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A Patent Application for NEXTGEN Flood Early Warning System

Published:13 July 2021Publication History
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Abstract

This design fiction re-imagines an important informational element of the flood early warning system in order to unpack some of the questionable assumptions that society makes about disaster. In presenting an updated, ironic, vision of an alternative system, we highlight some of the ways that received ideas about the root causes of disaster, who is responsible for public safety, and the role of private sector innovation, are so embedded in the design of technologies used in crisis management that they have become taken for granted. This work demonstrates the potential for design fiction to serve as a tool in the evaluation and critique of safety-critical information systems and as a communication tool for conveying the complex findings of disaster research. It also points to new avenues of exploration for crisis informatics work on public warning systems.

References

  1. P Agre. 1997. Toward a critical technical practice: Lessons learned in trying to reform AI. Lawrence Erlbaum Associates, Inc, Mahwah, NJ, USA, Chapter 6, 131--158.Google ScholarGoogle Scholar
  2. Madeleine Akrich. 1992. The De-scription of Technological Objects. Shaping Technology Building Society: Studjes in Sociotechnical Change (1992), 205--224.Google ScholarGoogle Scholar
  3. Jamal Al Qundus, Kosai Dabbour, Shivam Gupta, Régis Meissonier, and Adrian Paschke. 2020. Wireless sensor network for AI-based flood disaster detection. Annals of Operations Research (2020), 1--23.Google ScholarGoogle Scholar
  4. Ruha Benjamin. 2019. Race after technology: Abolitionist tools for the new jim code. Social Forces 98 (2019), 1--3. Issue 4.Google ScholarGoogle ScholarCross RefCross Ref
  5. Jenna Burrell. 2016. How the machine 'thinks': Understanding opacity in machine learning algorithms. Big Data & Society 3, 1 (2016), 2053951715622512.Google ScholarGoogle ScholarCross RefCross Ref
  6. Stephen Cave and Kanta Dihal. 2020. The Whiteness of AI. Philosophy & Technology 33:3 (2020), 1--19.Google ScholarGoogle ScholarCross RefCross Ref
  7. Ksenia Chmutina and Jason Von Meding. 2019. A Dilemma of language: "Natural disasters" in academic literature. International Journal of Disaster Risk Science 10, 3 (2019), 283--292.Google ScholarGoogle ScholarCross RefCross Ref
  8. Dharma Dailey, Robert Soden, and Nicolas LaLone. 2018. Crisis Informatics for Everyday Analysts: A Design Fiction Approach to Social Media Best Practices. In Proceedings of the 2018 ACM Conference on Supporting Groupwork. ACM, Sanibel Island, Florida, USA, 230--243. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Dharma Dailey and Kate Starbird. 2016. Addressing the information needs of crisis-affected communities: The interplay of legacy media and social media in a rural disaster. In The Communication Crisis in America, And How to Fix It. Palgrave Macmillan, London, United Kingdom, 285--303.Google ScholarGoogle Scholar
  10. Dharma Dailey and Kate Starbird. 2016. Beyond Official: Government Information Work through Personal Accounts. In Proceedings of the 19th ACM Conference on Computer Supported Cooperative Work and Social Computing Companion. ACM, New York, NY, USA, 249--252. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. RM de la Cruz, NT Olfindo Jr, MM Felicen, NJB Borlongan, JKL Difuntorum, and JJS Marciano Jr. 2020. Near-Realtime Flood Detection from Multi-Temporal Sentinel Radar Images Using Artificial Intelligence. The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences 43 (2020), 1663--1670.Google ScholarGoogle Scholar
  12. Anthony Dunne and Fiona Raby. 2013. Speculative everything: design, fiction, and social dreaming. MIT press, Cambridge, MA, USA. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. Sheri Fink. 2019. This High-Tech Solution to Disaster Response May Be Too Good to Be True. New York Times. Retrieved August 12, 2020 from https://www.nytimes.com/2019/08/09/us/emergency-response-disaster-technology.htmlGoogle ScholarGoogle Scholar
