Don't Predict AI's Future - Be Part of It

In edition #9:

• My latest thoughts on what it means to be human in the age of AI: Don't Predict AI's Future - Be Part of It.

• I’d love to hear your thoughts! As ever, get in touch at [email protected] or simply respond to this email.

Don't Predict AI's Future - Be Part of It

In exploring cognitive science through John Vervaeke's work, I discovered how meaning-making isn't just poetically different from computation—the distinction runs deeper. As I discussed in The Science of Meaning, the 4E's of cognitive science demonstrate how human cognition emerges from being embodied, embedded, enacted and extended, through tools. This fourth E—extended cognition—illuminates something fascinating about AI's potential role in human evolution.

I believe AI will be the next frontier of our extended cognition—a psychotechnology as transformative as language itself. Just as language reshaped not only how we communicate but how we think, AI could fundamentally alter human cognitive capabilities. But how can AI shape us? What could this evolution look like? How can we know the answer?

The evolution of language provides a clue. We created language, and then it shaped us— a co-evolution with humanity that’s not static, and that’s on-going, even today. Consider the Greek innovation of adding vowels to their writing system. What seems like a minor adjustment enhanced cognitive fluency in profound ways: it enabled new forms of systematic thought and cultural achievement. Through enhanced literacy and cognitive flow, they developed mathematics, geometry, and entirely new forms of systematic reasoning. These outcomes were impossible to predict. Language shows us that psychotechnologies don't just expand cognitive possibilities; they redefine who we are over time.

As Vervaeke reminds us, "You're a natural born cyborg; you have evolved to be integrated with machines." This insight highlights how deeply technologies shape not just what we do but who we are. To understand AI's impact, we must look beyond its technical parameters and consider how it interacts with our adaptive potential.

This perspective brings social psychologist Erich Fromm's framework into focus. Fromm described two modes of existence: "having" and "being." In the "having" mode, we focus on possession, control, and accumulation—what we own or know. In contrast, the "being" mode centers on active engagement, process, and participation. Fromm also warned of "modal confusion"—the tendency to mistake one mode for the other, such as conflating knowledge about wisdom with being wise.

Could we be suffering from modal confusion in how we approach AI? Consider our obsession with predicting AGI timelines, accumulating facts about AI's latest capabilities, and consuming endless streams of "AI news." These behaviors fall squarely in the "having" mode—they emphasize control, accumulation, and the illusion of understanding. Yet history shows us that meaningful engagement with transformative technologies, like language, requires participation—not merely possessing knowledge about their potential but actively integrating them into our lives and processes. The question, then, is whether we can shift from "having" AI to truly "being" with it.

This shift is central to the concept of extended cognition. As I've explored before, extended cognition emphasizes co-evolution: tools and users shape one another through use rather than prediction. My own early experiences collaborating with AI illustrate this dynamic. Writing and ideation with AI have helped me digest source materials faster, get ideas out more quickly, and reap compounding benefits. These connections with others send me on rewarding tangents that inspire new directions.

Now, as technical barriers dissolve and costs drop, we stand at a new threshold. The marginal cost of generating code, for example, is on a trajectory toward dramatic reductions, as noted by someone with deep experience in code generation for large models. With these technical hurdles falling away, the remaining challenges are not technological—they are cultural.

As one observer aptly put it, "The race is currently between non-technical people who can build coding skills and highly technical people who can tear down their egos." This is not just a race to adopt AI tools but to embrace the kind of collaboration that reshapes cognition itself.

Vervaeke's interpretation of Darwin offers perspective: evolution progresses through selective pressures across a species. Those who resist adapting to AI may find themselves competing against the very tools others use to extend their cognition. Like early human groups who mastered new technologies gained advantages over those who didn't, the ability to collaborate effectively with AI could become a crucial adaptive trait in our cognitive evolution.

Even so, this evolutionary lens should not lead us to simple conclusions. Human cultural evolution remains deeply complex, shaped by countless interacting forces. The real question isn't just what people will do with AI, but what we will become through it. History shows that transformative tools like language don't just enable new possibilities—they reshape us in ways we can't foresee. With AI, the path forward isn't about prediction; it's about participation.

You can't predict; you can only participate. By engaging with AI as a partner in our cognitive evolution, we open the door to new ways of thinking and being, shaped not by control but through collaboration.

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