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Suggested Citation:"3 A Research Agenda." National Academies of Sciences, Engineering, and Medicine. 2017. Emergency Alert and Warning Systems: Current Knowledge and Future Research Directions. Washington, DC: The National Academies Press. doi: 10.17226/24935.
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Suggested Citation:"3 A Research Agenda." National Academies of Sciences, Engineering, and Medicine. 2017. Emergency Alert and Warning Systems: Current Knowledge and Future Research Directions. Washington, DC: The National Academies Press. doi: 10.17226/24935.
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Suggested Citation:"3 A Research Agenda." National Academies of Sciences, Engineering, and Medicine. 2017. Emergency Alert and Warning Systems: Current Knowledge and Future Research Directions. Washington, DC: The National Academies Press. doi: 10.17226/24935.
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Suggested Citation:"3 A Research Agenda." National Academies of Sciences, Engineering, and Medicine. 2017. Emergency Alert and Warning Systems: Current Knowledge and Future Research Directions. Washington, DC: The National Academies Press. doi: 10.17226/24935.
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Suggested Citation:"3 A Research Agenda." National Academies of Sciences, Engineering, and Medicine. 2017. Emergency Alert and Warning Systems: Current Knowledge and Future Research Directions. Washington, DC: The National Academies Press. doi: 10.17226/24935.
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Suggested Citation:"3 A Research Agenda." National Academies of Sciences, Engineering, and Medicine. 2017. Emergency Alert and Warning Systems: Current Knowledge and Future Research Directions. Washington, DC: The National Academies Press. doi: 10.17226/24935.
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Suggested Citation:"3 A Research Agenda." National Academies of Sciences, Engineering, and Medicine. 2017. Emergency Alert and Warning Systems: Current Knowledge and Future Research Directions. Washington, DC: The National Academies Press. doi: 10.17226/24935.
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Suggested Citation:"3 A Research Agenda." National Academies of Sciences, Engineering, and Medicine. 2017. Emergency Alert and Warning Systems: Current Knowledge and Future Research Directions. Washington, DC: The National Academies Press. doi: 10.17226/24935.
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Suggested Citation:"3 A Research Agenda." National Academies of Sciences, Engineering, and Medicine. 2017. Emergency Alert and Warning Systems: Current Knowledge and Future Research Directions. Washington, DC: The National Academies Press. doi: 10.17226/24935.
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Suggested Citation:"3 A Research Agenda." National Academies of Sciences, Engineering, and Medicine. 2017. Emergency Alert and Warning Systems: Current Knowledge and Future Research Directions. Washington, DC: The National Academies Press. doi: 10.17226/24935.
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Suggested Citation:"3 A Research Agenda." National Academies of Sciences, Engineering, and Medicine. 2017. Emergency Alert and Warning Systems: Current Knowledge and Future Research Directions. Washington, DC: The National Academies Press. doi: 10.17226/24935.
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Suggested Citation:"3 A Research Agenda." National Academies of Sciences, Engineering, and Medicine. 2017. Emergency Alert and Warning Systems: Current Knowledge and Future Research Directions. Washington, DC: The National Academies Press. doi: 10.17226/24935.
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Suggested Citation:"3 A Research Agenda." National Academies of Sciences, Engineering, and Medicine. 2017. Emergency Alert and Warning Systems: Current Knowledge and Future Research Directions. Washington, DC: The National Academies Press. doi: 10.17226/24935.
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Suggested Citation:"3 A Research Agenda." National Academies of Sciences, Engineering, and Medicine. 2017. Emergency Alert and Warning Systems: Current Knowledge and Future Research Directions. Washington, DC: The National Academies Press. doi: 10.17226/24935.
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Below is the uncorrected machine-read text of this chapter, intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text of each book. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

3 A Research Agenda As Wireless Emergency Alerts (WEAs) and other new technologies have been deployed, research investments, in large part supported by the Department of Homeland Security (DHS), have provided some insight into questions around the use of new technologies for alerting (Appendix B includes summaries of this work). However, to reach the above-envisioned alert and warning system, additional research questions will need to be answered, not only about the use and design of WEA but evolving systems. Given that alerts and warning are inherently interdisciplinary, both a social science phenomenon (their goal is to change public behavior) and a technical phenomenon (technology is required for their assessment and dissemination) this research agenda includes a wide range of socio-technical questions and highlights the need to for social and behavioral scientists and technologists to interact frequently with each other. The agenda is divided into key sections, public response, feedback and monitoring, and technical-capabilities and their impact. PUBLIC RESPONSE TO ALERTS AND WARNINGS Ultimately, alert and warning systems need to be designed to elicit the most life and safety protecting response from the public. Research has evolved over the last several decades so that we have much more information about how individuals respond to alerts and warnings, nevertheless, as technologies shift, so does public responses; therefore, continued research is invaluable. These responses rely on several things, including characteristics of the messages themselves, demographics of the individuals who receive the messages, and, given our increased ability to geotarget messages, the understanding of an individual’s risk in relationship to their location and the hazard. Research is also needed to understand how best to educate the public about both alerting systems and impacts of and appropriate response to particular hazards. Message Characteristics Protective Guidance in Enhanced Media Links Prior research called for including URLs in WEAs to provide more complete information on the hazard and recommended protective guidance.1 Practitioners also spoke to the importance of enhanced warnings. For example, Christopher McIntosh, former Virginia statewide interoperable communications coordinator and current director for national government industries at GIS firm Esri observed that “without context, alerts are just noise.”2 1 M. Wood, H. Bean, B. Liu, and M. Boyd, 2015, Comprehensive Testing of Imminent Threat Public Messages for Mobile Devices: Final Report, National Consortium for the Study of Terrorism and Responses to Terrorism. 2 Christopher McIntosh, ESRI, presentation to the committee on January 26, 2017. PREPUBLICATION COPY – SUBJECT TO FURTHER EDITORIAL CORRECTION 40

