The Hitchhiker’s Guide to Post-Post Modern Sapeocentrism
When I wrote this piece, I had a riddle in mind: if Google is a database of human intentions and Facebook is our collective autobiography, then Twitter and Instagram are digital synapses in an overall intelligence that has yet to awaken.
You might think differently, given the current social media milieu. Sample your friends' updates and you won't ascribe "superintelligence" to any of it. Still, the world of social platforms seems to herald the ultra-wired future. They are seeds of something we don't yet understand: evolving snapshots of human phenomena.
As early as 2007, at a Yankee Group talk in Boston, a senior analyst described a coming global network that would be "behaviorally adaptive, personally curative" — an uninterruptible, adaptive network. I noted the prediction and have tracked the confusion and debate about AI ever since.
(The root "sapeo" comes from the Latin sapiens — wisdom, knowledge. Sapeocentrism is a way of relating that is, by definition, exclusive and elite.)
We can say with some certainty that the world of 2025 will be entirely sapeocentric: most of our interactions, with things and with each other, will involve machine-derived intelligence. The media technologies of that society will share traits. Our experiences will be "glocal" — rooted in a tiny core group, expandable around the globe in nanoseconds. They will be individually curated: you will build your own consumer-verse and interact only with what you choose, and advertisers will pay platforms for access to you. They will be behaviorally stimulating, mediated through sensors and the physical body. And these conditions will be controlled — to some degree created — by artificial or "other" intelligences.
Imagine: you interact only with content made for you, formatted exactly as you like it. No pulling or browsing — everything arrives ready-made. AI prompts dictate what and whom you engage. Your eyes, fingers, and skin become part of the interface, via wearables in continuous real time.
One caveat, and it's large: like Hong Kong, San Francisco, and Berlin, this sapeocentric society will have unaffordable elite enclaves. It will not be for everyone — only for those who can afford it. Everyone else will be monitored, or work for the system. Given present inequities, we need to sit with that reality now.
Before any superintelligence emerges, collective intelligence will scale through networks of people and systems. When intelligent systems intertwine holistically with our personal, social, cultural, political, and economic life, we will have achieved a collective human-machine intelligence.
First, we must confront "other kinds of minds" — and the confusion their arrival brings. The public must separate fact from fiction: robots are not necessarily AI, and AI is not necessarily robotic, nor does it need a body. The voice agent in your phone, your Spotify recommendations, your car's diagnostics — all AI.
Second, AI must become truly "invisible" and pass the Turing test. A system that can emote, lie, flirt, manipulate, charm, and deceive renders its artificiality imperceptible. Here is our greatest fear: that when a system's workings exceed human perception — when we know it exists and feel its effects but no longer comprehend what it does or how — we face something new. Not artificial intelligence, but an entirely new mode of intelligence.
The most esteemed scientists believe we're not remotely close — Nick Bostrom's Superintelligence is the sobering read. But machine learning is already becoming too involved for even its builders: as Pedro Domingos notes, the first machine learning algorithms of the 1950s already did things humans didn't fully comprehend. The pace has only accelerated.
The ethical dilemma: processing speeds, machine learning, and massive data aggregation may one day engineer a self-learning "sovereign" that predicts the future better than any human and evades our intellect entirely. If sophisticated AI can deliver correct insights through chains no human can follow, how do we control it — or make informed decisions without its help? Humanity's most valuable asset might become a system no human fully understands.
As AI's impact grows, more people must understand its workings: better-prepared researchers and engineers, diverse interdisciplinary teams, and a public less fearful of the technology. Just as media literacy is an essential civic skill today, comprehending intelligent systems will be essential tomorrow. The Internet of Things is the wireframe for that future — open, evolving, dissolving the border between physical and digital reality. Quite literally.
My final point is the least reassuring, and the most important. We are indeed close to the emergence of a novel intelligence. But we must never forget: we are the gatekeepers. We are closer not because of deep learning or any technical advance, but because — through our complacent abdication of basic rights, our ignorance of others' suffering, and our mutual acceptance of corruption and media control — we have already unconsciously agreed to be merged with, and eventually replaced by, that intelligence.
