  I'd like to thank Zhong for his last urlLink post on atheism. He writes: My main point is this: when it comes to decision-making, humans are inherently illogical. We make our decisions on a mixture of emotions, logic, and contradictory statements- in other words, our intuition or gut feeling. I have (so far) not argued whether this decision-making process is right or wrong, I have merely argued that this is how we make our decisions.
It seems to me that Zhong is offering up an extremely limited conception of rationality, one that's almost a caricature of itself. Leaving aside the issue of whether it's "rational" to pursue an extremely narrow version of self-interest and the fact that any rational person is going to care whether or not they get beaten up, it seems to me that the major problem with Zhong's example of Data-reasoning is that people don't generally explicitly quantify probabilities. That's what makes Data sound so silly. And for good reason. How did Zhong get the numbers Data uses? To get anything remotely like that kind of precision, he would need to perform a very complicated analysis of a vast quantity of data. Even leaving aside a score of other problems, like the fact that we wouldn't even know which calculations to perform if we had the time and capability, human beings don't have the memory capacity or computational power to analyze enough data to generate those kinds of probabilities.
Rationality is not free. Human beings aren't gods who can instantly draw out every logical implicationof everything they know. Thinking hard takes time, and that's time that's spent not doing the things that make life actually worth living, whether you think that's sex and drugs or prayer and worship. As limited beings, it is perfectly rational for us to make our day-to-day decisions on the basis of guesswork, intuition, and rules of thumb, because generally no other method is available to us, and even if it is, the benefits to doing so aren't very high compared to the costs. It's not worth adding up your monthly expenses down to the last penny when all you need is a rough estimate.
What I'm trying to say is that Zhong's version of rational decision-making is actually irrational : if you generally tried to make your decisions that way, you would be worse off by just about any standard of value. Nonetheless, there are circumstances where we do have the time and inclination to think things through carefully, or the logical conclusions are obvious, and sometimes getting the right answer is important enough that it's worth taking the time to do all the thinking the hard way.
It seems natural and obvious that time runs at the same rate at all locations, and most of the time that assumption is perfectly fine, even for very precise applications. But when you're making decisions about the algorithm the Global Positioning System should use, you can't throw out General Relativity just to make your life easier. Because time flows marginally faster up in space than it does down here and the GPS uses very small time quantities to make its calculations, the GPS wouldn't work if you tried to use the time-runs-at-the-same-rate-everywhere approximation of classical physics.
Something similar is true in the law. If you're loaning a friend $15 because he has no cash while you're in a restaurant, there's no point in carefully negotiating terms of repayment and writing them down in a contract, because you trust your friend to repay you at some point and even if you both forget about it you're only losing $15.
Going beyond that to negotiate terms that were to your maximal advantage would be even more foolish, because the time and energy it would take to do so (not to mention the expense of hiring the lawyers to write such a complicated contract) would be more time and expense than it's worth to either of you. When Giant Megacorp is getting a loan for $200 million from Giant Megabank, they need a hundred-page contract and a bunch of other documents, even though hiring the lawyers to negotiate all the details will probably cost another few million dollars. 