  14. D Fisher, K Hagon, C Lattimer, S O'Callaghan, S Swithern, and L Walmsley. 2018. World Disasters Report 2018: Leaving No One Behind. Technical Report. International Federation of Red Cross and Red Crescent Societies.Google ScholarGoogle Scholar
  15. John Patrick Flanagan. 2001. Early warning system for natural and manmade disasters. US Patent 6,169,476.Google ScholarGoogle Scholar
  16. United Nations Office for Disaster Risk Reductions. 2015. Sendai Framework for Disaster Risk Reduction 2015--2030. https://www.undrr.org/implementing-sendai-framework/what-sendai-frameworkGoogle ScholarGoogle Scholar
  17. Centre for Research on the Epidemiology of Disasters. 2009. EM-DAT: The International Disaster Database. Centre for Research on the Epidemiology of Disasters. https://www.emdat.be/Google ScholarGoogle Scholar
  18. Kim Fortun, Scott Gabriel Knowles, Vivian Choi, Paul Jobin, Miwao Matsumoto, Pedro de la Torre, Max Liboiron, and Luis Felipe Rosado Murillo. 2016. Researching Disaster from an STS Perspective. MIT Press, Cambridge, MA, USA, Chapter 34, 1003 -- 1028.Google ScholarGoogle Scholar
  19. Mary L Gray and Siddharth Suri. 2019. Ghost work: how to stop Silicon Valley from building a new global underclass. Houghton Mifflin Harcourt, New York, NY, USA.Google ScholarGoogle Scholar
  20. Chester W Hartman, Gregory Squires, Gregory D Squires, et al. 2006. There is no such thing as a natural disaster: Race, class, and Hurricane Katrina. Taylor & Francis, Oxfordshire, United Kingdom.Google ScholarGoogle Scholar
  21. Therese Huston. 2009. Teaching what you don't know. Harvard University Press, Cambridge, MA, USA.Google ScholarGoogle Scholar
  22. Ilan Kelman. 2020. Disaster by Choice: How our actions turn natural hazards into catastrophes. Oxford University Press, Oxford, United Kingdom.Google ScholarGoogle Scholar
  23. Z.W. Kundzewicz. 1996. Floods: lessons about early warning systems. Late lessons from early warnings. Science, Precaution, Innovation (1996).Google ScholarGoogle Scholar
  24. National Oceanic & Atmospheric Administration National Severe Storms Laboratory. 2020. Severe Weather 101--Floods. National Oceanic & Atmospheric Administration. https://www.nssl.noaa.gov/education/svrwx101/floods/Google ScholarGoogle Scholar
  25. Nicolas LaLone, Sultan A. Alharthi, and Z O Toups. 2019. A Vision of Augmented Reality for Urban Search and Rescue. In Proceedings of the Halfway to the Future Symposium 2019. ACM, Nottingham, UK, 1--4. Google ScholarGoogle ScholarDigital LibraryDigital Library
  26. Nicolas LaLone, Andrea Tapia, Christopher Zobel, Cornelia Caraega, Venkata Kishore Neppalli, and Shane Halse. 2017. Embracing human noise as resilience indicator: twitter as power grid correlate. Sustainable and Resilient Infrastructure 2, 4 (2017), 169--178.Google ScholarGoogle ScholarCross RefCross Ref
  27. M Girons Lopez, Giuliano Di Baldassarre, and Jan Seibert. 2017. Impact of social preparedness on flood early warning systems. Water Resources Research 53, 1 (2017), 522--534.Google ScholarGoogle ScholarCross RefCross Ref
  28. M Lynne Markus. 1983. Power, politics, and MIS implementation. Commun. ACM 26, 6 (1983), 430--444. Google ScholarGoogle ScholarDigital LibraryDigital Library
  29. Mike Monteiro. 2019. Ruined by design: How designers destroyed the world, and what we can do to fix it. Mule Design, San Francisco, CA, USA.Google ScholarGoogle Scholar
  30. Bonnie Nardi. 2015. Designing for the future: but which one? interactions 23, 1 (2015), 26--33. Google ScholarGoogle ScholarDigital LibraryDigital Library
  31. Richard Stuart Olson. 2000. Toward a politics of disaster: Losses, values, agendas, and blame. Crisis Management 18, 2 (2000), 154.Google ScholarGoogle Scholar
  32. World Meteorological Organization. 2011. Manual on flood forecasting and warning. World Meteorological Organization, Geneva, Switzerland.Google ScholarGoogle Scholar
  33. Palantir. 2020. Data vs. Disasters: Technology to Improve Crisis Response. Palantir. https://www.palantir.com/cgi/Google ScholarGoogle Scholar