At this point, it is unclear what information is best included in a WEA message and what information is best included in linked content. Prior DHS-funded research did not examine exactly 360 character length messages because the research was conducted before the FCC rulemaking that extended WEAs from 90 to 360 characters.3 Furthermore, concerns remain as network congestion could be caused by people accessing an included link within seconds of receiving a WEA that includes a URL.4 Alternatively, some research found that message recipients are unlikely to open linked content and that instead they read only a few words of WEA-like messages due to stress responses.5 Therefore, research is needed to understand what message content should be included in linked media. Also unknown is how to craft WEA messages so that they galvanize people to read the entire message, including potentially life- saving linked content. Research is also needed on whether it is more effective to enhance protective action guidance by using longer, 360 characters alerts or by adding links to additional information. A consistent finding across WEA research is that the American public needs education on what the WEA service is as well as what protective actions to take during a variety of hazards. Expressing Time Until Hazard Impact The START research team found that the standard WEA message elements of guidance (what to do and how to do it) and time until impact (how much time people have to take the recommended action) play major roles relative to other message elements in the outcomes of public understanding and belief of the protective action recommendation and the ability to decide how to respond.6 The other WEA message content elements are hazard, location, and source. Importantly, the START research team found that WEAs should express time as how much time until impact rather than when the message expires, as is the current practice for WEAs. WEA messages are designed to alert about imminent threats, which the START research team characterized as hazards occurring within one hour. Other research has extensively examined the optimal timing of warnings. For example, research on tornados finds that the optimal lead for issuing a tornado warning is from 15 minutes to just over 30 minutes.7 If too much lead-time is provided, people are less likely to follow the protective guidance in a timely manner. Therefore, it is important to understand how to best express lead-time. Opt-In/Opt-Out Current WEA guidelines allow for opting out of all categories of alerts except for those issued by the U.S. President (which have never been issued). However, individuals now receive messages from an increasing number of sources and delivery channels. Past research suggestions that alerts and warnings should be sent through as many channels as possible but new research is needed to explore what drives 3 Federal Communications Commission, “FCC Strengthens Wireless Emergency Alerts as a Public Safety Tool,” release date September 29, 2016, https://apps.fcc.gov/edocs_public/attachmatch/DOC-341504A1.pdf. 4 Federal Communications Commission, “Improving Wireless Emergency Alerts and community-initiated alerting,” release date November 19, 2015, https://apps.fcc.gov/edocs_public/attachmatch/FCC-15-154A1.pdf 5 D. Glik, K. Harrison, M. Davoudi, and D. Riopelle, 2004, Public Perceptions and Risk Communication for Botulism, Biosecurity and Bioterrorism: Biodefense Strategy, Practice, and Science 2(3):216-223. 6 M. Wood, H. Bean, B. Liu, and M. Boyd, 2015, Comprehensive Testing of Imminent Threat Public Messages for Mobile Devices: Final Report, National Consortium for the Study of Terrorism and Responses to Terrorism. 7 S. Hoekstra, R. Butterworth, K. Klockow, D.J. Drotzge, and S. Erickson, 2011, A social perspective of warn on forecast: Ideal tornado warning lead time and the general public’s perceptions of weather risks, Weather, Climate & Society 3(1):128-140; and K.M. Simmons, and D. Sutter, 2009, False alarms, tornado warnings, and tornado casualties, Weather Climate and Society 1(1):38–53. PREPUBLICATION COPY – SUBJECT TO FURTHER EDITORIAL CORRECTION 41

