True scientific progress comes from being proven wrong. When an experiment falsifies a prediction, it definitively rules out a potential model of reality, thereby advancing knowledge. This mindset encourages researchers to embrace incorrect hypotheses as learning opportunities rather than failures, getting them closer to understanding the world.

Fields like economics become ineffective when they prioritize conforming to disciplinary norms—like mathematical modeling—over solving complex, real-world problems. This professionalization creates monocultures where researchers focus on what is publishable within their field's narrow framework, rather than collaborating across disciplines to generate useful knowledge for issues like prison reform.

The concept of shaping reality is universal, just packaged differently. A psychologist calls it self-image psychology, a scientist quantum physics, an atheist the placebo effect, and a Christian prayer. Understanding this allows skeptics to access the benefits of mindset work using a framework they trust.

The strength of scientific progress comes from 'individual humility'—the constant process of questioning assumptions and actively searching for errors. This embrace of being wrong, or doubting one's own work, is not a weakness but a superpower that leads to breakthroughs.

Modern science almost exclusively investigates the 'efficient cause' (the agent that brought something about). It largely ignores the other three causes defined by Aristotle: the material cause (what it's made of), the formal cause (its form or shape), and the final cause (its purpose or 'telos'), thus providing an incomplete picture.

Philosophy should have been central to AI's creation, but its academic siloing led to inaction. Instead of engaging with technology and building, philosophers remained focused on isolated cogitation. AI emerged from engineers who asked "what can I make?" rather than just asking "what is a mind?".

Moving from science to investing requires a critical mindset shift. Science seeks objective, repeatable truths, while investing involves making judgments about an unknowable future. Successful investors must use quantitative models as guides for judgment, not as sources of definitive answers.

We operate with two belief modes. For our immediate lives, we demand factual truth. For abstract domains like mythology or ideology, we prioritize morally uplifting or dramatically compelling narratives over facts. The Enlightenment was a push to apply the first mode to everything.

Current LLMs fail at science because they lack the ability to iterate. True scientific inquiry is a loop: form a hypothesis, conduct an experiment, analyze the result (even if incorrect), and refine. AI needs this same iterative capability with the real world to make genuine discoveries.