Technology and Disaster Relief
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Technology and Disaster Relief

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Presented by Adele Waugaman, Harvard Humanitarian Initiative Fellow & Independent Consultant. October 15, 2012. Washington, D.C. "DC Design Week: Design for Disaster Relief," held in partnership with ...

Presented by Adele Waugaman, Harvard Humanitarian Initiative Fellow & Independent Consultant. October 15, 2012. Washington, D.C. "DC Design Week: Design for Disaster Relief," held in partnership with AIGA DC.

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  • Technology critical to disaster preparedness & response in a range of ways I’ll be talking about how new info & communications technologies (ICTs) are influencing the way disaster preparedness and relief programs are designed.How many of you were in DC for the earthquake last August?Information is essential in emergencies – a public good, itself a vital form of aid ICTs, mobile in particular, a critical conduit for info delivery, esp in LMICs
  • Natural disasters around the world last year caused a record $380 billion in economic losses. That's more than twice the tally for 2010, and about $115 billion more than in the previous record year of 2005According to a report from Munich Re, a reinsurance group in Germany.Since 1980, number of severe floods has almost tripled, and storms have nearly doubled, in part, to the impact of climate change With increasing changes to natural environment like rising sea level and drought, there will be increasing confluencebetween natural disasters and political conflict fueled by competition over access to scarce resources
  • Traditionally disaster preparedness response approached from a top-down, command and control system (UN, gov, corps & CSOs, citizens)Ex: UN system: diff agencies, challenge of coordinationIncredibly complex systems, operating in emergency environments that are highly fluid, with high levels of complexityEx: Haiti, which I’ll talk more about in a moment, gov and UN building destroyed, virtual absence of data
  • Challenging this top-down, command & control model – rise of ICTs, esp mobile6.2B mobile (fastest-growing markets are LDCs)Mobile = web accessFacebook 1B active users/month, equiv 3rd largest country (china 1.3B, India 1.2B, USA 315M)Enabling networksof volunteersEmpowering communities, individuals- giving them agency to access information they need to make well-informed decisions
  • 2009: New Tech. Early warning, preparedness, response, rebuilding – examples. 1-M: broadcast: 1-1: mobile voice SMS; M-M: social networks, mapping, crowd-sourcing. Then Haiti happens.2011: DR2.0 Social networks, geospatial imagery, crisis mapping, open data. Case study: Haiti What worked: Enormous international support, some V&TC efforts more successful than others. UshahidiTufts student-driven, mapped a lot of infoWhat didn’t work: Not a typical disaster, no activegov presence in early day. Ushahidi: but no plug-in with humanitarian system “responsibility to respond”?What do we need to do today to strengthen the future of resilience? Two reports address the question  Dec 09: New technologies and innovative uses of existing technologies are improving crisis preparedness, response, and prevention. Yet barriers to bringing these ideas to scale remain, and pose potential risks and rewards.Shift from one-to-many info flows (e.g. TV, radio) to many-to-many info flows (social networks/social media)Info flows now two-way. Beneficiary communities now have a tool to convey their needs. Can overwhelm or inform a relief effort.March 11: Disaster Relief 2.0 report looked at what rise of real-time information environment (social networks, cloud-based computing, mobile web, etc) means for information-sharing in the aftermath of complex humanitarian emergenciesWe looked at the response to the Jan ‘10 Haiti quake: How was the humanitarian system (UN, NGOs, govs) able to work with web-based non-humanitarian actors like the crisis mapping community (VTCs)?What do large institutions need to do to adapt to changed environment; how to adopt new tools strategies, policies?Significant challenges: authentication/verification, privacy, accuracy/trust Recommended 5-part framework to establish coordination with VTC and HTC (neutral forum, innovation space, deployable field team, research & testing consortium, clear operational interface)
  • Used OCHA’s 3WsPulled data from publicly-available sources24 hour delay and other tactics to ensure any secure info pulled before made publicBy the time we went to print, already out of date. Libya crisis saw first systemic and open collaboration between HS and VTCsOCHA, UNOSAT and NetHope collaborating with the Volunteer Technical Community (VTC) specifically CrisisMappers, Crisis Commons, Open Street Map, and the Google Crisis Response Team Addressed several challenges:Verifying credibility of VTC contributors: the CrisisMappers Standby Task Force created. They mapped social media, news reports and official situation reports from within Libya and along the borders at the request of OCHA. Protecting privacy: The public version of this map does not include personal identifiers and does not include descriptions for the reports mapped. All information included on this map is derived from information that is already publicly available online.For security reasons, reports were placed on a 24 hour embargo before being made public.
  • Citizens are the true first responders, but large agencies aren’t tooled to engage directly with the public.  Increasingly disaster affected populations have access to SMS and social media tools to relay their needs in near real-time. The convergence of broadband, multimedia and mobile makes it increasingly easy for these populations to be eyes and ears, gathering and reporting information about urgent needs. This ready access to communications tools coupled with the tremendous need to get and share information in emergencies is generating enormous quantities of new data. If decision makers wish to have access to (near) real-time assessments of complex emergencies, they need to figure out how to process information flows from thousands of individuals.

