Comment by xpe
3 years ago
> But the hard cold reality is that you cannot “own” an idea.
The above comment is true about the properties of information, as explained via the lens of economics. [1]
However, one ignores ownership as defined by various systems (including the rule of law and social conventions) at one's own peril. Such systems can also present a "hard cold reality" that can bankrupt or ostracize you.
[1] Don't let the apparent confidence and technicality of the language of economists fool you. Economics isn't the only game in town. There are other ways to model and frame the world.
[2] Dangling footnote warning. I think it is instructive to recognize that the field of economics has historically shown a kind of inferiority complex w.r.t. physics. Some economists ascribe to the level of rigor found in physics and that is well and good, but perhaps that effort should not be taken too seriously nor too far, since economics as a field operates at a different level. IMO, it would be wise for more in the field to eat a slice of humble pie.
[3] Ibid. It is well-known that economists can be "hired guns" used to "prove" a wide variety of things, many of which are subjective. My point: you can hire an economist to shore up one's political proposals. Is the same true of physicists? Hopefully not to the same degree. Perhaps there are some cases of hucksterism, but nothing like the history of economists-wagging-the-dog! At some point, the electron tunnels or it does not.
There are other games in town.
But whatever game gives the most predictive power is going to win.
By that metric, various economic schools have been hilariously inept and would get classified not dissimilar to various schools of religious theology with their own dogmas. It's only in the last 15 years or so that some focus on empiricism and explaining reality rather than building theoretical castles in the air is coming about and is still far from mainstream.
There is no need to frame this as "winning versus losing" regarding the many models that we draw upon.
Even when talking about various kinds of scientific and engineering fields, predictive power isn't the only criteria, much less the best. Sometimes the simpler, less accurate models work well enough with less informational and computational cost.
Even if we focus on prediction (as opposed to say statistical inference), often people want some kind of hybrid. Perhaps a blend of satisficing with limited information, scoped action spaces, and bounded computation; i.e. good enough given the information we have to make the decisions we can actuate with some computational budget.