I've read a bunch of times on LessWrong about how important is to test things.  It makes sure your beliefs are paying rent and helps you verify your hypotheses.  Testing ideas is obviously important to science, and it's about as obvious that testing ideas in everyday life can serve the same purpose.  I know all this, and I want to be the type of person that goes out and verifies my beliefs by experiment, but still I can't think of a single time I've done it.  I don't think I even recall thinking, about some everyday type of thing, "hmm how could test that?" (apart from trivial trial-error computer related things).  Anyway, I was wondering if some of the you could give me some examples of times you've done this.  I'm thinking maybe I'll be able to pattern-match the kind of things you guys have done and hopefully recognize in the moment when I'm looking at a testable thought.



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Vaniver's example points at a large family of cases where this is useful - you're surprised or confused about something that is happening, and want to find out why it happens, either to fix it, or make it happen more.

Another case is when you're trying to find ways to do something, or find ways to improve some measure. If you can make repeated trials of that thing, you can narrow and improve your techniques. In general, you can often remedy uncertainty about how to execute some task by trying something, and then varying it, and seeing how well it goes.

Example: I'm often ineffective in the morning. I've noticed that this seems to coincide with the morning being overcast, so I've set up a bedside lamp on a timer. Right now, I've got it set to turn on 30 minutes before I wake up, and I plan on trying this for about a week. If it doesn't wake me up immediately, I'll also try setting it for about an hour before I wake, or 15 minutes, and see in which of these conditions I'm more energetic in the morning.

Thanks this was really helpful. I think this will help me recognize such situations in the future.

The situation that calls for testing feels like being confused or curious.

The thought that generates a test looks like this: "If X is true, it is (more/less) likely that Y is true. I can examine Y by doing ___."

For example, one day my computer was running slowly. There were a bunch of possible explanations, but my room was hot, dusty, and it'd been a long time since I cleaned it out, so I suspected the slowness was because of overheating. "If my computer is slow because of overheating, it is less likely that it will be slow if I remove the case to increase ventilation. I can examine that by removing the case." I pull the case off, and the computer runs normally again.

Most of the examples tend to be banal, though, and so I've forgotten them. (Not quite sure how I remembered that one.)

Ideally you should also point a room fan at the inside of the computer after you take off a panel. Some systems, especially small form factor PCs and rack mount servers, actually need the case in order to be properly cooled. Removing a panel means that e.g. an exhaust fan no longer forces air across passively cooled components near the intake.

Right, thanks. I probably need to work on noticing when I'm confused. Your example reminded me of a few cases where I've behaved similarly (everyone I expect has), so I guess I do some "testing" occasionally.

In coding, I very often test such hypotheses as "The crash is in this piece of code" by not executing that code and seeing if I still get a crash. Then execute the first half of the code, then the first half of that, and so on.

Trivial personal example: I hypothesise she is attracted to me, I will test my conclusion by asking her.

Trivial personal example: I hypothesise she is attracted to me, I will test my conclusion by asking her.

Preferably after corrupting your experiment by engaging in attractive behaviors and flirting. Science can wait!

Its getting a statistically significant control thats the real issue... But the double blind was quite fun.

Here's a quick, everyday one: whenever you come across a sentence that starts with "research says" or "studies show", Google to check whether these studies actually exist, before changing your degree of belief in the claim.

For a more general idea: try changing things.

If you like cooking, try changing your recipes one step at a time to see which ingredients or steps (generally not mentioned in written recipes) actually make a difference. For instance, when making pizza mixing the yeast with the flour makes the dough rise better than pouring the water directly over it, and leaving out the salt makes a huge difference in taste. (Sometimes these experiments happen by accident.)

Change your driving style (from aggressive to smooth or vice-versa) to check for an effect on mpg.

Try deliberately changing your posture in social settings, looking for postural echo. Try smiling more or making more eye contact, see if that changes any outcomes relevant to you. (This seems to count for a fair bit in public speaking.)

Take a different route to work tomorrow, see if your current routine really is optimized for travel time or whatever else you value.

Ask your boss for a raise. Ask someone for something you haven't dared ask for previously. (For instance, ask for a discount the next time you shop anywhere.)

I's hard to use precisely since normally we test a lot of things - things we simply don't know about yet. That's not quite what you're thinking of. And if you think of an example where you tested something you were reasonably confident of, then you just think of it as 'making sure'.

Confronting your unspoken assumptions can't be a day-to-day occurrence unless you started with an astonishingly large number of them or keep generating more of them, or keep being unsatisfied by confirming results.

Do you cook? If you've never tried something new in the kitchen, you should.

It is common in day-to-day conversation to say something along the lines of, "I don't think that's likely to happen," or, "That's probably not true." I've adopted the habit of verbally attaching probabilities each time this happens. ("He probably won't be late" -> "There's maybe a 10% chance he'll be late." This way it's really obvious when I'm wrong about something, and I get a measure of how wrong I was. If you don't view your expectations as predictions to be tested, you miss the opportunity to learn.