Naval Intelligence Topic Week

By Stephen L. Dorton & Samantha Harper

With a combination of legitimate potential and hype, artificial intelligence and machine learning (AI/ML) technologies are often considered the future of naval intelligence. More specifically, AI/ML technologies promise to not only increase the speed of analysis, but also deepen the quality of insights generated from large datasets.¹ One can readily imagine numerous applications for AI/ML in naval intelligence at tactical, operational, and strategic levels: threat detection and tipping and cueing from signals intelligence (SIGINT) or electronic intelligence (ELINT), target classification with acoustic intelligence (ACINT) or imagery intelligence, using AI/ML to predict enemy movements for anti-submarine warfare, and many others.

The government, industrial, and academic sectors will continue to work fervently on challenges such as data collection, preprocessing, and storage, the development of better algorithms, and the development of infrastructure for storage and compute resources. However, even the best performing AI/ML technologies are moot if the analyst or downstream decision maker cannot trust the outputs. Given the gravity of decisions driven by naval intelligence, AI/ML outputs must be readily interpretable, and not only provide the what, but the why (i.e. why the answer is what it is) and the how (i.e. how specifically the AI/ML arrived at the answer). 

The Challenge: Trust in AI

To illustrate this challenge, consider the following hypothetical scenario: a watch supervisor on an aircraft carrier is doing pre-deployment qualifications off the coast of Virginia. After making a brief head call they come back to find out that one of their junior watchstanders has reported a dangerous, but unlikely, aerial threat to the Tactical Action Officer (TAO). After nearly putting the ship in general quarters, the TAO realized that based on the operating area, the considerable range from the threat, and other intelligence on the threat’s location, it was impossible for that threat to be there. Further inspection shows that the AI/ML in the system was programmed to automatically classify tracks as the most dangerous possible entity that could not be ruled out, but the junior watchstander was unaware of this setting. Unfortunately, the AI/ML did not explain why it classified the track as a high threat contact, nor did it explain what signatures or parameters it considered, nor how it generated a list of possible tracks, so the junior watchstander made a bad call based on an incomplete understanding of the AI system.

The problem is that this is not a purely hypothetical scenario, but is a real event that happened several years ago, as recounted during an ongoing study to investigate the role of trust and AI/ML in intelligence. While one may easily dismiss this and say “no harm, no foul,” that would be myopic. First, if this same scenario happened in contested waters or with a less experienced TAO, there could have been serious ramifications (such as another Vincennes incident, in which an Iranian airliner was shot down by a U.S. Navy cruiser). Second, this “boy who cried wolf” scenario caused the TAO to lose trust in the watchstander, the supervisor, and the entire section. Not only was the watchstander afraid to make decisive calls after the event, but it took nearly half of the deployment making correct calls and answering requests for information to regain the trust of the TAO. This lack of trust might have caused the TAO to hesitate to act on their reports if a real threat were to be identified. These kinds of delays and second guessing can cost lives.

This example highlights another dimension to the challenge facing employment of AI/ML in naval intelligence. The goal is not to simply develop systems that sailors and analysts trust as much as possible. Having too much trust in AI/ML can result in misuse of the system (e.g. immediately accepting its outputs without considering the other available intelligence). Conversely, having too little trust can result in disuse of the system (missing out on genuine benefits of the system). Therefore, the pressing challenge for the future of naval intelligence is to develop AI/ML capabilities that allow operators to rapidly develop and calibrate their trust to appropriate levels in the right contexts and scenarios, the same way they would with their human teammates.

What is Trust? What Affects It?

The experimental psychology community has studied trust for years, defining it as “the attitude that an agent will help achieve an individual’s goals in a situation characterized by uncertainty and vulnerability.”² In other words, trust is the degree to which one is willing to make oneself vulnerable, or put oneself in the hands of another agent (e.g. a person, or an AI/ML system). It is critical to understand what makes people gain or lose trust, as trust greatly impacts the adoption of new systems, and can make or break the performance in a human-machine team. This is especially challenging in the context of naval intelligence, where uncertainty and vulnerability are always present.

