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Big data, meager returns

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Presentation for the Workshop organized by Lorrayne Porciuncula and Yasodara Cordova at the Harvard Kennedy School in October, 2018

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Big data, meager returns

  1. 1. Big Data, meager returns? Fairness, Sustainability and Data for the Global South A collaborative Workshop 12 October 2018 - Event page
  2. 2. Why are we here?
  3. 3. Why are we here?
  4. 4. Why are we here?
  5. 5. Why are we here? Access????
  6. 6. Is this problem relevant?
  7. 7. Why take a perspective of the Global South (or of developed countries)? o The scale: - Geographic - Demographic o The stage of development - Economic - Institutional o The heterogeneity
  8. 8. Why talk about data in the Global South? o The natural next frontier for data collection due to its geographic and demographic scale o New public-private partnerships on IoT, Smart city & AI means new policy questions o Use of data can have positive externalities (marginal external benefits > marginal private benefits) which are not being harnessed for development - Data collection for private purposes vs gains from capacity building and training, or to improve public services - Data storage vs uses of data for artificial intelligence that could boost production and new business models
  9. 9. Why economic fairness and sustainability? New economic research points that poverty alleviation and sustainability are connected with economic development and social well-being. - As ethics, is there a place for a discussion on economic fairness and sustainability in AI? - If AI can boost innovation and productive gain for the digital transformation of countries, should we be thinking on how to make it economically inclusive and socially and environmentally responsible?
  10. 10. Which data? How have different infrastructures been monitored so far? Global Warming: growing need to manage resources based on scientific evidence. >> Who produces this data? Agriculture: drones, sensors* and satellites are being used to map rural areas and better manage future crops. >> Who has access to this information? *Precision sensors that are not dependable of human interaction (temperature, wind…)
  11. 11. How to govern data? What governance and regulatory models can inform us? - Data as oil? - Data as infrastructure? - Data as [insert here your better analogy or brand new idea]? Who has a claim and how to manage it? - Market-based model >> precification - Sovereign model >> sovereignty funds - Hybrid models >> regulation of market failures and PPPs
  12. 12. Objectives of this workshop - Map frameworks that could be applicable for data (governance) - Define the scope of the universe of data (typology) - Catalyse more questions! - Start a discussion towards policy proposals - Propose next steps

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