In the United States, the Intelligence Community provides valuable information to the US government and military branches to improve national security. The accuracy and reliability of their information is of key concern, and the community is constantly seeking to advance its capabilities in terms of information gathering. One area of exploration is through Open Innovation. Often the most critical issues at hand for intelligence agencies involve assessing human behavior. Either they must find and evaluate pertinent information which is otherwise hidden from the general public, such as identifying a potential \u201clone-wolf\u201d terror attack [1] [2], or they must interpret some broad social intuition that may not be evident at an individual scale, a \u201cwisdom of the crowd\u201d such as estimating refugee flows in Syria [3]. Each of these situations represents an extremely difficult challenge for a single expert assigned to the task. Either the expert is searching for a needle in a hay stack or they cannot see the forest for the trees. Crowdsourcing, or Open Innovation, where numerous human perspectives are gathered to construct are cohesive theory, offers a potential solution for the expert. With many new perspectives, there are many new eyes, making finding critical and rare information more likely while also providing a better sense of broader geopolitical trends that any one individual may otherwise miss. IARPA is an organization seeking to fill this gap [4] [5].<\/p>\n
Intelligence Advanced Research Project Activity (IARPA) is a government organization that researches new technology and processes for the Intelligence Community in the United States. In 2018, it conducted a $200,000 contest for demonstrating geopolitical forecasting through open source information gathering [6]. The idea was that despite having extremely well-educated and trained agents, who have been analyzing geopolitical trends for years, intelligence agencies\u2019 ability to predict future outcomes was simply worse than the capability of a collective of untrained, average citizens. In an unexpected outcome, by assembling the relatively uniformed opinions of a broad collection of people, more accurate conclusions could be achieved than by relying on experts alone. This proof of concept could serve to enhance the predictive capability of intelligence agencies in our world immediately.<\/p>\n
Another area where IARPA has considered open innovation is in counter-terrorism [7]. The modern face of terrorism has moved away from traditional organizations that plot and organize attacks as a cohesive unit. Instead it has been replaced by a so called \u201clone-wolf\u201d terrorism, where the attacker does not have direct interaction with the terrorist organization itself, but instead sympathizes with the organization\u2019s goals and ideologies, prompting an independent attack [8]. This new form of terrorism is significantly more difficult to find and trace, as it often appears sporadically, while also distributed throughout the nation. However, there may be warning signs of this behavior as it develops over time at an individual level. Crowdsourcing this information to a national reporting channel could increase awareness of these possible threats for further assessment. Similar to the Waze app [9], where map editors report traffic or construction concerns on the roadways, concerned citizens could report suspicious behavior in order to assess potential threats to national security. This application of crowdsourcing is likely not to be adopted in the immediate future, for the following reasons:<\/p>\n
Each of these applications of open innovation logically presents several challenges, which must be addressed by the Intelligence Community to achieve successful results. In both applications presented, there is a question of how to go about motivating a collective of individuals to participate in these crowdsourcing activities. For the Waze app, there is a direct product (navigation capability) which benefits from the user input and then benefits the user directly as well. However, with a public service like national security, this relationship is much less direct. What incentive does a citizen have to commit time to these crowdsourcing activities when the effects are not immediately observed? This incentive problem must be addressed, perhaps by formalizing the structure of these activities through direct financial compensation for forecasting efforts. To improve participation in the Crime Stoppers-like [10] crowdsourcing counter-terrorism initiative, a points system has been proposed where participants are rewarded for actively contributing to the proposed information sharing platform. However, what are the implications of this rewards system? From a cynical view, one might imagine a collective of children-spies, like those in 1984<\/em>, [11] seeking to report any suspicious activity to gain points. In context, a lack of trust in government agencies has also eroded the likelihood of adoption for this counter-terrorism application [12]. Perhaps this is not the best point in history for this innovation to succeed, and a longer timeline for adoption should be pursued.<\/p>\n What other public services could be improved with crowdsourced information gathering? What concerns do you have with intelligence agencies using crowdsourced data?<\/p>\n (Word Count: 793)<\/p>\n [1] [7] [8] [12] Coultas, Bryan T. \u201cCrowdsourcing Intelligence to Combat Terrorism: Harnessing Bottom-up Collection to Prevent Lone-Wolf Terror Attacks\u201d Thesis, Naval Postgraduate School, 2015, http:\/\/www.dtic.mil\/dtic\/tr\/fulltext\/u2\/a620622.pdf<\/a><\/p>\n [2] Vallone, Julie. \u201cCrowdsourcing Could Predict Terror Strikes, Gasoline Prices Netflix Was Early Adopter Researchers test system for gathering opinions on world events and trends.\u201d Investor’s Business Daily, Investor’s Business Daily, Inc., 29 Aug 2011, http:\/\/search.proquest.com.ezp-prod1.hul.harvard.edu\/docview\/915163452?accountid=11311<\/a><\/p>\n [3] Spiegel, Alix. \u201cSo You Think You’re Smarter Than A CIA Agent.\u201d NPR, NPR, 2 Apr. 2014, www.npr.org\/sections\/parallels\/2014\/04\/02\/297839429\/-so-you-think-youre-smarter-than-a-cia-agent<\/a><\/p>\n [4] Weinberger, Sharon. \u201cFuture – Intelligence Agencies Turn to Crowdsourcing.\u201d BBC News, BBC, 18 Nov. 2014, www.bbc.com\/future\/story\/20121009-for-all-of-our-eyes-only<\/a><\/p>\n [5] Hershkovitz, Shay. \u201cThe Future of Crowdsourcing: Integrating Humans with Machines.\u201d TheHill, The Hill, 20 Mar. 2017, thehill.com\/blogs\/pundits-blog\/technology\/324807-the-future-of-crowdsourcing-integrating-humans-with-machines<\/u><\/a><\/p>\n [6] \u201cIntelligence Community Looking At Crowdsourcing For Predicting Geopolitical Events.\u201d NPR, NPR, 26 Jan. 2018, www.npr.org\/2018\/01\/26\/581142439\/intelligence-community-looking-at-crowdsourcing-for-predicting-geopolitical-even<\/a><\/p>\n [9] Del-Colle, Andrew. \u201cInside Waze’s Volunteer Workforce.\u201d Popular Mechanics, Popular Mechanics, 14 Nov. 2017, www.popularmechanics.com\/technology\/a15624\/waze-volunteer-work-force\/<\/a><\/p>\n