Three ways CFAR has changed my view of rationality
The Center for Applied Rationality’s perspective on rationality is quite similar to Less Wrong’s. In particular, we share many of Less Wrong’s differences from what’s sometimes called “traditional” rationality, such as Less Wrong’s inclusion of Bayesian probability theory and the science on heuristics and biases.
But after spending the last year and a half with CFAR as we’ve developed, tested, and attempted to teach hundreds of different versions of rationality techniques, I’ve noticed that my picture of what rationality looks like has shifted somewhat from what I perceive to be the most common picture of rationality on Less Wrong. Here are three ways I think CFAR has come to see the landscape of rationality differently than Less Wrong typically does – not disagreements per se, but differences in focus or approach. (Disclaimer: I’m not speaking for the rest of CFAR here; these are my own impressions.)
1. We think less in terms of epistemic versus instrumental rationality.
Formally, the methods of normative epistemic versus instrumental rationality are distinct: Bayesian inference and expected utility maximization. But methods like “use Bayes’ Theorem” or “maximize expected utility” are usually too abstract and high-level to be helpful for a human being trying to take manageable steps towards improving her rationality. And when you zoom in from that high-level description of rationality down to the more concrete level of “What five-second mental habits should I be training?” the distinction between epistemic and instrumental rationality becomes less helpful.
Here’s an analogy: epistemic rationality is like physics, where the goal is to figure out what’s true about the world, and instrumental rationality is like engineering, where the goal is to accomplish something you want as efficiently and effectively as possible. You need physics to do engineering; or I suppose you could say that doing engineering is doing physics, but with a practical goal. However, there’s plenty of physics that’s done for its own sake, and doesn’t have obvious practical applications, at least not yet. (String theory, for example.) Similarly, you need a fair amount of epistemic rationality in order to be instrumentally rational, though there are parts of epistemic rationality that many of us practice for their own sake, and not as a means to an end. (For example, I appreciate clarifying my thinking about free will even though I don’t expect it to change any of my behavior.)
In this analogy, many skills we focus on at CFAR are akin to essential math, like linear algebra or differential equations, which compose the fabric of both physics and engineering. It would be foolish to expect someone who wasn’t comfortable with math to successfully calculate a planet’s trajectory or design a bridge. And it would be similarly foolish to expect you to successfully update like a Bayesian or maximize your utility if you lacked certain underlying skills. Like, for instance: Noticing your emotional reactions, and being able to shift them if it would be useful. Doing thought experiments. Noticing and overcoming learned helplessness. Visualizing in concrete detail. Preventing yourself from flinching away from a thought. Rewarding yourself for mental habits you want to reinforce.
These and other building blocks of rationality are essential both for reaching truer beliefs, and for getting what you value; they don’t fall cleanly into either an “epistemic” or an “instrumental” category. Which is why, when I consider what pieces of rationality CFAR should be developing, I’ve been thinking less in terms of “How can we be more epistemically rational?” or “How can we be more instrumentally rational?” and instead using queries like, “How can we be more metacognitive?”
2. We think more in terms of a modular mind.
The human mind isn’t one coordinated, unified agent, but rather a collection of different processes that often aren’t working in sync, or even aware of what each other is up to. Less Wrong certainly knows this; see, for example, discussions of anticipations versus professions, aliefs, and metawanting. But in general we gloss over that fact, because it’s so much simpler and more natural to talk about “what I believe” or “what I want,” even if technically there is no single “I” doing the believing or wanting. And for many purposes that kind of approximation is fine.
But a rationality-for-humans usually can’t rely on that shorthand. Any attempt to change what “I” believe, or optimize for what “I” want, forces a confrontation of the fact that there are multiple, contradictory things that could reasonably be called “beliefs,” or “wants,” coexisting in the same mind. So a large part of applied rationality turns out to be about noticing those contradictions and trying to achieve coherence, in some fashion, before you can even begin to update on evidence or plan an action.
