“What do we lose when machines create?”

“What do we lose when machines create?” I find myself asking this as I watch the words form on the screen, generated in seconds by an AI model trained on vast swaths of human language. The process feels like magic: efficient, boundless, tireless.

But magic often comes with a price, doesn’t it? Robert K. Logan, in The Alphabet Effect, traced how the phonetic alphabet fundamentally altered human thought, fostering systems like science, law, and individualism. Today, generative AI carries that torch, pushing abstraction even further, transforming how we create, communicate, and comprehend. But as Logan reminds us, such transformations come with consequences.

The Legacy of Abstraction

Logan’s central argument is that the phonetic alphabet revolutionized human cognition by breaking language into abstract symbols, allowing for deductive logic, codified laws, and universal principles. It wasn’t just a tool—it was a lens through which we saw the world. Generative AI extends this legacy, using algorithms to turn patterns into stories, visuals, or even ideas. The alphabet organized sounds into symbols; AI organizes data into outputs that mimic human creativity.

But Logan warned of a critical tension: abstraction, while powerful, creates distance. The alphabet’s ability to standardize and systematize thought came at a cost—it moved us away from relational, embodied forms of knowing.

Think about the passing of knowledge and wisdom prior to writing. It would always be in groups of people or one-on-one listening to another speak or teach. Humans together. Then writing created books and documents that could be stored and read individually, by oneself without others needed at any desired time.

Similarly, AI’s ability to mimic human creativity risks stripping creation of its context, intention, and humanity. Does a poem generated by AI carry the same weight as one born from lived experience? Does art lose its soul when produced without struggle or purpose?

A Mirror or a Substitute?

Generative AI, like the alphabet, is a tool—but tools shape us as much as we shape them. The phonetic alphabet, Logan argued, didn’t just encode language; it changed how we think, encouraging analysis and categorization. Generative AI does the same, but at a scale unimaginable to Logan’s time. It democratizes creativity, enabling anyone to produce art, music, or prose. Yet it also centralizes power, leaving questions about who controls these tools—and who profits from them.

The ethical stakes are high. What does it mean to create when machines can mimic us so seamlessly? If the alphabet fostered individualism, does AI threaten it by automating originality? And what happens to the deeply human act of care embedded in creation—when we write for someone, paint to process a feeling, or tell stories to pass on meaning?

Reimagining Creation

“What do we lose when machines create?” The question evolves as I think about Logan’s legacy. It’s both about what we lose and what we might gain if we approach AI thoughtfully. Logan saw the alphabet as a foundation for systems that fostered human progress—science, democracy, and law. AI, too, can be a foundation, but only if we remember that its strength lies in enhancing, not replacing, human connection.

The next time an AI writes a story, paints an image, or generates a song, ask: What is the purpose? If we use it to explore ideas, to empower more voices, to collaborate in ways we couldn’t before, then perhaps we are not losing the human touch but expanding it. But if we let it replace care, intention, and connection, then we risk creating a world of hollow words and empty art.

In Logan’s words, the alphabet gave us “a way of seeing.” Generative AI now asks us to decide: What do we want to see? And who do we want to be?