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Pitch

Cognitive surplus of millions of undergrads worldwide is squandered as they research uncoordinatedly. MIT alumni can encourage coordination.


Description

Summary

Linux has shown many years ago how groups of people with basic-to-good skills could be organized to create world changing intellectual capital. Mechanical Turk and other crowdsourcing engines show how to parse tasks to make them executable by relatively unskilled workers. More generally, global teams' coordination is much easier thanks to low cost communications. Today, advanced data science technology enables the parsing of extremely complex data and its serving in a coordinated workflow to people with basic understanding of analytics and with rudiments of the respective domain expertise. 

 

 


What actions do you propose?

From material science to astrophysics to life sciences to behavioral economics, worldwide undergrads' brainpower could be better coordinated by creating a marketplace for micro-projects stemming from a common thread of advanced research, parsed up through e.g. data science tools (from IBM to unicorn Hortonworks to many startups in that space) so that they can be executed in an fragmented yet coordinated manner globally.

Supervised machine learning is one special application of this mechanism, but other scenarios such as data structuring and remediation/transformation, quality control etc are possible. Basic primary research or preparation of the information corpus enabling meta-analysis is also a possibility. 

The benefit for individual students and their faculty is that they (a) will be able to demonstrate the advancement of big science projects and (b) teach data science foundation to all sorts of students who will benefit from the basic understanding of those techniques. 

MIT alumni are uniquely positioned to help at multiple levels

1) By influencing the adoption of such marketplace in the universities and other educational institutions close to them, by promoting the model to local government, as well as by involving marketing and advertising agencies who could promote the concept to the students and their faculty.. 

2) By finding funding and other resources for the buildup of the technical infrastructure of the marketplace - from the portal itself to foundational pieces of data science that enable the structuring of the data for the experiments

3) By creating templates and building blocks that enable the usage of such "crowdsourced ecosystem" for the myriad leading-edge research projects worldwide. And by coalescing groups of students with the capability to help researchers worldwide in structuring their research to harness the power of this model.