Designing AI/ML systems to engender trust is a complicated affair, due in no small part to what a complex and highly-dimensional phenomenon trust is. There are roughly a dozen factors that affect trust, including the following:³

• Reputation: The AI/ML has received endorsement or reviews from others. 
• Usability: The AI/ML is easy to interact with.
• Predictability: The ability to predict the actions of the AI/ML.
• Security: The importance of operational safety and data security to the AI/ML.
• Utility: The usefulness of the AI/ML in a task.
• Goal Congruence: The extent to which the AI/ML’s goals align with the user.
• Reliability: The AI/ML is reliable and consistent in functioning over time.
• Understandability/Explainability/Feedback: The extent to which one can understand what the AI/ML is doing, why it is doing it, and how it is doing it, either implicitly or explicitly.
• Trialability: There is opportunity to interact with the AI/ML prior to accepting or adopting it for operational use.
• Job Replacement: There is concern about the AI/ML taking one’s job.
• Errors/ False Alarms: Information provided by the AI/ML does not contain errors or false alarms.

A Naturalistic Study of Trust, AI, and Naval Intelligence: Early Findings

We are currently conducting a study to test the factors and better understand how trust is gained or lost in the context of naval intelligence, using a naturalistic decision making approach. Naturalistic decision making is the study of how people use their experiences in naturalistic settings, rather than in a controlled laboratory environment.⁴ This approach allows us to understand how these factors affect trust and decision making in the chaos of real world operations, complicated by missing information and time pressure.

More specifically, we used the Critical Incident Technique, a structured and repeatable means to collect data on prior incidents to solve practical problems.⁵ We recruited participants who had experience in intelligence, including planning, collection, analysis, or even military decision making as an active consumer of intelligence. Those in naval intelligence had experience in different intelligence fields, including ACINT, SIGINT, ELINT, GEOINT, and all-source intelligence, although most of their experiences were in tactical intelligence or operations using AI/ML that exploits intelligence. 

Participants were asked to identify an AI/ML technology they worked with in the context of intelligence, and then to think of any defining event (or series of events) that made them gain or lose trust in that technology. This resulted in a sample of nine stories about trust in AI/ML in the context of naval intelligence: four about gaining trust, and five about losing trust. These stories were similar to the earlier story about the junior watchstander reporting an impossible threat. A research team coded each story for the presence or absence of each trust factor, allowing insights to be gained from the data. So, what factors affected trust in AI/ML in naval intelligence?

Explainability and Utility are Paramount

Understandability/Explainability/Feedback was the most common factor in gaining or losing trust, which was found in eight of the nine examples. It was present in all five stories about losing trust, where a lack of explainability manifested itself in multiple ways. A lack of understanding how the AI/ML generated results prevented the captain of a ship from knowing if they could safely override navigation recommendations from a GEOINT tool. In another case, it prevented search and rescue planners from even knowing if there were errors or limitations in another GEOINT product: “they put garbage in and got garbage out… but our people didn’t understand the theory behind what the machine was doing, so they couldn’t find [the] errors [in the first place].” In stories about gaining trust, analysts said that understanding the underlying algorithms enabled them to trust the AI/ML, because even when the outputs were wrong, they knew why. This knowledge enabled a SIGINT collector to adapt their workflow based on their understanding of the strengths and weaknesses of their AI/ML system, capitalizing on its strengths (as a tipper) and mitigating its weaknesses (as a classifier), “ultimately I was happy with the system… it gave me good enough advice as a tipper that a human could have missed.”

Utility, or the usefulness of the AI/ML in completing tasks, was the second-most commonly cited factor in gaining or losing trust. It was present in three stories about gaining trust, and three stories about losing trust. Ultimately, if the AI/ML helps someone do their job successfully, then it is trusted, and the inverse is true if it makes success more difficult. As an all-source analyst said of one of their AI/ML tools, “it’s an essential part of my job… if I can’t use this tool it’s a mission failure for me.” Conversely, another all-source analyst lost trust in an AI/ML tool because its capabilities were so limited that it did not help them complete their tasking, “When I first heard of it I thought it was going to be useful… then I learned it was built on bad assumptions… then I saw the answers [it produced]…”

Other Findings and Factors

Reputation, or the endorsement from others was cited in half of the stories about gaining trust, but never as a factor in losing trust. Because of the immense interpersonal trust required in naval intelligence, endorsement from another analyst can carry significant weight, “the team was already using the tool and I trusted the team I was joining… that made me trust the tool a bit before even using it.” Interestingly, predictability of the AI/ML was not cited as a factor in gaining or losing trust. One participant seemed to explain that the operational domain is rife with uncertainty, so one cannot expect predictability in an inherently unpredictable environment, “I’m smart enough to know that the [AI/ML tools] are taking data and making estimates… the nature of submarine warfare is dealing with ambiguous information…” 

