Issues Faced by Open Source Intelligence

Introduction/Synopsis
Big Data is driving virtually every industry in today’s Digital Age, including, among all others, the work of the Intelligence community. From human intelligence (HUMINT) to open source intelligence (OSINT), “strategic intelligence as a professional discipline and force multiplier” has evolved from centering on “qualitative subject-matter content analyzed by human specialists” to leveraging “the increasingly massive collection and machine analysis of quantifiable, if not necessarily quantitative, data.”[footnoteRef:2] However, as Richard Best, Specialist in National Defense, Foreign Affairs, Defense and Trade Division, testified before Congress in 2006, OSINT, which is primarily derived from old and new media publications, including social media, lacks a systematic manner in which such data can be incorporated into or used to supplement classified information.[footnoteRef:3] As Best notes, “a consensus now exists that OSINT must be systematically collected and should constitute an essential component of analytical products.”[footnoteRef:4] The main challenge is that among the community itself, a systematic approach has not yet been adopted and the Director of National Intelligence has not taken sufficient steps to exploit OSINT to its maximum potential. How to better incorporate OSINT into strategic decision making within the intelligence community is a major issue that has to be discussed in more detail so that U.S. intelligence can be better fortified by making the utmost use of all available information. [2: Kevjn Lim, "Big data and strategic intelligence." Intelligence and National Security 31, no. 4 (2016), 620.] [3: Richard Best, Open Source Intelligence (OSINT): Issues for Congress, 2007, 2.] [4: Ibid 2.]
Background/Problems
While OSINT and HUMINT are recognized as the “most democratic intelligence disciplines,”[footnoteRef:5] they are also the most common. The fact that virtually every intelligence agency collects OSINT, however, means that there one of the major problems surrounding OSINT is tied to “duplicative efforts, wasted resources, and often budget competition that promoted information hoarding rather than information sharing.”[footnoteRef:6] There is also another challenge with respect to OSINT. As OSINT is the source of first resort (since it is so readily and broadly available), OSINT has a long history in intelligence gathering. The collection of this data, though, must be legal and lawful—and with so much data now being posted and shared via social media, a gray line exists as to whether such information is public or private and whether intelligence agencies should have lawful access to social media platforms for the purposes of collecting OSINT.[footnoteRef:7] Since the War on Terror, terror cells have used social media to relay information via the Internet to members around the world. Their ability to organize is viewed as one of their greatest strengths.[footnoteRef:8] In an effort to more effectively monitor such organized networks, intelligence agencies need to be able to see what information is being exchanged via social media. Yet, as Lowenthal and Clark note, this is an issue because if a profile is set to Private it cannot be accessed under the normal procedures of OSINT: “For example, an individual’s Facebook profile can be considered publicly available if it is wide open. However, should the individual choose to restrict their profile to “friends only,” then the profile is no longer publicly available. Any actions then to obtain access, such as sending the individual a friend request or attempting to hack their Facebook account, falls outside the scope of OSINT.”[footnoteRef:9] Thus the two main challenges related to OSINT are 1) the need for a systematized way in which the various intelligence agencies can collaboratively collect and share OSINT, and 2) the need for the intelligence community to combine OSINT with HUMINT with respect to “friending” individuals on social media so as to have access to private information—or else finding a legal means of procuring data from a private profile in a timely and systematized manner. A third problem also exists, which is the sheer scope and size of data available that must be processed by OSINT. The arrival of Big Data has presented its own unique challenges, which are as much related to information technology systems as they are to data collection and intelligence. [5: Mark M. Lowenthal and Robert M. Clark, eds, The five disciplines of intelligence collection (Sage, 2015), 23] [6: Ibid 23.] [7: Ibid 29] [8: Amy B. Zegart, "September 11 and the adaptation failure of US intelligence agencies." International Security 29, no. 4 (2005), 78.] [9: Mark M. Lowenthal and Robert M. Clark, eds, The five disciplines of intelligence collection (Sage, 2015), 29.]
Solution
The proposed solutions to these challenges are: 1) a systematized method should be developed and implemented by the intelligence community with regard to collecting OSINT; 2) OSINT operations should pair with HUMINT operations in order to negotiate the social media field; and 3) OSINT officers should pair IT personnel to develop and implement an effective method for screening and processing Big Data.
Pros
The pros of these solutions are that: 1) it enables better cohesion, collaboration, and information-sharing among the various intelligence agencies and eliminates duplication of efforts and waste of resources; 2) it allows for OSINT to be collected from profiles that would be publicly-accessible were it not for the preferences of some social media users to have a curtain of privacy in front of their social media posts; 3) it assists in the efficient and effective use of Big Data for the purposes of developing a more robust OSINT approach.
Cons
The cons of these solutions are that 1) collaboration and information-sharing among the intelligence agencies has never been a top priority in the intelligence community, as the various agencies often have competing aims and interests—so this solution is not as feasible or as practical as it sounds; 2) going beyond the scope of OSINT to actively seek to engage social media users so as to access their private information involves a degree of cyber HUMINT, which could lead to overlap and role confusion among intelligence officers; 3) to process Big Data effectively, OSINT officers must also work closely with IT developers to find effective ways of processing OSINT and distilling from the pool of Big Data the most essential sequences of information—which is easier said than done. As Krasner and Zegart show, “the national security landscape for the foreseeable future will be marked by unprecedented uncertainty. New threats are emerging and old threats are evolving at speeds unknown in earlier eras.”[footnoteRef:10] To get the most out of OSINT, new approaches and methods must constantly be employed, and this could absorb a great deal of time, energy and resources. [10: Amy Zegart and Stephen D. Krasner, eds., “Pragmatic Engagement amidst Global Uncertainty: Three Major Challenges,” Hoover Institution, 2015, 12]
Conclusion: Optimal Solution
The best solution going forward is to combine OSINT with HUMINT when searching social media for information and to develop an approach to OSINT that the intelligence community overall can agree to share. IT developers should also be sought to help develop a better method of processing Big Data so as to facilitate OSINT collection.
References
Best, Richard. Open Source Intelligence (OSINT): Issues for Congress. Washington,
DC, 2007.
Lim, Kevjn. "Big data and strategic intelligence." Intelligence and National Security 31,
no. 4 (2016): 619-635.
Lowenthal, Mark M., and Robert M. Clark, eds. The five disciplines of intelligence
collection. Sage, 2015.
Zegart, Amy B. "September 11 and the adaptation failure of US intelligence agencies." 
International Security 29, no. 4 (2005): 78-111.
Zegart and Stephen D. Krasner, eds. “Pragmatic Engagement amidst Global Uncertainty:
Three Major Challenges,” Hoover Institution, 2015.