  34. Leysia Palen and Kenneth M Anderson. 2016. Crisis informatics-New data for extraordinary times. Science 353, 6296 (2016), 224--225.Google ScholarGoogle Scholar
  35. D Perera, O Seidou, J Agnihotri, H Mehmood, and M Rasmy. 2020. Challenges and Technical Advances in Flood Early Warning Systems (FEWSs). Flood Impact Mitigation and Resilience Enhancement (2020).Google ScholarGoogle Scholar
  36. Duminda Perera, Ousmane Seidou, Jetal Agnihotri, Mohamed Rasmy, Vladimir Smakhtin, Paulin Coulibaly, and Hamid Mehmood. 2019. Flood Early Warning Systems: A Review Of Benefits, Challenges And Prospects. Technical Report. United Nations University Institute for Water, Environment and Health.Google ScholarGoogle Scholar
  37. Alan R Permut, Albert A Permut, and Ronald M Permut. 1979. Early flood warning system. US Patent 4,153,881.Google ScholarGoogle Scholar
  38. World Food Programme. 2019. The Innovation Accelerator wants your boldest ideas to disrupt hunger. World Food Programme. Retrieved August 12, 2020 from https://innovation.wfp.org/blog/innovation-accelerator-wants-your-boldest-ideas-disrupt-hungerGoogle ScholarGoogle Scholar
  39. Christian Reuter, Amanda Lee Hughes, and Marc-André Kaufhold. 2018. Social media in crisis management: An evaluation and analysis of crisis informatics research. International Journal of Human--Computer Interaction 34, 4 (2018), 280--294.Google ScholarGoogle ScholarCross RefCross Ref
  40. Rashida Richardson. 2019. Confronting Black Boxes: A Shadow Report of the New York City Automated Decision System Task Force. Technical Report. AI Now Institute.Google ScholarGoogle Scholar
  41. Himan Shahabi, Ataollah Shirzadi, Kayvan Ghaderi, Ebrahim Omidvar, Nadhir Al-Ansari, John J Clague, Marten Geertsema, Khabat Khosravi, Ata Amini, Sepideh Bahrami, et al. 2020. Flood detection and susceptibility mapping using sentinel-1 remote sensing data and a machine learning approach: Hybrid intelligence of bagging ensemble based on k-nearest neighbor classifier. Remote Sensing 12, 2 (2020), 266.Google ScholarGoogle ScholarCross RefCross Ref
  42. Robert Soden and Leysia Palen. 2018. Informating crisis: Expanding critical perspectives in crisis informatics. Proceedings of the ACM on human-computer interaction 2, CSCW (2018), 1--22. Google ScholarGoogle ScholarDigital LibraryDigital Library
  43. Robert Soden, Michael Skirpan, Casey Fiesler, Zahra Ashktorab, Eric PS Baumer, Mark Blythe, and Jasmine Jones. 2019. CHI4EVIL: Creative Speculation on the Negative Impacts of HCI Research. In Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems. 1--8. Google ScholarGoogle ScholarDigital LibraryDigital Library
  44. Susan Leigh Star and Karen Ruhleder. 1996. Steps toward an ecology of infrastructure: Design and access for large information spaces. Information systems research 7, 1 (1996), 111--134. Google ScholarGoogle ScholarDigital LibraryDigital Library
  45. Ted Steinberg et al. 2006. Acts of God: The unnatural history of natural disaster in America. Oxford University Press.Google ScholarGoogle Scholar
  46. Asaf Tzachor, Jess Whittlestone, Lalitha Sundaram, et al. 2020. Artificial intelligence in a crisis needs ethics with urgency. Nature Machine Intelligence 2, 7 (2020), 365--366.Google ScholarGoogle ScholarCross RefCross Ref
  47. Nuwan Waidyanatha. 2010. Towards a typology of integrated functional early warning systems. International journal of critical infrastructures 6, 1 (2010), 31--51.Google ScholarGoogle ScholarCross RefCross Ref
  48. Langdon Winner. 1980. Do artifacts have politics? Daedalus 109, 1 (1980), 121--136.Google ScholarGoogle Scholar
  49. William S Yerazunis and Darren L Leigh. 2003. Land and water based flash flood detection and warning system. US Patent 6,558,216.Google ScholarGoogle Scholar
  50. Baobao Zhang and Allan Dafoe. 2019. Artificial intelligence: American attitudes and trends. Elsevier SSRN, Amsterdam, Netherlands. https://dx.doi.org/10.2139/ssrn.3312874Google ScholarGoogle Scholar

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