Well, you can logically analyse whether an opinion is well-founded. For example: "I prefer Windows to Linux because I have more control over what I can do with it". You can't argue with "I prefer Windows", but you can argue that the reasoning behind this preference is flawed, and that the person's opinion (preference of Windows) is inconsistent with their stated values (control over software).
Of course, most people take great offense at being forced to think about their opinions. They want "Free Speech" to state their case, but Eris forbid that anyone might try to have a discussion about it!</sidetrack>
Do you find that pointing out inconsistency actually changes people's opinions much? Usually it just puts them on the defensive. It might be worth it for the benefit of third parties I suppose.
Actually changing people's opinions once they're formed and emotionally vested is really hard.
It works on rational people. These are unfortunately rare, and not trivial to identify before wasting effort on a discussion which can only lead to pointless flamewars.
It would help if the strength of someone's opinion was proportional to something meaningful, like supporting evidence, or how much they'd thought it through. Then "the defensive" might actually be a sound counter-argument. Bingo, useful discussion.
Can I at this point try arguing[1] that this is in fact underanalysis and not overanalysis? As in, to do it properly, you'd have to bring in fuzzy logic and Bayesian inference and lots and lots of qualifiers and biology and all of that good stuff. I mean, it's not as if there aren't notable correlations in matters of taste, preference and emotion.
There seem to be two distinct problems that both get lumped together as "overanalysis". One of these is where you have too little data, of too poor quality, to go on. Essentially I'm talking about statistical insignificance and other related things. This is truly and indisputably deserving of "overanalysis". The second is where the thing you're trying to understand is fearsomely complex, and something cobbled together with simple predicate logic and a few dodgy assumptions just won't do, especially if you've got something in your brain, provided by biology, which can do a much better job "on instinct". This is what I semi-jokingly suggested might be called "underanalysis", but "misanalysis" or better still "malanalysis"[2] may be better.
[1] Translation: This may itself be overanalysis. [2] Now try getting such a horrible-sounding word to catch on...
Gosh, I like the classification of overanalysis types (maybe I am a taxonomist for a reason). What about a situation that is fairly simple and suitable for analysis, but instead of accepting their conclusions and acting on them the person runs the analysis again and again with different input factors, until results are skewed and confused?
Wow, this whole thread seems to be made of over-analysis. o_O
Presumably, given all the above, if I say I prefer Windows because I can do all the stuff I want to more easily than Linux, and the only 'fuzzy logic' I know about is the cute fuzzy T-shirt on ThinkGeek, will all the geeks jump on me now?
Er, guys, are you trying to defend geekery or ramp up the stereotypes? I'm so confused.
<mock-offended>Sides? Me? I'm too busy being a geek here to have a side!</mock-offended> More seriously, I sometimes like to see if I can redefine the sides in a discussion in the hope that it might provide a way forward without anyone having to lose face. That, and the fact that I just like analysing things...
If I had to pick a side; well, I'd say there's more to be gained from engaging in excessive analysis and then being sceptical about the results of said analysis, than in being overcautious about how much analysis you do at all. Consider how science is meant to work (Awooga! Gross oversimplification incoming!): you do some analysis, come up with an idea, but you only accept it when you find that the experiments agree with your analysis.
As for your second sentence; well, you've got the core of a good point there, but I think you might need a bit more work on how you present it.
(Potted summary of fuzzy logic, BTW:
Long, skippable version: you know how you can do all of that boolean stuff where 1 is true and 0 is false? Fuzzy logic extends that so you can have 0.6 or 0.001. Some mathematicians have been able to prove that some sorts of fuzzy logic have all sorts of desirable properties in common with normal logic, but the jury's still out on whether it's possible to do anything useful with it that you couldn't do better with normal logic and some probability, and it's entirely unclear what relation (if any) it has to what the brain does or what sentences mean.
Short version: it's one of those things for dealing with uncertainty and in particular ambiguity that AI types like to argue about.)
I'm not sure I entirely agree with this. You can use logic on matters of emotion (I do quite frequently). In fact, I said to someone that it was entirely logical that they were feeling something they thought was illogical ;)
However, I feel that there is a significant difference between applying analysis to these categories and insisting that anyone else should do so, or that anyone else should accept your analysis as being inevitably superior.
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Of course, most people take great offense at being forced to think about their opinions. They want "Free Speech" to state their case, but Eris forbid that anyone might try to have a discussion about it!
</sidetrack>Actually changing people's opinions once they're formed and emotionally vested is really hard.
It would help if the strength of someone's opinion was proportional to something meaningful, like supporting evidence, or how much they'd thought it through. Then "the defensive" might actually be a sound counter-argument. Bingo, useful discussion.
There seem to be two distinct problems that both get lumped together as "overanalysis". One of these is where you have too little data, of too poor quality, to go on. Essentially I'm talking about statistical insignificance and other related things. This is truly and indisputably deserving of "overanalysis". The second is where the thing you're trying to understand is fearsomely complex, and something cobbled together with simple predicate logic and a few dodgy assumptions just won't do, especially if you've got something in your brain, provided by biology, which can do a much better job "on instinct". This is what I semi-jokingly suggested might be called "underanalysis", but "misanalysis" or better still "malanalysis"[2] may be better.
[1] Translation: This may itself be overanalysis.
[2] Now try getting such a horrible-sounding word to catch on...
Presumably, given all the above, if I say I prefer Windows because I can do all the stuff I want to more easily than Linux, and the only 'fuzzy logic' I know about is the cute fuzzy T-shirt on ThinkGeek, will all the geeks jump on me now?
Er, guys, are you trying to defend geekery or ramp up the stereotypes? I'm so confused.
<mock-offended>Sides? Me? I'm too busy being a geek here to have a side!</mock-offended> More seriously, I sometimes like to see if I can redefine the sides in a discussion in the hope that it might provide a way forward without anyone having to lose face. That, and the fact that I just like analysing things...
If I had to pick a side; well, I'd say there's more to be gained from engaging in excessive analysis and then being sceptical about the results of said analysis, than in being overcautious about how much analysis you do at all. Consider how science is meant to work (Awooga! Gross oversimplification incoming!): you do some analysis, come up with an idea, but you only accept it when you find that the experiments agree with your analysis.
As for your second sentence; well, you've got the core of a good point there, but I think you might need a bit more work on how you present it.
(Potted summary of fuzzy logic, BTW:
Long, skippable version: you know how you can do all of that boolean stuff where 1 is true and 0 is false? Fuzzy logic extends that so you can have 0.6 or 0.001. Some mathematicians have been able to prove that some sorts of fuzzy logic have all sorts of desirable properties in common with normal logic, but the jury's still out on whether it's possible to do anything useful with it that you couldn't do better with normal logic and some probability, and it's entirely unclear what relation (if any) it has to what the brain does or what sentences mean.
Short version: it's one of those things for dealing with uncertainty and in particular ambiguity that AI types like to argue about.)
However, I feel that there is a significant difference between applying analysis to these categories and insisting that anyone else should do so, or that anyone else should accept your analysis as being inevitably superior.