Lumifer comments on Open thread, Oct. 12 - Oct. 18, 2015 - Less Wrong Discussion
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I'm contemplating a discussion post on this topic, but first I'll float it here, since there's a high chance that I'm just being really stupid.
I'm abysmally unsuccessful at using anything like Bayesian reasoning in real life.
I don't think it's because I'm doing anything fundamentally wrong. Maybe what I'm doing wrong is attempting to think of these things in a Bayesian way in the first place.
Let's use a concrete example. I bought a house. My prior probability that any given household appliance or fixture will break and/or need maintenance in a given month is on the order of 5%, obviously with some variability depending on what appliance we're talking about. This prior is an off-the-cuff intuitive figure based on decades of living in houses.
Within a month of buying this house, things immediately start breaking. The dishwasher breaks. Then the garbage disposal. The sump pump fails completely. The humidifier needs repair. The air conditioner unit needs to be entirely replaced. The siding needs to be repainted. A section of fence needs to be replaced. The sprinklers don't work. This is all within roughly the first four months.
So, my prior was garbage, but the real issue for me is that Bayesian reasoning didn't really help me. The dishwasher breaking didn't cause me to shift my Background Probabilistic Breakage Rate much at all. One thing breaking within the first month is allowed for by my prior model. Then the second thing breaks - okay, maybe I need to adjust my BPBR a a bit. Still, there's little reason to expect that several more important things will break in short order. But that's exactly what happened.
There is a causal story that explains everything (apparently) breaking at basically the same time, which is that the previous owners were not taking good care of the house, and various things were already subtly broken and limping along at passable functionality for a long time. The problem is that this causal story only becomes promoted to "hypothesis with significant probability mass" after two or three consecutive major appliance disasters.
What is annoying about all this is that my wife doesn't attempt to use any kind of probabilistic reasoning, and she is basically right all the time. I was saying things like, "I really doubt the garbage disposal is really broken, we just had two other major things replaced, what are the odds that another thing would break so quickly?" and she would reply along the lines of, "I'm pretty sure it's actually broken, and I can't fathom why you keep talking about odds when your odds-based assessments are always wrong," and I'm at the point of agreeing with her. Not to mention that she was the one who suggested the "prior owners didn't maintain the house" hypothesis, while I was still grimly clinging to my initial model, increasingly bewildered by each new disaster.
I am probably a poster child for "doing probabilistic thinking wrong" in some obvious way that I am blind to. Please help me figure out how and where. I have my own thoughts, but I will wait for others to respond so as to avoid anchoring.
You have two hypotheses: the appliances breaking are not connected (independent); and the appliance breaking are connected (dependent).
In the first case you are saying the equivalent of "I tossed the coin twice and it came up heads both times, it's really unlikely it will come up heads the third time as well" which should be obviously wrong.
In the second case you should discard your model of independence alongside with your original prior and consider that the breakages are connected.
I think the moral of the story is that life is complicated and simple models are often too simple to be useful. You should discard them faster when they show signs of not working.
And, of course, if you are wondering whether your garbage disposal is really broken, you should go look at your garbage disposal unit and not engage in pondering theoretical considerations.
See my response to ChristianKl below for my clarification on my reasoning about "consecutive coin flips" which could still be wrong but is hopefully less wrong than my original wording.
I agree that I should have discarded my model more quickly, but I don't quite see how to generalize that observation. Sometimes the alternative hypothesis (e.g. the breakages are connected) is not apparent or obvious without more data - and the process of collecting data really just means continuing to make bad predictions as you go through life until something clicks and you notice the underlying structure.
My wife seems to think that making explicit model-based predictions in the first place is the problem. I have a lot of respect for System 1 and am sympathetic to this view. But System 2 really shouldn't actively lead me astray.
Yes, and note that this part -- "that I have to start considering that the die is loaded" -- is key.
Um, directly? All models which you are considering are much simpler than the real world. The relevant maxim is "All models are wrong, but some are useful".
I think you got caught in the trap of "but I can't change my prior because priors are not supposed to be changed". That's not exactly true. You can and (given sufficient evidence) should be willing to discard your entire model and the prior with it. Priors only make sense within a specified set of hypotheses. If your set of hypotheses changes, the old prior goes out of the window.
The naive Bayes approach sweeps a lot of complexity under the rug (e.g. hypotheses selection) which will bite you in the ass given the slightest opportunity.
Yeah, well, welcome to the real world :-/
She is correct if your models are wrong. Getting right models is hard and you should not assume that the first model you came up with is going to be sufficiently correct to be useful.
I see absolutely no basis for this belief. To misquote someone from memory: "Logic is just a way of making errors with confidence" :-P