This example actually proves the opposite. Bitcoin was described in a white paper that wasn’t very impressive by academic crypto standards—few if anyone became interested in Bitcoin from first reading the paper in the early days. It’s success was proven by experimentation, not pure theoretical investigation.
By experimentation, do you mean people running randomized controlled trials on Bitcoin or otherwise empirically testing hypotheses on the software? Just because your approach is collaborative and incremental doesn’t mean that it’s empirical.
By experimentation, do you mean people running randomized controlled trials on Bitcoin or otherwise empirically testing hypotheses on the software?
Not really—by experimentation I meant proving a concept by implementing it and then observing whether the implementation works or not, as contrasted to the pure math/theory approach where you attempt to prove something abstractly on paper.
For context, I was responding to your statement:
But first, this isn’t obviously true… mathematicians, for instance, have found theoretical approaches to be more powerful. (I’d guess that the developer of Bitcoin took a theoretical rather than an empirical approach to creating a secure cryptocurrency, for instance.)
Bitcoin is an example of typical technological development, which is driven largely by experimentation/engineering rather than math/theory. Theory is important mainly as a means to generate ideas for experimentation.
By experimentation, do you mean people running randomized controlled trials on Bitcoin or otherwise empirically testing hypotheses on the software? Just because your approach is collaborative and incremental doesn’t mean that it’s empirical.
Not really—by experimentation I meant proving a concept by implementing it and then observing whether the implementation works or not, as contrasted to the pure math/theory approach where you attempt to prove something abstractly on paper.
For context, I was responding to your statement:
Bitcoin is an example of typical technological development, which is driven largely by experimentation/engineering rather than math/theory. Theory is important mainly as a means to generate ideas for experimentation.