Post-statistics: Lies, damned lies and data science patents
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US Patent (Wikipedia) |
One of the most important characteristics of data science appears to be shared ideal with open source movement, i.e. free software. Note that “free” here means freedom of using the source code and sharing recipes, i.e. a workflows/combination of algorithms for example. The entire innovation in data science we are witnessing last 5 years or so fundamentally driven by this attitude that is embraced by giants like Microsoft, Google and IBM supporting a huge number of enthusiastic individuals from industry and academics. These technology giants open source their workflows and tools to the entire community like Tensorflow and supporting community via event or investing in research that partly goes into public. On the other hand, traditionally patents are designed to encourage innovation and invention culture. A kind of a gift and a natural right to innovator that given certain time frame he/she or organisation ripe some benefits.
A recent patent on predicting data science project outcome, unfortunately, do not entirely served to this purpose:
This patent US 9710767 B1 is a tremendous disservice to the entire data science community and damaging to an industry and professionals that are trying to use the data in outcome prediction for the greater good in society and solve problems. We definitely do not claim that data science is the solution to our problems in general but will help us to tackle important problems in industry and society. So maybe in the post-statistics world, we have to yell; lies, damned lies and data science patents. While holders of such patent may look like encouraging a patent shark or troll, rather than the intention of innovating or inventing.
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