Thread by @JMateosGarcia

Today we launch Innovation Mapping Now, a report about our @nesta_uk work using new data sources, analytics and visualisations to inform innovation policy.
Summary thread ensues [1/7]
nesta.org.uk/report/innovat…

We start with the policy problem: a disconnect between technological innovation and growth/sustainability/wellbeing. Traditional innovation policy instruments don't seem enough to address it. A new wave of activist, directional & holistic policies emerge as an alternative [2/7]

These new policies need a new evidence base that is more detailed, inclusive and timely. Traditional data sources (business survey) and indicators (national statistics and counts) fall short of its needs [3/7]

New data sources, analytical methods (text mining, machine learning, network science. interactive visualisations) could help. Innovation mapping exploits these opportunities to inform innovation policy.
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Exhibits with opportunities based on our work...
1. Monitor emerging technologies like AI
2. Map innovation systems and identify gaps and opportunities for collaboration
3. Identify mission fields and analyse their composition.
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But new data isn't without problems: there are biases, quality and ethical issues and problems with interpretability. Predictive models could entrench economic inequality instead of helping reduce it. We try to address them with an approach that is...[6/7]

Today we are getting together with @OECDinnovation and @EUScienceInnov in London to explore how to bring it new data to the innovation policy mainstream, making it smarter, more inclusive and open.
Follow the discussion at #ND4IP
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