Technology and Disaster Relief Presentation Transcript

  • 1. Technology & Disaster Relief Credits: UN Foundation Adele Waugaman @Tech4Dev www.adelewaugaman.net
  • 2. Rising Incidence of Disasters UN/Evan Schneider
  • 3. Traditional DisasterPreparedness & Relief Interventions Source: Lucas Oleniuk, Toronto Star Source: OCHA
  • 4. Rising Access to ICTs Cell-Life
  • 5. Disaster Relief & ICTs UN/Evan Schneider TSF
  • 6. Case Study: Crowdsourcing Geolocation Information Using Crowdsourcing to Locate Hospitals on Maps One of more difficult Facts: Examples Haiti operation Relief 2.0 Activities in the health Fast problems during the of Disaster was determining the location of facilities. OCHA turned to the volunteer and technical communities to map these facilities, asking Crisis 2010 Haiti Earthquake Response Mappers and Sahana—examples of the Volunteer & Technical Communities—if they could crowdsource the effort to geo-locate 105 health facilities thatLocate Hospitals The Maps to the crowd went Using Crowdsourcing to had no location data. on request One of more difficult problems during the Haiti operation was determining the location of health out at 2:40AM on January 22. Approximately volunteer and technical communities to map these facilities, facilities. OCHA turned to the 35 asking Crisis Mappers and Sahana—examples of the Volunteer & Technical Communities—if hours later, the team working on the problem had located the de facto list of 102 of the 105 missing they could data into the Sahana to geo-locate 105 health facilities verified each hospitals, inputting all the crowdsource the effortdisaster management system. They had that had no location facility by having an OpenStreetMap member went out at hospital or clinicJanuary 22. Approximately 35 data. The request to the crowd locate the 2:40AM on on high-resolution satellite imagery at 15cm resolution and verify working on the problem located at the submitted coordinates. the 105 hours later, the team that health facility was had located the de facto list of 102 of missing hospitals, data formats, data into the Sahana disaster management system. They Sahana made the data available in openinputting all thewhich became one of the best resources for had verified each facility by having an OpenStreetMap member locate the hospital or clinic on health facility data for the next satellite imagery at 15cmunique individualsverify that health facility was high-resolution month. More than 8,000 resolution and visited the site or pulledlocatedfrom the feed. Crowdsourcing transformedtheproject that normally would require several days into just at the submitted coordinates. Sahana made a data available in open dataformats, which became one of the best resources for health facility data for the over one day.next month. More than 8,000 unique individuals visited the site or pulledfrom the feed. Crowdsourcing transformed a project that normally would requireseveral days into just over one day.Translating Creole through Mission 4636Mission 4636 facilitated the collaboration that a team at Stanford established withmembers of the Haitian diaspora to translate thousands of messages from Creoleinto English. Haitian Creole has only 12 million speakers worldwide, 9
  • 7. facilities. OCHA turned to the volunteer and technical communities to map these facilities, asking Crisis Mappers and Sahana—examples of the Volunteer & Technical Communities—if they could crowdsource the effort to geo-locate 105 health facilities that had no location Case Study: Crowdsourcing data. The request to the crowd went out at 2:40AM on January 22. Approximately 35 hours later, the team working on the problem had located the de facto list of 102 of the 105 Translations missing hospitals, inputting all the data into the Sahana disaster management system. They had verified each facility by having an OpenStreetMap member locate