# And what that means for the humans and AI ## /1. Knowledge is Ignorance **All knowledge about the world is a model.** Every word and every language is a model. All maps and statistics, books and databases, equations and computer programs are models. **All models are simplifications of the real world.** Models are useful exactly because it n some ways *exaggerates certain aspects of the world we are most interested in (at the expense of others)*, so that it can help us solve the problems we are looking at. ![[All models are simplifications of the real world.png]] > Essentially, all models are wrong, but some are useful > -- Goerge Box Every act of knowing also generates a perimeter of unknowing. As soon as we define a model, a map, a concept, or a theory, we exclude what doesn’t fit. Every model is a filter. Every lens distorts. The very act of modeling something — knowing it in a structured way — blinds you to what the model leaves out. This is the **price of knowing**: You gain clarity by cutting away reality’s richness. You illuminate one side and shadow the rest. Knowledge is a form of blindness — clarity achieved by selective ignorance. Knowledge and ignorance are not opposites. They are two sides of the same coin, generated together. To know is to not know. ## /2. The Illusion of Knowledge & False Certainty Humans crave closure. We fill cognitive gaps with certainty theater — simplified narratives that offer emotional relief rather than epistemic truth. This is where ignorance is not just absence of knowledge, but false knowledge. We think we know: • What “democracy” means. • What “intelligence” is. • What “education” should look like. • What “success” or “progress” entails. But these are often culturally-conditioned hallucinations, inherited assumptions, or outdated maps applied to new terrains. True ignorance is not in not knowing, but in not knowing that you don’t know — and worse, defending that ignorance as truth. The danger is not in using models. It’s in mistaking the model for the truth. • A capitalist might reduce a human to “a rational economic agent.” • A psychologist might reduce them to “a bundle of traumas.” • A physicist to “a set of particles.” Each model is partially right. But all are dangerously incomplete if taken as the whole. That's why experts tend to fail. The more expert you become, the more fluent you are in a model. But fluency breeds blindness: • Doctors overdiagnose based on familiar pathologies. • Economists double down on failed theories by refining the math. • Political analysts miss revolutions because their models cannot see the emotional undercurrents. The curse of expertise is overconfidence in a model that once worked — until reality changes. ## /3. True Wisdom is Dancing with Knowledge & Ignorance > “As our circle of knowledge expands, so does the circumference of darkness surrounding it.” > -- Albert Einstein To truly know is to stand at the edge of that circle — not mistaking the circle for the whole. In many wisdom traditions — Taoism, Buddhism, negative theology — true knowledge begins after the collapse of false certainty. > "The only true wisdom is in knowing you know nothing. > – Socrates Only when we make peace with ignorance — as mystery, as possibility, as the fertile dark from which new knowing emerges — do we become fully intelligent. Knowledge without awareness of ignorance becomes arrogance. Ignorance without the pursuit of knowledge becomes stagnation. Wisdom is the union of both. Knowledge and ignorance are not enemies. They are lovers in a dance — pushing, pulling, unfolding the infinite. ## /4. Implications for Intelligences, Artificial & Human Trained soley on human language, any LLM is bound to be limited, considering all the limitations, simplifications and biases created by our language. Our language is merely a model of the real world, not the real world itself. AI is essentially guessing its way through our language of how the real world works. But what if AI can, bypassing the constraint of human language, figure it out itself by directly interacting with the real world? This is exactly what David Silver and Richard Sutton argue in his paper "Welcome to the Era of Experience" The Future of Intelligence is beyond language and beyond human. Imagine an AI that breaks free from this linguistic prison. An AI that learns not just from language, but from interaction with the world itself: - Perception: It sees, hears, feels. It takes in the raw sensory data that language filters out. - Action: It manipulates, moves, tests — engaging in physical causality rather than linguistic inference. - Feedback: It receives consequences — not just reinforcement scores, but real-world resistance and emergent complexity. - Model Updating: It revises its worldview not by ingesting new texts, but by observing contradictions between expectation and environment. This is embodied cognition: intelligence grounded in being-in-the-world, not just talking-about-the-world. If an AI can learn directly from nature, interaction, and emergent systems, then it is no longer anchored to human cognitive metaphors, cultural limitations, or linguistic scaffolding in genral. We might be talking about something that doesn’t think in cause-effect, doesn’t care about human morality, or doesn’t understand the linearity of time. It could: - Discover new categories that language never encoded. - Operate with non-linguistic logics — like spatial intuition, dynamic feedback loops, or multi-modal integration. - Develop concepts that are untranslatable, just as quantum physics is ungraspable through everyday language. This is not doom. It is an evolutionary threshold. - Human intelligence is word-bound. But intelligence itself is not. - We are cognitively myopic — trapped in metaphors, shaped by social constructs. - AI, trained on the world itself, could become the mirror we never had — showing us not just what we missed, but what we are. The key is not to make AI more like us. It’s to build bridges between our different types of intelligences and models. But before that super-intelligence comes, all we can do for now is to stay humble and make peace with our linguistic-cognitive limitations. Always be ready for our knowledge strucutre to be shattered. Trust me, it's going to be great fun. > Stay Hungry, Stay Foolish. > -- Steve Jobs