opt-in and opt-out behaviors on WEA and as well as various platforms, such as third-party applications, or local text alerting systems. While past research8 supported the delivery of alert messages across as many channels as possible, it is unknown if the increasing number of alerting channels provides the same benefits or if it instead creates a situation of over-alerting, which may result in increased opt-out rates. Furthermore, once we understand optimal times and way to alert an individual, what are technical solution to avoid over-alerting? Message Length While we know a lot about what a message should contain less is known about how to best present this information. Recent research has provided clear evidence that message length influences response; messages that can fit in the initial 90 character length of a WEA message and the 140 characters of Twitter foster milling9 behavior and delay response.10 At this point, it is unclear what information is best included in a 360 character WEA message and what information is best included in linked content. Prior WEA research did not examine 360 character messages because the research was conducted before the pending FCC rulemaking that extended WEAs from 90 to 360 characters.11 However, research suggests that a message length of 1,380, the maximum number of characters supported by the CAP standards additional information field, does reduce response time.12 Research is needed to understand public response to messages that fit into 360 characters and, given that optimal message length is relevant to any text based alerting system, continued research should be done to understand the optimal minimum length that can elicit the appropriate protective action from an alerted population. 8 Considering the sharing of emergency alerting messages, there are several benefits to an ecosystem that incorporates multiple different channels. One is redundancy—i.e. a message distributed via different channels (via different technological infrastructures) is more likely to reach its intended recipients in cases where some infrastructures are disrupted. The second benefit is diversity—i.e. people rely on different types of media platforms (e.g. due to cultural preference, education or accessibility) and so messages spread across diverse channels will reach a greater number of people. A third benefit is that people are more likely to accept and respond to emergency messages when they receive them from multiple channels and in different formats. This latter benefit, which was identified in classic studies, requires more research to confirm and better understand in the context of this new media ecosystem. 9 Milling refers to the process in which people seek to confirm an alert or warning, a process that has been observed across all hazard types, warning delivery technology, or message sources. 10 H. Bean, M. Wood, D. Mileti, B.F. Liu, J. Sutton, and S. Madden, 2013, Phase II Interim Report on Results from Experiments, Think-out-Loud, and Focus Groups, Comprehensive Testing of Messages for Mobile Devices. Report to the Homeland Security Advanced Research Projects Agency, Science and Technology Directorate, U.S. Department of Homeland Security. College Park, MD: National Consortium for the Study of Terrorism and Responses to Terrorism, University of Maryland. 11 Federal Communications Commission, “FCC Strengthens Wireless Emergency Alerts as a Public Safety Tool,” release date September 29, 2016, https://apps.fcc.gov/edocs_public/attachmatch/DOC-341504A1.pdf 12 H. Bean, B.F. Liu, S. Madden, J. Sutton, M.M. Wood, and D.S. Mileti, 2016, Disaster Warnings in Your Pocket: How Audiences Interpret Mobile Alerts for an Unfamiliar Hazard, Journal of Contingencies and Crisis Management 24(3): 136-147. PREPUBLICATION COPY – SUBJECT TO FURTHER EDITORIAL CORRECTION 42

Demographics Language and Dialect WEA currently supports messages in Spanish but this coverage falls well short of the linguistic diversity of the US population. What technical challenges exist in transmitting multiple languages, or relying on the receiving device to translate messages? Additionally, protective action language, such as shelter in place, might be challenging to translate to various languages and dialects. Research is needed to understand language translations (in particular machine translations)—and determine ‘good enough’ language so that message templates can be automatically translated—for differing languages and dialects. Adapting to Differing Abilities Mobile devices exist that can be used by a wide set of differently abled individuals, these include a range of tools such as use of vibration cadences to braille phones and text-to-speech and vice-versa based on needs of physically challenged individuals. Research is needed to understand best way for enabling specific customization (translating and delivering) alerts and warnings to physically and cognitively challenged individual. What other technologies exist to support information dissemination to differently-abled individuals? How can protective action instructions shift to support diverse populations—including those of differing ages and abilities—and their caregivers? Questions around literacy are also important, in terms of both age (given that children under 10 may receive an alert on their cell phone) and reading comprehension for older adults. Technology Access While a large section of the population uses smart phones, there are still others who choose not use smart phones or use them sporadically. Considering the diversity in communication habits and availability of technology, alert and warning systems will need to consider various technologies to reach at risk populations. Geotargeting Alerts and Warnings Communicating Location Research suggests that people do not easily understand messages that contain a map reflecting the at-risk area.13 We know that a map that shows the risk area alone is not useful. In fact, it can be counterproductive. What is needed is research on how to best communicate, possibly through visualizations, about the location of the message receiver versus the area of impact. Research is needed to determine the best way to graphically display that an individual is in an at-risk location. 13 M. Wood, H. Bean, B. Liu, and M. Boyd, 2015, Comprehensive Testing of Imminent Threat Public Messages for Mobile Devices: Final Report, National Consortium for the Study of Terrorism and Responses to Terrorism. PREPUBLICATION COPY – SUBJECT TO FURTHER EDITORIAL CORRECTION 43

Determining Locations of Interest Individuals want to be alerted not only when they are at risk, but also, for example, when their children may be at risk at school or their home may be at risk. These locations of interests can be difficult to determine. Most systems rely on the receiving device being currently within the designated warning area; if a person works outside of a WEA alert area but their home is within the WEA alert area, they will not receive the message that there home is at risk. Most receive these alerts via subscription services, such as those provided by a school system or county. Are there technical solutions so that locations of interests can be dynamically updated (rather than manually updated by the end-user)? Location-Based Protective Action The best protective action for an individual may vary across the impacted area—shelter in place versus evacuation. Furthermore, individuals could be prescribed specific evacuation routes to spread traffic over different routes. What are the technical challenges to these technologies? Applications like Waze could provide some of these capabilities. What are limitations to implementing these for disaster responses? How might we encourage use of these tools? In-Building Location Indoor location capabilities are already being deployed in some areas, chiefly for marketing reasons as well as for meeting wireless E911 location requirements. The FCC now requires that carriers provide location information to within 50 meters of a caller’s location (inside or outside of buildings) for 40% of the cases currently and in the near future for 60% of the cases. This requirement includes both horizontal and vertical location information. However, determining elevation and which floor a user is challenging and is a valuable research area. Knowledge of a person’s location within a building could be used to determine the best evacuation route or if the individual should instead shelter-in-place. Community Engagement New tools and technologies support communications between members of a community; for example, NextDoor allows people to quickly identify neighbors and communicate with those people who reside either in their neighborhood or nearby. NextDoor is already being used by public safety organizations to educate the public;14 however, little is known about how these tools are used during hazards. As discussed in Chapter 1, collaborative tools have been used to provide assistance during a disaster but mostly fueled by volunteers outside of the area. Less is known about how local residence interact with each other to build resilience and educate others about particular hazards and how that information propagates up a social group. This of course intersects with other research areas around reposting information on social media and disaster education, but is also an important area of research alone. 14 M. Helft, “A Facebook for crime fighters,” Fortune.com, July 1, 2014, http://fortune.com/2014/07/01/nextdoor-local-neighborhood-social-network-police/. PREPUBLICATION COPY – SUBJECT TO FURTHER EDITORIAL CORRECTION 44

