on relationship between science and predictions, i think you might enjoy freeman dyson's musings on the topic. loosely quoting (~4:40) "what scientists do is to arrange things in an experiment to be as unpredictable as possible, and then do the experiment... you might say that if something is predictable, then it's not science". in some ways i feel this hints at weighing the "context of discovery" (aka coming up with the hypothesis) just as much as that of the justification.
on fake data, how does one think about 'noise' in the way of stochastic processes or such, where the real data is hard to measure with existing equipment? side note, i wonder what Meehl (and you) would think about the increasing use of 'synthetic datasets' ubiquitous in the current paradigm of internet scale datasets?
on relationship between science and predictions, i think you might enjoy freeman dyson's musings on the topic. loosely quoting (~4:40) "what scientists do is to arrange things in an experiment to be as unpredictable as possible, and then do the experiment... you might say that if something is predictable, then it's not science". in some ways i feel this hints at weighing the "context of discovery" (aka coming up with the hypothesis) just as much as that of the justification.
https://www.youtube.com/watch?v=8xFLjUt2leM
on fake data, how does one think about 'noise' in the way of stochastic processes or such, where the real data is hard to measure with existing equipment? side note, i wonder what Meehl (and you) would think about the increasing use of 'synthetic datasets' ubiquitous in the current paradigm of internet scale datasets?