![]() ![]() In the 2012 workshop I attended, we learned to apply Bayes’ theorem - the formalized math for changing your mind based on new information about an uncertain situation - to our thinking and carefully mapped out the different, sometimes conflicting motivations and goals involved in major life decisions. CFAR, by contrast, hoped to provide concrete, immediately useful training. LessWrong was a space to discuss ways of mitigating and working around these very human flaws, but discussions there tended to be abstract. While intelligence is responsible for the astounding advances in technology, prosperity, and quality of human lives over the past several thousand years, it can also be applied to causing massive harm.Īs the Nobel Prize-winning economist and psychologist Daniel Kahneman argued in his influential 2011 book Thinking, Fast and Slow, human beings are prone to systematic errors: making assumptions or jumping to conclusions, seeing what we expect to see, and often leaning over-optimistic on plans and deadlines. She and the other founders of CFAR - who met via the rationality blog LessWrong (for which I’ve written) - believe that human intelligence alone isn’t enough to address the biggest problems facing the world. At the retreat, Galef advised a room full of philosophy students and programmers (and me, a random intensive care unit nurse) on how to think about probabilities and uncertainty in real-life contexts.Ī decade later, Galef continues to write about and advocate for a concept that is more important than ever in our irrational age: that we shouldn’t assume which conclusions must be defended, and need to stay open to uncertainty. I first met Julia Galef in 2012 at the inaugural weekend workshop of the Center for Applied Rationality (CFAR), a nonprofit that Galef co-founded that same year to teach the concepts and practical skills of human rationality.įor CFAR, this means refining techniques for reasoning more accurately, understanding the world, and making plans that work (and happen on schedule!).
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