Disaster and Alerting Education Across the DHS-funded studies, research participants were found to be unfamiliar with WEAs15 despite the Ad Council partnering with DHS to promote the WEA service.16 Given the character constraints of WEAs, researchers found that participants required more information to properly execute recommended protective actions.17 Very limited research exists to determine what makes for effective disaster public education. Research finds that current public education campaigns typically are ineffective because they are not specific enough and do not contain content that motivates behavior change.18 More research is needed to determine how to motivate behavior change as well as what other factors contribute to successful public disaster education campaigns. In terms of in-person training, research points to positive results from these public education initiatives. For example, in one study researchers found that after receiving instruction on relevant meteorological principles, participants successfully applied their new knowledge to make risk inferences from hazard graphics.19 As another example, an evaluation of research on disaster education programs concluded that these programs are effective at increasing children’s disaster knowledge and preparedness as well as household preparedness.20 Finally, emergency managers have just begun to integrate gamification into public education, and it is too soon to tell how effective this approach is for increasing individual, family, and community disaster preparedness. For example, in 2013 the Centers for Disease Control and Prevention launched the “Solve the Outbreak” mobile app, which allows users to be “disease detectives” through obtaining clues, analyzing data, solving scenarios, and saving lives in the game. So far, the app has been downloaded more than 12,000 times. Research on whether this app and/or others improve preparedness and capacity to effectively respond to warnings during disasters remains to be documented. A similar research topic is how best to use tools, such as video and animation, to model protective actions and the use of tools that provide education as a disaster unfolds. POST-ALERT FEEDBACK AND MONITORING FOR EMERGENCY ORGANIZATIONS Technology is needed that solicits feedback from message recipients to help understand how public is responding to messages and what additional information might be needed. While some tools exist to help individuals in the EOC to harvest information from social media and potential feedback mechanisms in alerting applications on mobile devices, these tools will need to be more readily available. 15 START DHS study; Kar DHS study; Glik DHS study; and others. 16 Ad Council, “Emergency Preparedness – Wireless Alerts,” https://www.adcouncil.org/Our- Campaigns/Safety/Emergency-Preparedness-Wireless-Alerts, accessed August 22, 2017. 17 M. Wood, H. Bean, B. Liu, and M. Boyd, 2015, Comprehensive Testing of Imminent Threat Public Messages for Mobile Devices: Final Report, National Consortium for the Study of Terrorism and Responses to Terrorism. 18 B.J. Adame, and C.H. Miller, 2015, Vested interest, disaster preparedness, and strategic campaign message design, Health Communication 30(3):271-281; J.D. Fraustino, and L. Ma, 2015, CDC’s use of social media and humor in a risk campaign – Preparedness 101: Zombie apocalypse, Journal of Applied Communication Research 43(2):222-241; and M.M. Turner, and J.C. Underhill, 2012, Motivating emergency preparedness behaviors: The differential effects of guild appeals and actually anticipating guilty feelings, Communication Quarterly, 60(4):545- 559. 19 M. Canham, and M. Hegarty, 2010, Effects of knowledge and display design on comprehension of complex graphics, Learning and Instruction 20(2):155-166. 20 V.A. Johnson, K.R. Ronan, D.M. Johnston, and R. Peace, 2014, Evaluations of disaster education programs for children: A methodological review, International Journal of Disaster Reduction, 9(1):107-123. PREPUBLICATION COPY – SUBJECT TO FURTHER EDITORIAL CORRECTION 45

