People are predictably irrational, right? We have a poor intuitive understanding of statistics, we leap to drawing cause and effect relationships where none exist, we don’t understand exponential growth very well, and we gorge ourselves on junk food and junk television. We’re broken! While there are all kinds of quirks to our built-in reasoning hardware, some of those quirks might not be as irrational as they seem. Jason Collins has a PhD in economics and evolutionary biology, and he’s long been writing about they ways in which our "cognitive biases" may - in some cases - actually be adaptive decision-making strategies. In this episode, we dig into some of Jason’s recent posts on ergodicity, and how that may inform the "loss averse" ways that humans make decisions. While this episode does get pretty technical, anyone who is interested should take a look at Jason’s blog posts on the topic.

[Note: In this episode I talk about logarithmic functions as asymptotic functions. This is incorrect, and I apologize in advance to anyone who I may offend with such foolishness.]

Check out more from Jason here: Website: www.jasoncollins.blog Twitter: @jasonacollins

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Show Notes: [01:50] What is “cognitive bias?” What kinds of systematic judgment errors do humans make – and why do some people think that these errors are actually adaptive heuristics? [06:50] What are the ethics of “nudges”? What are the actual effect sizes of “nudges”? How do the actual results of interventions in things like organ donation and retirement account opt-ins actually play out? [12:40] What heuristics should someone use to evaluate whether a social science claim is worth paying attention too? Is the effect size too large? Why would humans have evolved a certain type of “bias”? And, what is the piranha problem and what is the garden of forking paths? [22:53] How context dependent are social psychology effects? What do we typically see in attempts to replicate studies? [28:53] What actually is “loss aversion”? How do we differentiate loss aversion from risk aversion and negativity bias? [36:07] “Loss aversion” may actually be a rational response to certain types of systems where people have a risk of having their wealth wiped out. [43:01] What is the variance across individuals in terms of psychological effects and different strategies relative to risk taking? [46:32] What is “ergodicity”? What are real-life examples of ergodic and non-ergodic systems? [58:14] What is the optimal strategy for trying to maximize your wealth in a non-ergodic system where gains and losses are potentially compounded? [01:05:20] Would we expect people to have evolved some sort of intuitive understanding of non-ergodic systems based upon the real-life dynamics of things like wealth and prestige? [01:16:16] How can the rules of an experimental game impact the ways that people strategize? Do people have an intuitive sense that they are likely to be iteratively playing the same game over and over again with the same people? Links and Resources Mentioned “Nudge” by Richard Thaler and Cass Sunstein Freakonomics NPR Dan Ariely “‘Opt Out’ Policies Increase Organ Donation” from SPARQ “Comparison of organ donation and transplantation rates between opt-out and opt-in systems” from Kidney International Default effect “Judges are more lenient after taking a break, study finds” from The Guardian “Impossibly Hungry Judges” from Nautilus “Overlooked factors in the analysis of parole decisions” from PNAS “Automaticity of social behavior: Direct effects of trait construct and stereotype activation on action.” PsycNET “Priming Effects Replicate Just Fine, Thanks” from Statistical Modeling, Causal Inference, and Social Science “Walking Fast and Slow” from Marginal Revolution Andrew Gelman “The piranha problem in social psychology / behavioral economics” from Andrew Gelman “The garden of forking paths” from Andrew Gelman “The WEIRDest people in the world?” from Behavioral and Brain Sciences Loss aversion Risk aversion Negativity bias St. Petersburg paradox Kelly criterion Gerd Gigerenzer “Gigerenzer versus Kahneman and Tversky” from Jason Collins

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