I don’t think we can give you favorable feedback, because you haven’t claimed anything yet.
Truth is a terrible goal for epistemology. Nature gives us information, not access to truth. Many structuralist and post-modern critiques of meaning evaporate if you interpret the meaning of the sentence “The sky is blue” as refining the probability distribution describing the sky’s color, rather than as being problematic because “blue” isn’t clearly defined, or because the speaker hasn’t been outside in ten minutes. A sentence’s meaning is more like the odds ratio multipliers it provides for your priors than like a truth predication.
A sentence’s meaning is more like the odds ratio multipliers it provides for your priors than like a truth predication.
And what do you mean by this? That the old truth model is less correct than the probabilistic model, or that the probabilistic model performs better in applications? Or maybe you’re prone to say that the latter is more correct, but what you mean by that is that there’s more use for it. That’s the tension I am trying to bring out, those two different interpretations of epistemic claims. And my claim is that the second gets us farther than the first. For instance it permits us to use combinations of tools that most epistemologies would frown upon, like contradictory theories.
There’s a shift in perspective that has to happen in the course of this discussion, from evaluating the intuitive correctness and reality-correspondence (even probabilistically) of theories as sets of claims about the world to evaluating the potential uses and practical strength of theories as tools to accomplish our goals. I’m supporting my approach epistemology in the second more pragmatic way rather than the first way, which is more epistemic.
I don’t think we can give you favorable feedback, because you haven’t claimed anything yet.
Truth is a terrible goal for epistemology. Nature gives us information, not access to truth. Many structuralist and post-modern critiques of meaning evaporate if you interpret the meaning of the sentence “The sky is blue” as refining the probability distribution describing the sky’s color, rather than as being problematic because “blue” isn’t clearly defined, or because the speaker hasn’t been outside in ten minutes. A sentence’s meaning is more like the odds ratio multipliers it provides for your priors than like a truth predication.
And what do you mean by this? That the old truth model is less correct than the probabilistic model, or that the probabilistic model performs better in applications? Or maybe you’re prone to say that the latter is more correct, but what you mean by that is that there’s more use for it. That’s the tension I am trying to bring out, those two different interpretations of epistemic claims. And my claim is that the second gets us farther than the first. For instance it permits us to use combinations of tools that most epistemologies would frown upon, like contradictory theories.
There’s a shift in perspective that has to happen in the course of this discussion, from evaluating the intuitive correctness and reality-correspondence (even probabilistically) of theories as sets of claims about the world to evaluating the potential uses and practical strength of theories as tools to accomplish our goals. I’m supporting my approach epistemology in the second more pragmatic way rather than the first way, which is more epistemic.