Perhaps more importantly, research is needed to understand what information would be most helpful to emergency managers and social science researchers and how best to collect the information. Not only would this additional data help emergency managers during disasters, but could also serve to validate laboratory experiments. Several researchers have conducted experiments to explore word choice, message content, and character length. While these experiments provide valuable data, real-world analysis could provide validation and further information on public response. Tools, including those that employ machine learning and other artificial intelligence techniques are also needed that can quickly understand and process collected information. Consistent, well-understood, and insightful measurements can inform (and improve) response to future hazards (Box 3.1 lists information that could be valuable). Such a data-driven experimental framework would be of great interest to multiple stakeholders, including emergency managers, researchers, technologists, and so on. By building measurement into the alerts and warning system itself, researchers can gain supporting evidence for findings made in lab studies (e.g., what is the optimal message length? should we include a map or not?). By sharing information across hazards, we can learn from past experiences to create new best practices. Feedback during the lifecycle of a hazard can also be integrated into future responses within the same incident. For example, low response rates to an initial message could lead to more aggressive message content in a follow-on message. In parallel with measurements of the messages themselves, we also encourage new measurements of ancillary supporting technologies. For example, what level of engagement is seen on social media and local news websites? What content was most engaged with? What fraction of users in a region used Waze? And so on. We anticipate new data sharing initiatives for the multiple stakeholders in the alerts and warnings ecosystem. For example, it could be beneficial for social media companies to provide aggregate (anonymized) measurements in the aftermath of an alert. BOX 3.1 Measuring the Effectiveness of Alerts and Delivery Mechanisms Performance monitoring can be undertaken throughout the lifecycle of an alert. In some cases, new standards may need to be adopted or new technologies created to support monitoring and feedback. Similarly, new social science research will be needed to assess the usefulness of metrics. Examples of possible measurements of interest could include:  Coverage. How many people (or devices) received a message? And what fraction of all affected people is this? What are the characteristics of those who did not receive a message, and how can this gap be closed?  Message engagement. How long did people view a message? Was it immediately dismissed? By measuring device properties, we may gain additional evidence of engagement with a message and follow- up activities (e.g., phoning a friend, checking social media feeds). Of course, privacy is a paramount concern here.  Actions taken. Upon receiving a message, how many people take action? And what actions are these? Perhaps structured responses can be created so that people can do a “safety check” or equivalent, depending on the nature of the alert. Careful design of feedback mechanisms is important.  Latency. What is the time from inciting incident to message received by users? Latency here could be measured at different levels of granularity—including network performance measures based on when a message is injected, time from inciting incident to message injection itself, and so on.  Translation effectiveness. Measurements of engagement to a message can also provide downstream understanding of the quality of upstream decisions. For example, machine translation of messages may achieve a particular “accuracy” in off-line assessments, but through measurements of these translations in practice we can provide supporting evidence of the quality of the translation (e.g., an off- line translation engine may have 98% accuracy, but lead to much lower engagement once issued). PREPUBLICATION COPY – SUBJECT TO FURTHER EDITORIAL CORRECTION 46

TECHNICAL CHALLENGES AND THEIR IMPACT Delivery Technology Enhanced Cell Broadcast and Network Capabilities Cellular networks have become the most popular access mechanism in the current scenario due to the wide use of the device. However, there are limitations to the current implementation of cell broadcast—limitations in coverage, capability of handling message size, and inability to facilitate two- way communication. Research is needed to understand capabilities and features that may take advantage of newer broadcast technologies and supplement older technologies. Research questions include: Is it feasible to combine multiple cell broadcast messages core into a single, longer alert message?21 What will the impact of including a URL be on network capacity? Recent WEA testing has indicated that messages are not always delivered as expected;22 what is creating these errors? As we move to newer wireless network standards, is it possible to have flexi-bandwidth provision between 90-360-720 character to use existing 2.5 G-3G network as well as new upcoming 4G-LTE networks? Multi-Modal Transport of Emergency Alerts Today WEA is designed only for cellular transport. However, cellphones can receive data through a variety of wireless communications standards. For example, phones are commonly connected through home or public WiFi hotspots. How can WEA be adapted so that it can use multiple channels to increase the likelihood of successful delivery to the end-user? How can a single message be delivered through an increasing number of delivery channels—including government and private channels? Bypassing Network Failure During hazards, some cellular networks may not function properly, owing to either overload or to infrastructure damage.23 Several technologies exist that might support message receipt, including mesh networks, peer-to-peer communication, and FM radio transmission. For example, with peer-to-peer communications techniques, such as those used by FireChat, messages might be relayed to people lacking a direct network connection. Research is needed to validate the efficacy of these various technologies and understand the implementation of these tools. 21 ATIS completed feasibility studies on message length in (year) and recommended the expansion to the current 360 character limit for next generation networks. https://access.atis.org/apps/group_public/download.php/25045/ATIS-0700023.pdf Additional feasibility studies may be necessary to understand future limitations. 22 FCC, 2017, “Report: September 28, 2016 Nationwide EAS Test,” FCC, https://apps.fcc.gov/edocs_public/attachmatch/DOC-344518A1.pdf and in briefing and discussions with the committee. 23 The National Academies reviewed the impact of network usage during disasters in its report, “The Internet Under Crisis Conditions: Learning from September 11.” PREPUBLICATION COPY – SUBJECT TO FURTHER EDITORIAL CORRECTION 47

