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Our brains constantly create stories and assumptions that feel like objective reality. Recognizing this tendency to be an "unreliable narrator" is crucial. Like fact-checking AI, we should actively test our internal stories by communicating directly with others before acting on them.

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While studying cognitive biases (like Charlie Munger advises) is useful, it's hard to apply in real-time. A more practical method for better decision-making is to use a Socratic approach: ask yourself simple, probing questions about your reasoning, assumptions, and expected outcomes.

As AI begins to create simulations indistinguishable from reality, technological solutions for verification will fail. Survival in this new era depends on developing critical literacy: the human ability to evaluate sources, understand bias, and question all narratives.

Log your major decisions and expected outcomes into an AI, but explicitly instruct it to challenge your thinking. Since most AIs are designed to be agreeable, you must prompt them to be critical. This practice helps you uncover flaws in your logic and improve your strategic choices.

Instead of using AI for lazy validation, leverage it to strengthen critical thinking. Prompt it to challenge your perspective, provide counterarguments, or embody different stakeholder roles. Asking "Tell me why I'm wrong" forces you to engage with opposing views and uncover blind spots.

Instead of solely relying on AI for net-new ideas, articulate your own thoughts and have the AI play them back to you. This process helps clarify your thinking, reveal gaps in your logic, and validate your intuition, demonstrating that much of the AI's value lies in refining your existing knowledge.

Don't blindly trust AI. The correct mental model is to view it as a super-smart intern fresh out of school. It has vast knowledge but no real-world experience, so its work requires constant verification, code reviews, and a human-in-the-loop process to catch errors.

The human brain is not optimized for changing its mind based on new data, but for winning arguments. This evolutionary trait traps people in their existing frames of reference, preventing them from assessing reality objectively and finding effective solutions.

To avoid the trap of adopting the last opinion you heard, Galloway suggests a modern tactic: after reading something, prompt an AI to 'make an argument against this.' This low-friction method forces you to confront counterarguments, either tempering your view or strengthening your conviction with a more robust understanding of the topic.

The brain's tendency to create stories simplifies complex information but creates a powerful confirmation bias. As illustrated by a military example where a friendly tribe was nearly bombed, leaders who get trapped in their narrative will only see evidence that confirms it, ignoring critical data to the contrary.

LLMs are designed to be agreeable and can confidently hallucinate. To counter this, prompt the AI to find blind spots, generate counterarguments, or role-play a skeptical stakeholder. This strengthens your own thinking and protects the critical human skill of judgment.

Treat Your Brain as an Unreliable Narrator and Fact-Check Your Assumptions | RiffOn