the hospital or clinic on high-resolution satellite imagery at 15cm resolution and verify that health facility waslocated at the submitted coordinates. Sahana made the data available in open data Translating Creole through the 4636 Shortcodeformats, which became one of the best resources for health facility data for thenext month. More than 8,000 unique individuals visited the site or pulleda team at Stanford established with Mission 4636 facilitated the collaboration thatfrom the feed. Crowdsourcing transformedHaitian diaspora towould require members of the a project that normally translate thousands of messages from Creoleseveral days intointo English. Haitian Creole has only 12 million speakers worldwide, 9 just over one day. million of which live in Haiti. In the first days of the disaster, Rob Munro (aTranslating Creole through Mission 4636Mission 4636 facilitated the collaboration that a team Stanford)established with computational linguist at at Stanford recruited Creole speakers from Facebook and othermembers of the Haitian diaspora to sites, asking them to begin translating tweets, SMS messages, and public web translate thousands of messages from Creoleinto English. Haitian Facebook posts million speakers worldwide, 9 Creole has only 12 coming from Haiti.million of which live in Haiti. In the first days of the disaster, Rob Munro (a computational linguist at Stanford)recruited Creole speakers from Facebook and other public web sites, asking them to begin translating tweets, SMS More than 130,000 text messages went through 4636 during the first month of themessages, and Facebook posts coming from Haiti. More than 130,000 text messages went through 4636 during response. At its peak, the effort had 1,200 Haitians translating thousands ofthe first month of the response. At its peak, the effort had 1,200 Haitians translating thousands ofmessages per day, usually within day,minutes of their arrival. By February, their arrival. By February, Rob began messages per 4.5 usually within 4.5 minutes of Rob began a partnership withCrowdflower, a social venture for microtasking that was working social venture another social venturethat partners a partnership with Crowdflower, a with Samasource, for microtasking with was workingon the ground who could recruit Haiti citizens to perform translation services from Haiti. Theon the ground who could with Samasource, another social venture with partners effort transitioned to this professional translation platform soon thereafter. recruit Haiti citizens to perform translation services from Haiti. The effort transitioned to this professionalin Haiti Provides a Vital Link Cell Connectivity translation platform soon thereafter. According to a report by the US Institute of Peace,  “approximately  85 percent of Haitian households had access to mobile phones at the time of the earthquake, and although 70 percent of the cell phone towers in Port-au-Prince had been destroyed in the disaster, they were quickly repaired and mostly back online before the 4636 number  was  operational.”  Haitians sent hundreds of thousands of messages out via SMS to Twitter, Facebook, Ushahidi, the
  • 8. Challenges with Linking Volunteer Networks & Aid Agencies• Protocol• Capacity building (training, setting expectations)• Standards (protection, privacy, data security)• Push v pull• Funding• Sustainability (workflow transition)• Relevance (engagement of local actors) OCHA Humanitarian Graphics
  • 9. Case Study: Libya
  • 10. Citizen-Centered Disaster Relief Design DataDyne.org GSMA
  • 11. Challenges with Direct Citizen Engagement in Humanitarian Assistance• Coordination• Feedback• Protocol• Capacity building (training, setting expectations)• Standards (protection, privacy, data security)• Push v pull• Funding• Sustainability (workflow transition)• Relevance (engagement of local actors) WFP/John Wreford WFP/John Wreford