In open source, anyone can access the facts of the code. No other has ever achieved consensus at scale without recourse to coercion. It’s a messy process but it works, the only one in all of human history that ever has. Members of the community pay more attention to those who have been right in the past, and to those who enhance their reputation for integrity by admitting in public when they are wrong. They must explain clearly and listen to those who response with equal clarity. There is a straightforward process for finding a true answer to any question. Membership in an open source community is like membership in the community of science. Jupyter exemplifies the social systems that emerged from the Scientific Revolution and the Enlightenment, systems that make it possible for people to cooperate by committing to objective truth Mathematica exemplifies the horde of new Vandals whose pursuit of private gain threatens a far greater pubic loss–the collapse of social systems that took centuries to build. Jupyter encourages individual integrity Mathematica lets individuals hide behind corporate evasion. Jupyter rewards transparency Mathematica rationalizes secrecy. Moreover, at a time when trust and truth are in retreat, the social dimension is the one that matters. It is along this social dimension that open source unambiguously dominates the proprietary model. Does it increase trust? Does it increase the importance that people attach to a reputation for integrity? There is an independent social dimension, where the metrics assess the interactions between people. This technical engineering dimension is not the only one we should use to compare the proprietary and open models.
PAUL ROMER PYTHON JUPYTER NOTEBOOK SOFTWARE
Still, Mathematica’s early lead offers some support for the claim that from the perspective of software engineering, the proprietary model may sometimes have its advantages. (Pay no attention to the preposterous suggestion that it is still the technological leader.) There are, of course, many offsetting examples of visionaries who succeeded by mobilizing an open-source community.
To their credit, Mathematica did open up a huge technical lead in the 1990s. The Mathematica developers claim that the hierarchy afforded by the proprietary model is a better way to organize innovation. The obvious contrast is between the proprietary world of Wolfram and the open-source model of the software ecosystem that Jupyter mobilizes. The article asks why Jupyter succeed where Mathematica failed. I’m experimenting with, and excited about, its potential as a way to write up research results. Now, I’m much more productive with Jupyter. I had to learn the hard way why so many kept their distance from Mathematica.
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