Finally, errors and false alarms were cited in three of the five stories with a loss of trust in AI/ML, but were never cited as factors for gaining trust. It seems plausible that this may be because a lack of errors may manifest itself as utility or reliability (it functions consistently over time), or it could be because of the previous sentiment: there will always be errors in an inherently uncertain domain such as naval intelligence, so there is no reasonable expectation of error-free AI/ML.

Conclusions

AI/ML tools will become more ubiquitous in naval intelligence across a wide variety of applications. Several factors affect trust in AI/ML, and some naturalistic investigation identified factors, such as explainability and utility, that play a role in gaining or losing trust in these systems. Appropriately calibrated trust, based on an understanding of the capabilities and limitations of AI/ML, is critical. Even in cases where the AI/ML does not produce a correct answer, operators will adapt their workflows and reasoning processes to use it for the limited cases or tasks for which they do trust it. 

Unfortunately, AI/ML capabilities are often developed with good intentions, but fall into disuse and fail to provide value if they do not consider the human element of analysis. Analyst reasoning and sensemaking is one such component of the human element,⁶ but trust is another component that must be considered in the development of these systems, particularly in regard to explainability. Greatly complicating the matter of trust, but not addressed adequately yet, is that AI/ML can be deceived.⁷ Our potential adversaries are well aware of this weakness, so developing an understanding of how our AI/ML systems can be deceived and ultimately protected from deception is crucial.

If an analyst were asked how they arrived at their findings and their response was simply “.79” the commander would likely not trust their findings enough to make a high-stakes decision from them, so why would that be acceptable output from AI/ML? Developing trustable AI/ML technologies is one of the greatest challenges facing the future of naval intelligence.

Steve Dorton is a Human Factors Scientist and the Director of Sonalysts’ Human-Autonomy Interaction Laboratory. He has spent the last decade conducting RDT&E of complex human-machine systems for the Navy and other sponsors. More recently, his research has focused on human interactions with AI/ML and applying crowdsourcing in the context of intelligence analysis.  

Samantha Harper is a Human Factors Engineer in Sonalysts’ Human-Autonomy Interaction Laboratory, who has experience in the design, execution, analysis, and application of user-centered research across various technical domains, including intelligence analysis, natural language processing, undersea warfare, satellite command and control, and others.

Acknowledgments

This work was supported in part by the U.S. Army Combat Capabilities Development Command (DEVCOM) under Contract No.W56KGU-18-C-0045. The views, opinions, and/or findings contained in this report are those of the authors and should not be construed as an official Department of the Army position, policy, or decision unless so designated by other documentation. This document was approved for public release on 10 March 2021, Item No. A143.

Endnotes

[1] McNeese, N. J., Hoffman, R. R., McNeese, M. D., Patterson, E. S., Cooke, N. J., & Klein, G. (2015). The human factors of intelligence analysis. Proceedings of the Human Factors and Ergonomics Society 59th Annual Meeting, 59(1), 130-134.

[2] Lee, J. & See, K. (2004). Trust in Automation: Designing for Appropriate Reliance. Human Factors, 46, 50-80. 10.1518/hfes.46.1.50.30392. 

[3] Siau, K. & Wang, W. (2018). Building trust in artificial intelligence, machine learning, and robotics. Cutter Business Technology Journal, 31, 2. 

Muir, B. M. (1994). Trust in automation: Part I. Theoretical issues in the study of trust and human intervention in automated systems. Ergonomics, 37(11), 1905-1922.

Rempel, J. K., Holmes, J. G., & Zanna, M. P. (1985). Trust in close relationships. Journal of Personality and Social Psychology, 49(1), 95–112. https://doi.org/10.1037/0022-3514.49.1.95. 

Balfe, N., Sharples, S., & Wilson, J. R. (2018). Understanding is key: An analysis of factors pertaining to trust in a real-world automation system. Human Factors, 60(4), 477–495. 

