isn’t the machine. It’s the effort.
Responsible Progress
This is not an argument to abandon caution. Data governance matters. Consent matters. Transparency matters. But the core idea—that machines learning from us is inherently unethical—misunderstands how human learning works.
We’ve always learned from each other. Now our machines are doing it too.
And if you take the time to use AI well—critically, intentionally, and with care—then all you’re doing is stepping forward into the future as a responsible participant in human progress. You’re not bypassing the creative process. You’re evolving it.
We don’t stop progress to protect a romanticized past. We shape it, with clarity, accountability, and full awareness of what’s at stake. The ethics of AI are not about resisting change. They are about ensuring that the future we’re building remains human at the core.
Because AI didn’t invent knowledge. We did.
It’s still our story.
And it always will be.
Historical Citations:
Socrates on writing: Plato, Phaedrus, c. 370 BCE
Printing press impact: Eisenstein, Elizabeth L. The Printing Press as an Agent of Change, 1979
Wikipedia skepticism: Chesney, Thomas. "An empirical examination of Wikipedia's credibility." First Monday, 2006
Digital music & Napster: Gopal, R.D. et al. "The Music Industry in the Digital Era." Communications of the ACM, 2004
