▲ | JumpCrisscross 8 days ago | ||||||||||||||||
> guess hope can be false now "Hope is false if it is based on ignorance of the correct assessment of the probability that a desire is fulfilled or on ignorance with regard to the desirability of the object of desire. Hope is justified—realistic—when the hoping person knows and accepts experts’ judgement about the probability of hope fulfillment. However, I argued, what matters for evaluating a person’s hope is not only whether it is realistic, but also whether it is reasonable in light of the aim and goals for which the person strives in (the remainder of) his life ...a person’s hope that an (experimental) treatment may prolong his or her life or improve the quality of his or her life can only be called false when he or she thinks that the chances of personal benefits are greater than those estimated by experts. If he or she does accept their judgement, continuing to hope is realistic. Hope is moreover reasonable if it contributes to realizing what a person strives for in (the remainder of) his life" [1]. | |||||||||||||||||
▲ | mllev 8 days ago | parent | next [-] | ||||||||||||||||
I agree that the probability of a desired outcome is valuable information. But to call being unaware of this information “false hope” is a blight on our language. Hope is hope. It’s quite proven that believing a certain outcome is likely increases the likelihood of that outcome. | |||||||||||||||||
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▲ | hnfong 8 days ago | parent | prev [-] | ||||||||||||||||
Hope is premised on the basis that nobody knows the future 100%. Experts can give a mostly-frequentist analysis based on past medical cases. The unknown part is whether those cases apply to yours. And nobody knows. All the so-called probability is meaningless. It matters not whether your chances of remission is "99%" or "1%". Those numbers are meaningless in a specific case under a specific situation. I understand this is not the commonly understood notion of probability, but the common notion is simply wrong. I'm not saying experts are wrong, I'm happy to assume that their analyses are quite correct when applied to a population. I'm just saying the common way of interpreting their statistics onto one specific case (the one you care about) is wrong, because you can't just plug the probability onto a single person/case and round it off to zero or one. |