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Part one is about how science works even when the public thinks it doesn't. Part two will certainly ruffle some feathers by offering a reason- and science-based perspective on issues where political correctness has gone awry. Part three provides some data-driven advice for your health and well-being. Part four looks at human behavior and how we can better navigate our social worlds. In part five we put on our skeptical goggles and critically examine a few commonly-held beliefs. In the final section, we look at a few ways how we all can make the world a better place.
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This appears to be a improper use of induction. Induction is great for making predictions but only probabilistically. For example, we can say that all past end of the world predictions have failed, so it is extremely likely (not with certainty—at least not based on the past examples) that a particular/current one will also fail (say 1,000,000 failed past predictions, and this is just one more, so 1/1million). However, to claim that all future predictions will fail (i.e., "never" come true) the mathematical equation has shifted from 1,000,000 past predictions in the last 5000+ years to one prediction, to 1,000,000 to perhaps a billion more in the next 100,000 years. This is unreasonable and an unwarranted conclusion. In the context of the argument, the conclusion does not follow - non sequitur . |
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answered on Wednesday, Sep 08, 2021 05:28:39 AM by Bo Bennett, PhD | ||||
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There's another implied (and I suggest false) premise that needs to be inserted into the "more formal" version of the argument. That premise is that the accuracy of a current prediction is related directly to the accuracy of previous predictions. It's related to the gambler’s fallacy . It seems to me that the accuracy of a current prediction is more strongly based on the data and logical processes on which the current prediction is based ... not on the track record of previous predictions. Assuming that predictions can be related because of their accuracy is a non sequitur in that the conclusion doesn't follow from the premises. The best I get out of this argument is that basing future predictions on the same sort of data that were used for earlier predictions that didn't work out so well is likely to result in a new prediction that doesn't work out well, either. It's instructive, but not in terms of whether to believe predictions; it's instructive (perhaps) in terms of the sort of data one needs to make good predictions. |
answered on Wednesday, Sep 08, 2021 11:28:29 AM by Arlo | |
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