# Rationality slides

Here is a presentation (in spanish) on rationality for skepticamp I’ve worked on recently. It needs some polish but the content is essentially complete. A summary of the main points

• Optimization and the second law of thermodynamics are opposing forces
• Intelligence is a type of optimization that evolved in certain species to counteract the 2nd law through behavior. Intelligence functions through observation, learning and prediction
• Prediction requires a correct representation of the environment, this defines epistemic rationality as a component of intelligence
• Classical logic fails to model rationality as it cannot deal with uncertainty
• Probability theory is an extension of logic to domains with uncertainty
• Probability theory and Bayes define a standard of ideal rationality. Other methods are suboptimal approximations
• Probability theory as formalization of rationality:
• Provides a quantitative model of the scientific method as a special case of Bayes theorem
• Provides operational, quantitative definitions of belief and evidence
• Naturally relates predictive power and falsifiability through the sum rule of probability
• Explains pathological beliefs of the vacuous kind; astrology, card reading, divination, etc
• Explains pathological beliefs of the floating kind; “There is a dragon in my garage”
• Dissolves false disagreements described by matching predictions but different verbal formulations
• Naturally embeds empiricism, positivism and falsificationism
• Pathological beliefs can be analyzed empirically by re-casting them as physical phenomena in brains, the province of cognitive science.
• A naturalistic perspective automatically explains human deviations from rationality; evolution will always favor adaptations that increase fitness even if they penalize rationality
• Today, politics is an example of rationality catastrophe; in the ancestral environment, irrationality that favored survival in a social context (tribes) was a successful adaptation. (Wright, Yudkowsky)
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Various papers

Bayesian probability – Bruyninckx(2002)
Philosophy and the practice of Bayesian statistics – Gelman(2011)
Varieties of Bayesianism – Weisberg
No Free Lunch versus Occam’s Razor in Supervised Learning – Lattimore, Hutter(2011)
A Material Theory of Induction – Norton(2002)
Bayesian epistemology – Hartmann, Sprenger(2010)
The Illusion of Ambiguity: from Bistable Perception to Anthropomorphism – Ghedini(2011)
Bayesian Rationality and Decision Making: A Critical Review – Albert(2003)
Why Bayesian Rationality Is Empty, Perfect Rationality Doesn’t Exist, Ecological Rationality Is Too Simple, and Critical Rationality Does the Job* – Albert(2009)
A Better Bayesian Convergence Theorem – Hawthorne