Hoff, K. A., & Bashir, M. (2015). Trust in automation: Integrating empirical evidence on factors that influence trust. Human Factors, 57(3), 407–434.

[4] Klein, G. (2017). Sources of Power: How People Make Decisions (20th Anniversary Edition). Cambridge, MA: MIT Press.

[5] Flanagan, J.C. (1954). The Critical Incident Technique. Psychological Bulletin, 5, 327-358. doi: http://dx.doi.org/10.1037/h0061470

[6] Moon, B. M. & Hoffman, R. R. (2005). How might “transformational” technologies and concepts be barriers to sensemaking in intelligence analysis, Proceedings of the Seventh International Naturalistic Decision Making Conference, J. M. C. Schraagen (Ed.), Amsterdam, The Netherlands, June 2005.

[7] Brennan, M. & Greenstadt, R. (2009). Practical attacks against authorship recognition techniques. Proceedings of the Twenty-First Innovative Applications of Artificial Intelligence Conference, 60-65.

Featured image: Lt. Jon Bielar, and tactical action officer Lt. Paul O’Brien call general quarters from inside the combat information center during the total ship’s survivability exercise aboard the Ticonderoga-class guided-missile cruiser USS Antietam (CG 54).  (U.S. Navy photo by Mass Communication Specialist 3rd Class Walter M. Wayman/Released)

Naval Intelligence Topic Week

By Lieutenant Commander Gerie Palanca, USN

“The essential foundation of all naval tactics has been to attack effectively by means of superior concentration, and to do so first, either with longer-range weapons, an advantage of maneuver, or shrewd timing based on good scouting.”—Captain Wayne P. Hughes, U.S. Navy

Rear Admiral Michael McDevitt states in his 2020 Proceedings article that by 2035 the People’s Liberation Army Navy (PLAN) will have approximately 430 ships. Former Pacific Fleet Chief of Intelligence, Capt. (ret.) Jim Fanell called the span between 2020 and 2030 a “decade of concern” – Chinese Communist Party leaders likely assess 2030 as their last opportunity to militarily “reunite” Taiwan and mainland China. By that time the PLAN fleet will dwarf the estimated U.S. Navy fleet size of 355 ships. This imbalance in fleet size will likely embolden China’s regional efforts to deny American presence within the 9-dash line, China’s territorial claim in the South China Sea. By 2035, the PLAN will not only have a larger maritime force, but they will also procure anti-surface weapons and supporting capabilities that will either match or outshine U.S estimated capabilities. To characterize this scenario, the Congressional Research Service report on precision-guided munitions highlighted that the current anti-access/area denial weapon systems deployed along China’s coast and afloat outrange U.S. weapon systems, with ranges of almost 1000 nautical miles, creating a need for U.S. ships and aircraft to engage the adversary at longer ranges in order to maintain survivability. According to Fleet Tactics, increasing a weapon’s range squares the scouting (i.e. intelligence) requirement for that system.¹

This exponential growth in the need for scouting to support fires is underscored in the congressional report on intelligence, surveillance, and reconnaissance (ISR) design for great power competition (GPC). The report describes the need for a system that embraces disruptive technology and the importance of operational integration, specifically in the form of “sensor-to-shooter.” For the U.S. to maintain its information advantage and dominate in a long-range fight, the military will need to adopt an information warfare approach that is rapid enough to operate within the adversary’s decision cycle. To achieve this effectively, the U.S. will need to find, fix, and disseminate targets to the warfighter at a speed far greater than ever before.

In 2020, Vice Admiral White, Commander Fleet Cyber Command, emphasized that the Navy Information Warfare Community (NIWC), including the Naval Intelligence Community, must provide warfighting capabilities enabling precision long-range strike and the community must normalize these critical capabilities with urgency. GPC has added a dimension that has created a greater requirement to support the tactical decision makers executing these fires. With the adversary’s adoption of long-range weapons to combat U.S. carrier strike groups, the decision space and tempo of traditional ISR is obsolete. 

In the long-range fight, rapid, actionable, targetable information is now the center of gravity. For the NIWC to execute an ISR construct that supports this evolving nature of warfare effectively, the community will need to develop a tailored artificial intelligence (AI) capability. Scouting in support of maritime fires is a culture shift for the NIWC, but it is not the only change that needs to happen. For over a decade, NIWC has been primarily focused on either supporting the Global War on Terror and combating violent extremist organizations or tracking global civilian shipping. While these focused efforts have been immensely important, it is time for a pivot.

