Part of the sequence: Rationality and Philosophy
Hitherto the people attracted to philosophy have been mostly those who loved the big generalizations, which were all wrong, so that few people with exact minds have taken up the subject.
Bertrand Russell
I've complained before that philosophy is a diseased discipline which spends far too much of its time debating definitions, ignoring relevant scientific results, and endlessly re-interpreting old dead guys who didn't know the slightest bit of 20th century science. Is that still the case?
You bet. There's some good philosophy out there, but much of it is bad enough to make CMU philosopher Clark Glymour suggest that on tight university budgets, philosophy departments could be defunded unless their work is useful to (cited by) scientists and engineers — just as his own work on causal Bayes nets is now widely used in artificial intelligence and other fields.
How did philosophy get this way? Russell's hypothesis is not too shabby. Check the syllabi of the undergraduate "intro to philosophy" classes at the world's top 5 U.S. philosophy departments — NYU, Rutgers, Princeton, Michigan Ann Arbor, and Harvard — and you'll find that they spend a lot of time with (1) old dead guys who were wrong about almost everything because they knew nothing of modern logic, probability theory, or science, and with (2) 20th century philosophers who were way too enamored with cogsci-ignorant armchair philosophy. (I say more about the reasons for philosophy's degenerate state here.)
As the CEO of a philosophy/math/compsci research institute, I think many philosophical problems are important. But the field of philosophy doesn't seem to be very good at answering them. What can we do?
Why, come up with better philosophical methods, of course!
Scientific methods have improved over time, and so can philosophical methods. Here is the first of my recommendations...
More Pearl and Kahneman, less Plato and Kant
Philosophical training should begin with the latest and greatest formal methods ("Pearl" for the probabilistic graphical models made famous in Pearl 1988), and the latest and greatest science ("Kahneman" for the science of human reasoning reviewed in Kahneman 2011). Beginning with Plato and Kant (and company), as most universities do today, both (1) filters for inexact thinkers, as Russell suggested, and (2) teaches people to have too much respect for failed philosophical methods that are out of touch with 20th century breakthroughs in math and science.
So, I recommend we teach young philosophy students:
more Bayesian rationality, heuristics and biases, & debiasing, | less | informal "critical thinking skills"; |
more mathematical logic & theory of computation, | less | term logic; |
more probability theory & Bayesian scientific method, | less | pre-1980 philosophy of science; |
more psychology of concepts & machine learning, | less | conceptual analysis; |
more formal epistemology & computational epistemology, | less | pre-1980 epistemology; |
more physics & cosmology, | less | pre-1980 metaphysics; |
more psychology of choice, | less | philosophy of free will; |
more moral psychology, decision theory, and game theory, | less | intuitionist moral philosophy; |
more cognitive psychology & cognitive neuroscience, | less | pre-1980 philosophy of mind; |
more linguistics & psycholinguistics, | less | pre-1980 philosophy of language; |
more neuroaesthetics, | less | aesthetics; |
more causal models & psychology of causal perception, | less | pre-1980 theories of causation. |
(In other words: train philosophy students like they do at CMU, but even "more so.")
So, my own "intro to philosophy" mega-course might be guided by the following core readings:
- Stanovich, Rationality and the Reflective Mind (2010)
- Hinman, Fundamentals of Mathematical Logic (2005)
- Russell & Norvig, Artificial Intelligence: A Modern Approach (3rd edition, 2009) — contains chapters which briefly introduce probability theory, probabilistic graphical models, computational decision theory and game theory, knowledge representation, machine learning, computational epistemology, and other useful subjects
- Sipser, Introduction to the Theory of Computation (3rd edition, 2012) — relevant to lots of philosophical problems, as discussed in Aaronson (2011)
- Howson & Urbach, Scientific Reasoning: The Bayesian Approach (3rd edition, 2005)
- Holyoak & Morrison (eds.), The Oxford Handbook of Thinking and Reasoning (2012) — contains chapters which briefly introduce the psychology of knowledge representation, concepts, categories, causal learning, explanation, argument, decision making, judgment heuristics, moral judgment, behavioral game theory, problem solving, creativity, and other useful subjects
- Dolan & Sharot (eds.), Neuroscience of Preference and Choice (2011)
- Krane, Modern Physics (3rd edition, 2012) — includes a brief introduction to cosmology
(There are many prerequisites to these, of course. I think philosophy should be a Highly Advanced subject of study that requires lots of prior training in maths and the sciences, like string theory but hopefully more productive.)
Once students are equipped with some of the latest math and science, then let them tackle The Big Questions. I bet they'd get farther than those raised on Plato and Kant instead.
You might also let them read 20th century analytic philosophy at that point — hopefully their training will have inoculated them from picking up bad thinking habits.
Previous post: Philosophy Needs to Trust Your Rationality Even Though It Shouldn't
Our de facto reasoing is wrong. Either it is not leading to wrong predictions, or it is not easy to see something is wrong.
In any case, the world is not the only standard rationality can be compared to. We can spot the incoherence of bad rationality by theoretical investigation.
And yet a paperclipper has perfectly coherent preferences. Without direct access to some source-of-morality that somehow supersedes mere human ethics, how can we judge our morality except by it's own standards? If you have such a source, it would make an excellent top-level post, of perhaps even a sequence.