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Teaching AI in data journalism

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Presentation at ESJ Lille about teaching AI and machine learning to data journalists and journalism students

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Teaching AI in data journalism

  1. 1. Teaching #DDJ + #AI @PaulBradshaw Birmingham City University, BBC Data Unit
  2. 2. https://github.com/paulbradshaw/ Data journalism at Birmingham City ● DJ techniques + issues, from spreadsheets to HTML, JS, R, AI ● Narrative: newswriting, longform, social, video and audio, visual, VR ● Investigations: docs, scraping (Pyth), FOI, accounts, stats, OSINT, networks ● Critical issues, methodologies ● Law, ethics - and institutions ● Newsrooms - negotiating cultures!
  3. 3. Teaching DDJ+AI? 1. Holding data’s power to account 2. Reporting accurately with AI 3. Problems — and problem-solving https://github.com/paulbradshaw/
  4. 4. 1. Holding [data] to account
  5. 5. “We are moving from the knowledge/power nexus portrayed by Foucault to a data/action nexus that does not need to move through theory: All it needs is data together with preferred outcomes” Geoffrey Bowker, 2014 https://ijoc.org/index.php/ijoc/article/download/2190/1156
  6. 6. https://www.propublica.org/series/machine-bias
  7. 7. https://www.bloomberg.com/view/articles/2017-03-08/how-data-can-turn-immigrants-into-criminals
  8. 8. “[Algorithms] are not isolated deterministic actors but an inextricable component within a network of communicative practices that includes economic, institutional and increasingly legal and ethical issues” Matt Carlson
  9. 9. https://projects.propublica.org/graphics/hatecrime-map
  10. 10. http://museumofhomelessness.org/2019/03/12/dying-homeless-project/
  11. 11. https://twitter.com/guardian/status/1009433445032976389?s=09
  12. 12. Lowrey 2015; Reporters Lab 2016
  13. 13. 2. Reporting [stories] accurately
  14. 14. “When we teach computers to write, the computers don’t replace us any more than pianos replace pianists—in a certain way, they become our pens, and we become more than writers. We become writers of writers.” Ross Goodwin
  15. 15. https://onlinejournalismblog.com/2019/05/23/ai-in-journalism-guidelines-on-reporting-uncertainty/
  16. 16. Showing uncertainty Gauge; box and whisker plots; ranges; visualising uncertainty;
  17. 17. https://www.wired.com/story/polisis-ai-reads-privacy-policies-so-you-dont-have-to/
  18. 18. http://jonathanstray.com/extracting-campaign-finance-data-from-gnarly-pdfs-using-deep-learning
  19. 19. 3. Speaking the language of [power]
  20. 20. Kao, 2017
  21. 21. Julia Wolfe, WSJ, quoted in Cairo (2017) Nerd Journalism
  22. 22. Read more here
  23. 23. “We find journalists are “writing for machines” by converting unstructured information into structured data to enable automated recombination and future re-use of content. This impacts editorial control by delegating responsibility to either the algorithm or the audience, in the name of choice.” Jones and Jones 2019
  24. 24. https://onlinejournalismblog.com/2017/08/07/10-principles-for-data-journalism-in-its-second-decade/
  25. 25. Merci. @PaulBradshaw, Birmingham City University Online Journalism Blog, BBC England data unit

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