GPC with China may depart from previous examples, such as the Cold War, by resulting in an open conflict between great powers. An escalation with China would involve weapon systems that are designed to engage the adversary at greater than 1000 NM. This paradigm is not new, with the Navy’s reliance on the BGM-109 Tomahawk cruise missile since 1983, but future attacks against unplanned, mobile targets at that range, while at risk of the adversary’s long-range anti-ship ballistic and cruise missiles is an altogether novel and unfamiliar challenge.

To address this issue by 2035, the NIWC will need to regain information superiority. Rapid acquisition of realistic AI will be only one of many tools required to accomplish this. The NIWC will need swift development of doctrine and tactics, techniques, and procedures (TTPs) to execute AI-supported intelligence and modern support to precision long-range fires. Additionally, there will not be any need for new TTPs that do not address the high-end fight. The NIWC will need to support rapid acquisition of the capabilities it needs to fight tonight. 

Speed up the decision cycle by defining the role of the analyst in a world of mature AI

The director of the National Geospatial Intelligence Agency (NGA) stated that “if trends hold, intelligence organizations could soon need more than eight million imagery analysts to analyze the amount of data collected, which is more than five times the total number of people with top secret clearances in all of government.” The DoD noticed this trend and established the Joint AI Center to develop products across “operations intelligence fusion, joint all-domain command and control (JADC2), accelerated sensor-to-shooter timelines, autonomous and swarming systems, target development, and operations center workflows.” Under these architectures, AI is the only technological way that the IC, and NIWC, will be able to use all the data available to support the warfighter in precision long-range fires. 

AI is a force multiplier for the NIWC, and the integration of the technology is a matter of when, not if. The NIWC must identify the role of the operator and analyst when augmented with AI. According to the 2019 Deloitte article titled “The future of intelligence analysis,” the greatest benefit from automation and AI blooms when human workers use technology to increase how much value they bring to the fight. This newfound productivity allows analysts to spend more time performing tasks that have a greater benefit to the NIWC, instead of focusing on writing detailed intelligence reports or spending twelve hours creating a daily intelligence brief. If nurtured and trained now and over the next decade, by 2035 AI will have the ability to make timely, relevant and predictive briefs for commanders, freeing analysts to provide one of those most valuable analytical tools: recommendations.

Since AI is inextricably linked to the rapid analytic cycle required to enable long-range fires, the NIWC needs to determine the ideal end state of the analyst-AI relationship. One of the biggest misunderstandings about AI in the IC is the fear of losing the intelligence analyst. The opposite is more probable: the IC will fail to incorporate and use AI to its fullest potential to solve its hardest problems. As AI matures, the NIWC will need to integrate AI afloat and ashore to allow analysts to focus on tracking hard targets, elevating predictive analysis, and collaborating across the strike group and IC, while communicating the results effectively to the warfighter.

The advancement of AI alone will not ensure the NIWC’s success in conflict. The process and outputs of intelligence must be refocused to effectively enable fires and fully integrate into operations. The Navy and Air Force have also both heavily invested in the smart, network-enabled AGM-158 Long-Range Anti-Ship Missile and the Navy and Marine Corps have invested in the RGM-184 Naval Strike Missile. With the estimated flight times of these vehicles as a matter of minutes, coupled with their impressive ranges, target intelligence generated by non-organic sensors must get directly to the end user. The IC provides a majority of target intelligence to the warfighter and is woefully unprepared for this new paradigm. The IC needs to embrace a fully informed, holistic intelligence picture for the DoD to effectively execute a long-range fight in GPC. These advanced weapons also require machine speed intelligence to keep up with the timeline of engagement and the pace of dynamic targeting. Machine-to-machine systems are not new in the DoD, but AI is the avenue connecting those systems to modern missions. Because of traditional hurdles due to stovepipes and information security, the IC and DoD have the arduous chore of ensuring AI does not become an empty technology hindered by issues of classification and policy, ultimately minimizing the inputs into the algorithms. AI is also idealized as the savior of all hard intelligence problems. The NIWC needs to use AI for what it can actually do now. To that point, the IC is the key player in ensuring the NIWC has the data it needs to develop this capability.