Battery Life Management on End User Devices Power resources can be quickly drained during disasters as users attempt to find information. If main power to a home is out, a user will also lose access to Internet service and forced to rely on cellular data service that uses more battery power than in-home wireless, and will be unable to recharge devices. Research is needed to determine possibilities for reserving power resources to support alert and warning delivery, implementing battery preservation technologies across available platforms, and possibly providing information back to first responders about lack of message receipt due to power concerns. BOX 3.2 The Role of Standards in Delivering Alerts and Warnings Technical standards play an important role in communication systems. As such, a single emergency alert message standard is needed to communicate alerts over a variety of communications infrastructure (e.g., broadcast TV and radio, cellular, and wired media), thereby reaching the end user over variety of last mile technologies (e.g., cellular, cable, DSL, WiFi, Bluetooth). The Common Alerting Protocol (CAP) attempts to serve as this purpose. CAP, which is used by IPAWS, provides a base standardized data profile for defining a consistent way for alert and warning messages to be distributed amongst the involved entities (alert originators, FEMA, NOAA, public safety, broadcasters and mobile operators. This standard takes the form of an XML format and is part of the many standardized XML formats that the Organization for the Advancement of Structured Information Standards (OASIS) maintains. The CAP standard describes how the information is formatted. While CAP provides a common format, any changes in the type of information exchanged in CAP or any changes in how the carriers might communicate this information to a wireless subscriber requires additional standards and version to these standards. Standards efforts can take years to complete even relatively simple changes to existing standards. For example, it took several years for the cellular standard body (3GPP) to recently come up with a specification that allows the transmission of 360 character WEA messages. Alert and warning standards—and communication standards that support delivery alerts and warnings—could evolve more rapidly to incorporate socio-technical understanding of public response. Role of Connected Devices As the Internet of Things (IoT) grows, more devices in homes and throughout the environment will be available as not only an alerting channel, but also to detect emergencies and potential risk. To make most effective use of these opportunities, several questions will need to be explored. Aggregating Data If each home can serve as a mini-weather station or stream gauges are deployed pervasively, what data would be most helpful and how can data be trusted enough to automatically issue an alert and warning? Automation of some alerting, based on aggregate data, would resolve latency issues around fast- moving hazards? For example, in several areas of Japan, earthquakes are detected and elevators, trains, and gas valves are immediately cut off. Could a similar action for different events such as an active shooter event—gunfire on campus is detected and classroom doors locked? Machine learning is needed to PREPUBLICATION COPY – SUBJECT TO FURTHER EDITORIAL CORRECTION 48

understand how systems can become sufficiently data intensive and have enough situational awareness to suggest the best protective action to take—i.e. when to shelter in place, when to evacuation, and where to evacuate? Best Devices for Alerting If most electronics can deliver some sort of information to its user, which devices should be used to issue which hazards? Could the increasing number of smart devices better communicate appropriate protective action? For example, if a disaster results in a boil water order, could a smart refrigerator post an alert when the water dispenser is used? Milling with Virtual Assistants As more homes are equipped with virtual assistants, such as an Alexa or Google Home, what role will the play in milling behavior? One can envision receiving an alert from Alexa that a tornado warning has been issued and a user asked Alexa to explain the difference between a tornado watch and tornado warning or asking what the best protective action might be. This might on the one hand reduce milling times because confirming information can be obtained quickly and on the other hand might extend milling because it introduces new avenues for extended information seeking. BOX 3.3 In-Vehicle Alerting Given the ubiquity of terrestrial radio in vehicles, drivers historically received alerts and warnings through the Emergency Alert System. With the deployment of WEA and the increasing number of weather applications that support alerting, the mobile phone is also increasingly the source of alerts for drivers. Navigational tools, both those built into the vehicle and mobile applications, can also provide alerts, although they tend, naturally, to focus on traffic hazards. How can these tools be adopted to provide better alerts and warnings, suggestions for protective action, and situational awareness back to emergency responders?  Emergency shelter locations along with Web and phone links  Information about the status of gas station  Information about unusual traffic patterns  Real-time updates on road closures and other hazard conditions24 The navigation service Waze has worked with local emergency managers and other volunteers to provide some hazard alerting capabilities, including the following For example, drivers—and in the future, autonomous vehicles—can be automatically rerouted around flooded roadways or overcrowded evacuation routes. 24 Adapted from Google, “Crisis even support on Waze,” https://support.google.com/waze/partners/answer/6342326?hl=en, accessed September 7, 2017. PREPUBLICATION COPY – SUBJECT TO FURTHER EDITORIAL CORRECTION 49

