In 2014, the RAND National Defense Research Institute published Data_Flood: Helping the Navy Address the Rising Tide of Sensor Information, a report focusing on the overwhelming amount of data an intelligence analyst must filter through as a result of the ever-increasing number of intelligence, surveillance, and reconnaissance sensors. “Common wisdom among analysts is that they spend 80 percent of their time looking for the right data and only 20 percent of their time looking at the right data,” the report notes.1 In 2020, speed and scope of data collection has never been greater, and the insatiable demand for accurate, timely intelligence analysis persists. If naval intelligence is to remain relevant and deliver penetrating insight and decision advantage against great power competitors, it must improve data analytics and invert the 80/20 paradigm.
1. Isaac R. Porche III, Bradley Wilson, Erin-Elizabeth Johnson, Shane Tierney, Evan Saltzman, “Data_Flood: Helping the Navy Address the Rising Tide of Sensor Information,” (RAND: 7 April 2014), www.rand.org/content/dam/rand/pubs/research_reports/RR300/RR315/RAND_RR315.pdf.
2. Bernard Marr, “What is the Difference Between Artificial Intelligence and Machine Learning?” Forbes, 6 December 2016, www.forbes.com/sites/bernardmarr/2016/12/06/what-is-the-difference-between-artificial-intelligence-and-machine-learning/#163608232742.
3. Marr, “What is the Difference Between Artificial Intelligence and Machine Learning?”
4. Arvin Hsu, “Deep Learning vs. Machine Learning for Business Outcomes: A Data Scientist’s Perspective,” insideBIGDATA, 27 October 2017, https://insidebigdata.com/2017/10/27/deep-learning-vs-machine-learning-business-outcomes-data-scientists-perspective/.
5. Arvin Hsu, “Deep Learning.”
6. ADM Scott H. Swift, USN, “A Fleet Must Be Able to Fight,” U.S. Naval Institute Proceedings 144, no. 5 (May 2018).
7. Cynthia M. Grabo, Anticipating Surprise: Analysis for Strategic Warning (Lanham, MD: University Press of America, 2004).
8. Michael Brett, George Duchak, Anup Ghosh, Kristin Sharp, “Artificial Intelligence for Cybersecurity: Technological and Ethical Implications,” panel, George Washington University Center for Cyber & Homeland Security 8 November 2017, https://cchs.gwu.edu/sites/g/files/zaxdzs2371/f/downloads/Fall%202017%20DT%20symposium%20compendium.pdf.
9. “Intelligence Community Information Environment (IC IE) Data Strategy,” www.dni.gov/files/documents/CIO/Data-Strategy_2017-2021_Final.pdf.
10. Department of the Navy Chief Information Officer, “Department of the Navy Strategy for Data and Analytics Computation,” 15 September 2017.
11. Director of National Intelligence, “The AIM Initiative – A Strategy for Augmenting Intelligence Using Machines,” 16 January 2019.
12. James E. McPherson, “Designation of the Department of the Navy Deputy Chief lnformation Officer (Navy) and the Department of the Navy Deputy Chief Information Officer (Marine Corps),” 30 April 2020.
13. Aaron Mehta, “DoD Stands up its Artificial Intelligence Hub,” C4ISRNet, 29 June 2018, www.c4isrnet.com/it-networks/2018/06/29/dod-stands-up-its-artificial-intelligence-hub/.
14. Defense Advanced Research Project Agency, “AI Next Campaign,” 19 July 2020, www.darpa.mil/work-with-us/ai-next-campaign.
15. Jack Corrigan, “IARPA is Investing in AI That Constantly Analyzes Worldwide Satellite Images,” NextGov, 16 April 2019, www.nextgov.com/emerging-tech/2019/04/iarpa-investing-ai-constantly-analyzes-worldwide-satellite-images/156335/.
16. Office of Naval Intelligence, “Nimitz Operational Intelligence Center,” 20 July 2020, www.oni.navy.mil/This-is-ONI/Who-We-Are/Nimitz/.
17. Megan Eckstein, “New Cyber Office Will Unify NAVSEA’s Digital Efforts,” USNI News, 27 May 2020, https://news.usni.org/2020/05/27/new-cyber-office-will-unify-navseas-digital-efforts.
18. Matthew Schehl, “NPS Launches Interdisciplinary Data Science and Analytics Group,” Naval Postgraduate School, 2 July 2018, https://my.nps.edu/-/nps-launches-interdisciplinary-data-science-and-analytics-group.
19. CAPT Dale Rielage, USN, “Building Human-Machine Dream Teams,” U.S. Naval Institute Proceedings 143, no. 5 (May 2017), www.usni.org/magazines/proceedings/2017-05/build-human-machine-dream-teams.
20. Julian E. Barnes and Josh Chin, “The New Arms Race in AI,” Wall Street Journal, 2 March 2018, www.wsj.com/articles/the-new-arms-race-in-ai-1520009261.
21. Justin Lynch, “Why Project Maven Is a ‘Moral Hazard’ for Google,” C4ISRNet, 26 June 2018, www.c4isrnet.com/it-networks/2018/06/26/why-googles-project-maven-pullout-is-a-moral-hazard/.
22 Samuel Bendett, “In AI, Russia Is Hustling to Catch Up,” Defense One, 4 April 2018, www.defenseone.com/ideas/2018/04/russia-races-forward-ai-development/147178/.
23. Statista, “Artificial intelligence (AI) funding investment in the United States from 2011 to 2019,” statista.com, www.statista.com/statistics/672712/ai-funding-united-states/.