Many of the techniques we’re developing at CFAR fall roughly into the template of coordinating between your two systems of cognition: implicit-reasoning System 1 and explicit-reasoning System 2. For example, knowing when each system is more likely to be reliable. Or knowing how to get System 2 to convince System 1 of something (“We’re not going to die if we go talk to that stranger”). Or knowing what kinds of questions System 2 should ask of System 1 to find out why it’s uneasy about the conclusion at which System 2 has arrived.
This is all, of course, with the disclaimer that the anthropomorphizing of the systems of cognition, and imagining them talking to each other, is merely a useful metaphor. Even the classification of human cognition into Systems 1 and 2 is probably not strictly true, but it’s true enough to be useful. And other metaphors prove useful as well – for example, some difficulties with what feels like akrasia become more tractable when you model your future selves as different entities, as we do in the current version of our “Delegating to yourself” class.
3. We’re more focused on emotions.
There’s relatively little discussion of emotions on Less Wrong, but they occupy a central place in CFAR’s curriculum and organizational culture.
It used to frustrate me when people would say something that revealed they held a Straw Vulcan-esque belief that “rationalist = emotionless robot”. But now when I encounter that misconception, it just makes me want to smile, because I’m thinking to myself: “If you had any idea how much time we spend at CFAR talking about our feelings…”
Being able to put yourself into particular emotional states seems to make a lot of pieces of rationality easier. For example, for most of us, it’s instrumentally rational to explore a wider set of possible actions – different ways of studying, holding conversations, trying to be happy, and so on – beyond whatever our defaults happen to be. And for most of us, inertia and aversions get in the way of that exploration. But getting yourself into “playful” mode (one of the hypothesized primary emotional circuits common across mammals) can make it easier to branch out into a wider swath of Possible-Action Space. Similarly, being able to call up a feeling of curiosity or of “seeking” (another candidate for a primary emotional circuit) can help you conquer motivated cognition and learned blankness.
And simply being able to notice your emotional state is rarer and more valuable than most people realize. For example, if you’re in fight-or-flight mode, you’re going to feel more compelled to reject arguments that feel like a challenge to your identity. Being attuned to the signs of sympathetic nervous system activation – that you’re tensing up, or that your heart rate is increasing – means you get cues to double-check your reasoning, or to coax yourself into another emotional state.
We also use emotions as sources of data. You can learn to tap into feelings of surprise or confusion to get a sense of how probable you implicitly expect some event to be. Or practice simulating hypotheticals (“What if I knew that my novel would never sell well?”) and observing your resultant emotions, to get a clearer picture of your utility function.
And emotions-as-data can be a valuable check on your System 2′s conclusions. One of our standard classes is “Goal Factoring,” which entails finding some alternate set of actions through which you can purchase the goods you want more cheaply. So you might reason, “I’m doing martial arts for the exercise and self-defense benefits… but I could purchase both of those things for less time investment by jogging to work and carrying Mace.” If you listened to your emotional reaction to that proposal, however, you might notice you still feel sad about giving up martial arts even if you were getting the same amount of exercise and self-defense benefits somehow else.
Which probably means you’ve got other reasons for doing martial arts that you haven’t yet explicitly acknowledged—for example, maybe you just think it’s cool. If so, that’s important, and deserves a place in your decisionmaking. Listening for those emotional cues that your explicit reasoning has missed something is a crucial step, and to the extent that aspiring rationalists sometimes forget it, I suppose that’s a Steel-Manned Straw Vulcan (Steel Vulcan?) that actually is worth worrying about.
I’ll name one more trait that unites, rather than divides, CFAR and Less Wrong. We both diverge from “traditional” rationality in that we’re concerned with determining which general methods systematically perform well, rather than defending some set of methods as “rational” on a priori criteria alone. So CFAR’s picture of what rationality looks like, and how to become more rational, will and should change over the coming years as we learn more about the effects of our rationality training efforts.