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Just because people might choose to misinterpret the results of a test doesn't mean the test is invalid. People already do an acceptable job understanding the e

• R_haterade 9y ago
  You don't know many teenagers, do you? The potential for ostracism is just too great.
• pizza 9y ago
  If people thought about what they were doing at all times, both claims could be true but in the real world, both of those claims will almost surely be rejected. People don't choose to be certain, they are just unaware of their overconfidence. Overconfidence doesn't change the probabilities of the rare, harmful events that they are predicting won't happen. But their bias against self-doubt does increase their willingness to bet against unprecedented events.. n=1001 safe observations (where E[payoff] > 0) cannot predict that the next will be catastrophic (E[payoff] = -inf, or at least absolute value >> O(N*E[payoff seen up till then])) with non-zero probability beforehand; the expected payoff would appear vastly different before the event than after. The bets they choose will reflect the way they underestimate the consequences of speculation. Evidence of absence > absence of evidence, another way to put that is the weight of ¬valid(test) >> the weight of ¬¬valid(test), so we should not decide the test is invalid just because it's not yet invalidated. My gut feeling is that the upper-bound of proven benefit (to individuals/society) of the test (even if ~99.99% accurate) << upper-bound of the harm (intentionally or not) - because 'invalidity' isn't a question of whether a test is always non-satisfiable, the burden of proof falls upon the one introducing it, rather than the one rejecting it.