Radicalization, expertise, and skepticism among doctors & engineers: the value of philosophy in education
November 22, 2015 3 Comments
This past Friday was a busy day for a lot of the folks in Integrated Mathematical Oncology here at the Moffitt Cancer Center. Everybody was rushing around to put the final touches on a multi-million dollar research center grant application to submit to the National Cancer Institute. Although the time was not busy for me, I still stopped by Jacob Scott’s office towards the end of the day to celebrate. Let me set the scene for you: it is a corner office down the hall from me; its many windows are scribbled over with graphs, equations, and biological interaction networks; two giant screens crowd a standing desk, and another screen is hidden in the corner; the only non-glass wall has scribbles in pencil for the carpenters: paint blackboard here. There are too many chairs — Jake is a connector, so his office is always open to guests.
In addition to the scientific and administrative stress of grant-writing, Jake was also covering for his friend as the doc-of-the-day for radiation oncology. So as I rambled on: “If we consider nodes of degree three or higher in this model, we would break up contingent blocks of mutants and result in the domain of our probability distribution going from to “, scribbling more math on his wall, we would get interrupted by phone calls. His resident calling to tell him that the neurosurgeons have scheduled a consultation for an acute myeloid leukemia patient who is recovering from surgery earlier that day.
“Only on a Friday afternoon do you get this kind of consult!” Jake fires off, “He’s still in surgery! We can’t do anything for at least a few days – schedule him for Monday.”
The call was on speakerphone, but I could not keep up with the conversation. After years of training and experience, this was an effortless context-shift for Jake. He went from the heavy skepticism of a scientist staring at a blackboard to the certainty of a doctor that needed to get shit done, and back, in moments. I couldn’t imagine having this sort of confidence in my judgements, mostly because I have no training in medicine, but also because I am not expected to be certain. That is why I lean towards using abductive models versus insilications for clinial research; I have more confidence in machine learning than in my own physical and biological intuitions about cancer. Even if that approach might produce less understanding.
In recent weeks, I’ve noticed a theme in some of the (news and blog) articles I’ve been reading. In this post, I wanted to provide an annotated collection of some of these links, along with my reflections on what they say about the tension between expertise and skepticism and how that can radicalize us, both in mundane ways and in drastic ones. And what role philosophy can play in helping us cope. I will end up touching on recent events and politics as a source context, but hopefully we can keep the overall conversation more or less detached from current events.
Read more of this post
Rationality, the Bayesian mind and their limits
September 7, 2019 by Artem Kaznatcheev 1 Comment
Bayesianism is one of the more popular frameworks in cognitive science. Alongside other similar probalistic models of cognition, it is highly encouraged in the cognitive sciences (Chater, Tenenbaum, & Yuille, 2006). To summarize Bayesianism far too succinctly: it views the human mind as full of beliefs that we view as true with some subjective probability. We then act on these beliefs to maximize expected return (or maybe just satisfice) and update the beliefs according to Bayes’ law. For a better overview, I would recommend the foundations work of Tom Griffiths (in particular, see Griffiths & Yuille, 2008; Perfors et al., 2011).
This use of Bayes’ law has lead to a widespread association of Bayesianism with rationality, especially across the internet in places like LessWrong — Kat Soja has written a good overview of Bayesianism there. I’ve already written a number of posts about the dangers of fetishizing rationality and some approaches to addressing them; including bounded rationality, Baldwin effect, and interface theory. I some of these, I’ve touched on Bayesianism. I’ve also written about how to design Baysian agents for simulations in cognitive science and evolutionary game theory, and even connected it to quasi-magical thinking and Hofstadter’s superrationality for Kaznatcheev, Montrey & Shultz (2010; see also Masel, 2007).
But I haven’t written about Bayesianism itself.
In this post, I want to focus on some of the challenges faced by Bayesianism and the associated view of rationality. And maybe point to some approach to resolving them. This is based in part of three old questions from the Cognitive Sciences StackExhange: What are some of the drawbacks to probabilistic models of cognition?; What tasks does Bayesian decision-making model poorly?; and What are popular rationalist responses to Tversky & Shafir?
Read more of this post
Filed under Commentary, Preliminary, Reviews Tagged with bayesian, cognitive science, learning, prisoner's dilemma, rationality