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Science lessons

Can policy makers learn anything from the way in which some elements of the scientific community now approach collaboration?

Can policy makers learn anything from the way in which some elements of the scientific community now approach collaboration?

When Galileo first turned his telescope on Saturn he sent his scientific rivals information on his new discovery in the form of an anagram.  That was the dissemination norm in the seventeenth century – it enabled the discoverer to lay claim to the new finding – without letting rivals in too soon.  Scientists were deeply hostile to the notion of publication.

The change – from “black box alchemy” to science as we know it came as a result of two scientific revolutions that century – a revolution on how to make discoveries; and a revolution on how to share them. The problem with science is that it is still too stuck in the seventeenth century sharing paradigm based on papers – and excluding the potential for sharing inter alia ideas, data, questions.  While journals represented long-term collective memory, new technology offered the capacity to create a collective short-term working memory – but that capacity was being only poorly exploited. This is the subject of a forthcoming book on “Rediscovering Discovery” by quantum computing pioneer Michael Nielsen (www.michaelnielsen.org) and who gave a talk at the Royal Society this week as part of their project on Science as a Public Enterprise.  He gave fantastic examples of success – the “polymath project”, the solution of a mathematical problem posted on his blog by leading Cambridge mathematician Timothy Gowers which – after a slow start – generated 800 contributions; (http://stackoverflow.com/) which solves programming problems; the amazingly named “github” (https://github.com/) which allows users to upload open source software and tracks activity – so people can see who is doing what and how.  But for all the successes there were also failures – for example, creating dedicated wikis as online super textbooks which died for lack of contributions.  And a big reason behind the failure was the lack of incentives to contribute – as Michael put it “a short mediocre published paper” counts for reputation (and thus funding) – a major input into a collaborative online forum does not. Black box policy So what can policy makers learn?  Some thoughts:

  • Too much policy making has not yet moved beyond the “black box alchemy”.  There is too little attempt to show the workings behind policy making.
  • Where policy making has been opened up (eg on the Red Tape Challenge) the focus has been on opening up the input not in developing the solutions; but it is in the hammering out solutions that real innovation can come.  Yet this is when government goes offline.
  • But it is also potentially interesting to open up the questions as well.  Is government addressing the right issues and getting to the core of what matters?
  • Technology alone is not enough – people need incentives (particularly if it takes an effort).  Within government, our incentive systems under-reward helping others to solve their or problems rather than pursuit of their own objectives.

Solving the research conundrum There was agreement at the session that different research system is needed to drive collaboration and opening up data.   To the scientists in the room, this was a problem for governments to solve. But the collaborative model that solved Timothy Gowers’s mathematical problem might also be able to solve the funding puzzle.  If scientists could come together and come up with a way of allocating research money which met government objectives, but also promoted better scientific research methods, why would a government say no?  An opportunity for proof of concept? As long as they don’t send the answer as an anagram.

Keywords
Technology
Publisher
Institute for Government

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