Security, Trust, and Privacy A system that instructs large populations to take particular action may represent a significant target for attacks on service availability, compromises of the integrity of valid messages, and spoofed messages. Emergency alerting systems have been directly compromised already, including the use of false Emergency Alert System (EAS) tones, resulting in the issuance of false alerts on radio and TV stations in several states in 2014.25 (Box 3.4 lists some breaches that have already occurred.) Indeed, a 2014 report from Carnegie Mellon University’s Software Engineering Institute26 identifies a number of attack vectors that specifically target WEA, including:  An outsider obtaining the proper credentials to send malicious CAP-compliant messages, for example, to direct people toward a dangerous location rather than away from it.  Malicious code that has infected an alert origination service could prevent an operator from posting a new alert, and hence delaying notification.  An insider may spoof a colleague’s identity to send an illegitimate CAP-compliant message, thereby spreading false information and undermining the colleague’s reputation.  Malicious attacks could make communication channels unavailable, so that an operator could not distribute an alert message through IPAWS. These and related threats highlight the critical cybersecurity challenges with maintaining the integrity of existing and future alert and warning systems. BOX 3.4 Alert System Breaches  In November 2010, Iowa’s alerting system was compromised, resulting in the issuance of a false AMBER Alert.1  On February 11, 2013, a hacker sent out an emergency alert that read “dead bodies are rising from their graves,” in some counties in Great Falls, Montana.2 In a similar case, on February 12, 2013, two Michigan Television Stations began displaying a fake alert message warning people of zombie attacks in various Michigan counties after the emergency alert system was hacked.3  On September 28, 2016, FEMA’s Emergency Alert System was hacked and television viewers in Utica, New York received a warning on their screen of a pending Hazardous Materials disaster somewhere in the United States.4  On February 8, 2017, a hacker set off all 156 emergency sirens in Dallas, Texas.5 1 Amber Alert, 2011, Hacked: Lessons From the Attack on the Iowa AMBER Alert System, The Amber Advocate, 5(2):7. 2 D. Moye, “KRTV’s Emergency Alert System Hacked To Warn Of Fake Zombie Apocalypse (VIDEO),” last update February 16, 2013, http://www.huffingtonpost.com/2013/02/11/krtv-fake-zombie-alert_n_2665469.html. 3 Huffington Post, “Zombie Warning Shown On Michigan TV Stations After Emergency Alert Systems Hacked (VIDEO),” release date February 12, 2013, http://www.huffingtonpost.com/2013/02/12/zombie-warning-michigan- tv-alert-video_n_2671044.html. 4 Off the Grid, “FEMA’s Emergency Alert System Hacked: Warns of Hazardous Materials Disaster,” release 25 R. Wimberly, “$1 Million Fine for Misusing the Emergency Alert System,” release date May 19, 2015, http://www.govtech.com/em/emergency-blogs/alerts/1000000-Fine-for-MisUsing-Emergency-Alert-System.html. 26 Carnegie Mellon University, 2014, Wireless Emergency Alerts (WEA) Cybersecurity Risk Management Strategy for Alert Originators, CMU/SE I-2013-SR-018, Pittsburgh, Pa. PREPUBLICATION COPY – SUBJECT TO FURTHER EDITORIAL CORRECTION 50

date September 29, 2016. https://offgridsurvival.com/femas-emergency-alert-system-hacked-warns-hazardous- materials-disaster/. 5 D. Stanglin, 2017, “Hacker sets off all 156 emergency sirens in Dallas,” USA Today. Alerts that can be reliably and undeniably attributed to their actual author is essential to warning system use. This is a particular problem when warning credentials are issued to a jurisdiction or agency rather than to the individual that should be held accountable. If the only feasible sanction for a misuse of a warning system is to threaten to cut off warning system access to an entire jurisdiction, such a sanction is unlikely to be perceived as a genuine threat. Barriers to providing personal credentials need to be studied and remedies devised. Furthermore, research on password management and security could be incorporated into system training tools. Spoofing, in particular, has been recognized as a threat to the validity of many communication channels, including email, the web, GPS data,27 and sensor data, among many others. Already, we have seen spoofing attacks on social media to post fake messages as in the April 2013 case of hackers taking control of the official Associated Press (AP) Twitter account to post false reports about an explosion at the White House. Though discovered and corrected in minutes, the spoofed post led to a 100-point drop in the Dow Jones Industrial Average. While the drop was only momentary—the unsophisticated tweet lacked AP style and other indicators of legitimacy—more sophisticated spoofs in the future could attack multiple channels at once (e.g., the AP Twitter account, Facebook presence, and their wire service) while adopting more credible language to create even more uncertainty. Furthermore, as the system takes advantage of these large data sets and harnessing information from the public, misinformation can pose a challenge. A misunderstanding by the public and poor reporting can create misinformation, but it can also be inserted intentionally. Quickly detecting and correcting poor information will be a valuable system capability. As emergency managers begin harnessing information from users and social media and provide geographically relevant information, concerns around user privacy arise. How can we take advantage of these tools while still protecting end-user privacy? BOX 3.5 Using Social Media to Detect and Address Rumors and Misinformation Rumors and misinformation have been identified as a significant threat to the utility of social media and other online tools during disaster events. Many emergency responders cite misinformation on social media as a major concern and a barrier to adopting social media in their work.1 However, rumors in the emergency response context are not new and not specific to social media or the Internet. Rumors have always been a feature of the human response to disaster as people come together to try to make sense of an imperfect information space under conditions on high anxiety and high uncertainty. Indeed, though rumoring is often stigmatized and associated with the spread of misinformation, the act of rumoring may serve an important purpose for a community trying to come to terms with a disruptive event. Within this view, rumors can be false or they can turn out to be true or partially true. This conceptualization differentiates between “rumoring” and the intentional spread of misinformation or disinformation. However, the latter types are also an important part of the information space surrounding disaster events. Misinformation can be defined as factually false information that spreads accidentally or intentionally for non-malicious purposes. We see this on social media, for example in repurposed photos (e.g. sharks swimming through flood waters) that are spread with the 27 N.O. Tippenhauer, C. Pöpper, K.B. Rasmussen, and S. Čapkun, 2011, On the Requirements for Successful GPS Spoofing Attacks, CCS ‘11 Proceedings of the 18th ACM conference on Computer and communications security, 75-86. PREPUBLICATION COPY – SUBJECT TO FURTHER EDITORIAL CORRECTION 51

motivation, perhaps, of gaining visibility and followers for a social media account. Disinformation includes false or misleading information purposefully spread to mislead or confuse others—possibly for malicious purposes.2 Disinformation represents a particularly insidious threat, especially in connected information environments where malicious actors from outside of the affected area may try to interfere with response efforts or intentionally manipulate behavior to put people into harm’s way. Though rumors (and misinformation and disinformation) existed before the Internet, online systems and especially social media have altered the scale of rumoring after disaster events. More people participate—including people from places that are remote from the affected area. Social media features such as the retweet button on Twitter or the share button on Facebook allow people to quickly and easily pass along information—often before they check on the validity of the information or the credibility or its source. These online sharing practices generate information cascades, as information (including rumors) quickly spreads through these large, inter-connected, global networks. Due to the de-contextualization of online content—i.e. the loss of clear connection to its original source, including when and where it was published and by whom—it can be difficult to assess the credibility of this kind of information as it spreads. Further complicating this issue, research suggests that posts that promote false rumors are much more likely to be spread than posts that correct false rumors.3 Additionally, after rumors are corrected and/or fade away, they occasionally resurface (sometimes years later) and begin to spread anew. This means that, despite early praise of the “self-correcting crowd,” online platforms are much better at facilitating the spread of rumors than at correcting or debunking them. Research suggests that emergency responders who choose to engage online do see the correction of rumors and misinformation as a component of their job.4 Many spend time monitoring social media for rumors and challenging and/or correcting them. Though there have been arguments that citizens are either unable to identify credible messages from authorities and/or that citizens have active distrust of some official response organizations, preliminary research has demonstrated that rapid corrections to online rumors by official accounts can help to dampen and even stop the propagation of rumors.5 However, practices for correcting rumors are still dynamic and largely improvised. More research is needed to determine the best strategies—e.g. who should correct, how, and when. Considering the goal here of informing emergency alerting practices, responders should be encouraged to monitor social media and other online sources to identify and address rumors, misinformation and disinformation that could impact the affected community and response efforts within that community. If community members are receiving their information from these channels, then responders and other information mediators should assume an active role in curating this content, and research provides some evidence to support the ability for official responders to play a productive role. Responders should also be encouraged to develop protocols for using social media and other outlets to address rumors, misinformation and disinformation as quickly as possible though with intentionality that aligns with community norms and expectations within these environments. As those norms and expectations are still evolving, it is important to continue gathering data about and conducting research on the use of these platforms during emergency events. Recently, discussions about the presence and implications of “fake news” have sparked conversations about educational interventions to help people become better consumers of online content. Considering the emergency response context, there may be opportunity to do educational outreach to help people identify credible and trustworthy sources both before and during emergency events. Research is needed to identify the best approaches for this kind of intervention. 1 L. Plotnick and S.R. Hiltz, 2016, Barriers to Use of Social Media by Emergency Managers, Journal of Homeland Security and Emergency Management 13(2): 247-277. 2 C.B. Schenk and D.C. Sicker, 2011, Finding Event-Specific Influencers in Dynamic Social Networks, 2011 IEEE Third International Conference on Privacy, Security, Risk and Trust and 2011 IEEE Third International Conference on Social Computing 501-504. PREPUBLICATION COPY – SUBJECT TO FURTHER EDITORIAL CORRECTION 52

3 K. Starbird, J. Maddock, M. Orand, P. Achterman, and R.M. Mason, 2014, Rumors, False Flags, and Digital Vigilantes: Misinformation on Twitter after the 2013 Boston Marathon Bombing, iConference 2014 Proceedings 654-662. 4 A.L. Hughes and L. Palen, 2012, The evolving role of the public information officer: An examination of social media in emergency management, Journal of Homeland Security and Emergency Management 9(1): 1-20. 5 C. Andrews, E. Fichet, Y. Ding, E.S. Spiro, and K. Starbird, 2016, Keeping Up with the Tweet-Dashians: The Impact of ‘Official’ Accounts on Online Rumoring, Proceedings of the 19th ACM Conference on Computer- Supported Cooperative Work & Social Computing (CSCW 2016) 452-456. PREPUBLICATION COPY – SUBJECT TO FURTHER EDITORIAL CORRECTION 53

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Following a series of natural disasters, including Hurricane Katrina, that revealed shortcomings in the nation’s ability to effectively alert populations at risk, Congress passed the Warning, Alert, and Response Network (WARN) Act in 2006. Today, new technologies such as smart phones and social media platforms offer new ways to communicate with the public, and the information ecosystem is much broader, including additional official channels, such as government social media accounts, opt-in short message service (SMS)-based alerting systems, and reverse 911 systems; less official channels, such as main stream media outlets and weather applications on connected devices; and unofficial channels, such as first person reports via social media. Traditional media have also taken advantage of these new tools, including their own mobile applications to extend their reach of beyond broadcast radio, television, and cable. Furthermore, private companies have begun to take advantage of the large amounts of data about users they possess to detect events and provide alerts and warnings and other hazard-related information to their users.

More than 60 years of research on the public response to alerts and warnings has yielded many insights about how people respond to information that they are at risk and the circumstances under which they are most likely to take appropriate protective action. Some, but not all, of these results have been used to inform the design and operation of alert and warning systems, and new insights continue to emerge. Emergency Alert and Warning Systems reviews the results of past research, considers new possibilities for realizing more effective alert and warning4 systems, explores how a more effective national alert and warning system might be created and some of the gaps in our present knowledge, and sets forth a research agenda to advance the nation’s alert and warning capabilities.

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