Speed up the development of doctrine 

For the NIWC, operating alongside AI and supporting precision long-range fires are doctrine gaps. In GPC the most important intelligence will be actionable intelligence with the fight progressing at a tempo where information must be available directly to the shooter and provide confidence in the target within seconds to minutes. Not to mention, the target will most likely be well outside of any organic sensors of the distributed platforms. The NIWC is not famous for disseminating information within seconds to minutes directly to the warfighter, but the right doctrine will enable this construct. This doctrine must be developed rapidly, meet the needs of the future war, and be promulgated to the Fleet for feedback based on the environment. 

According to JP 1-02 DoD Dictionary of Military and Associated Terms, doctrine is the fundamental principle that guides the actions of military forces or elements thereof in support of national objectives. The national objectives in this case are decision superiority and LRF. These require a culture shift away from intelligence support to military operations towards intelligence-driven operations. This culture is not new. An example can be seen through the effectiveness of special operations forces (SOF). In the SOF community, intelligence is the foundation of the mission plan and deliberately phased execution. To tackle this modern adversary in a dynamic maritime environment, we need to adopt this culture. Within the SOF skillset, GWOT-type targets were time sensitive targets of opportunity. The intelligence team supporting these targets needed rapid processing and dissemination so the operators could engage on a compressed timeline. While cutting-edge technology played a part, the culture was the clear distinction from traditional intelligence operations. New doctrine needs to be developed to support and sustain this large culture shift within the NIWC for intelligence driving long-range fires.

In addition to a culture shift, pushing the authority to engage targets down to lower levels will enable the speed required for decision superiority and LRFs . The PROJECT CONVERGENCE exercise, the Army’s contribution to the JADC2 joint warfighting construct, highlighted that improvements must be made in mission command and command and control (C2) . These improvements can be technology-based, but many modifications can happen at the TTP and doctrine level. To make this possible, the NIWC will have to develop TTPs within battlespace awareness, assured C2, and integrated fires that inform, ensure, and synchronize mission command in precision long-range fires. Doctrine is how the NIWC will standardize this tradecraft, allowing ashore C2 and afloat mission command even in a contested environment. 

While these sound like simple changes, those in the doctrine community may not be comfortable with rapid doctrine development and dissemination, especially on topics that are continually evolving like intelligence collaboration with AI and IW support to precision long-range fires. The risk of incomplete and insufficient TTPs on nascent capabilities is real for the warfighter. Unfortunately, there are countless anecdotes of systems delivered to platforms without proper doctrine and training for the sailors to be able to use or integrate the systems into current operations. With the ability to win in a GPC fight hanging on the ability to rapidly integrate emerging and disruptive technology into present operations, the NIWC cannot operate without doctrine any longer nor can it wait for the archaic doctrine process to catch up.

Speed up the acquisition process 

VADM White prioritized delivering warfighting capabilities and effects as the third goal for Fleet Cyber Command. Specifically, delivering warfighting capabilities that enable movement, maneuver, and fires using emerging concepts and technologies. A rapid acquisition culture allowing for risks is the only way to achieve VADM White’s desire for persistent engagement that will allow the USN to compete during day to day operations, especially in support of holding the adversary at risk via long-range kinetic capabilities.² This concept raises a concern that speed should not be the only goal post. The NIWC needs to ensure that it buys what is needed for the future war. If it buys the programs that are in the process now, but faster, it might not actually solve any problems. It must create a culture that is able to let go of programs that do not meet the growing threat. The NIWC also needs a strategy that integrates with the joint warfighting concept for supporting precision long-range fires. 

According to the Director of the Space Development Agency, Dr. Derek Tournear, during the Sea-Air-Space 2020 Modern Warfighter panel, U.S. adversaries execute an acquisition timeline of about three to five years at the longest. By contrast, the U.S. acquisition cycle is about 10 years at the shortest. While this comment was space systems-focused, the reality rings true across the DoD acquisition system. This means a capability gap between the U.S. and an adversary will be short lived. Dr. Tournear also highlighted that this issue is not particular to the DoD acquisition program, but is a culture and process issue within the acquisition community. The DoD acquisition community is currently designed around not taking risks and overdesigning any issues that could impact program progress. A technique to combat this culture issue would be iterative designs that embrace 80% solutions on compressed time scales allowing feedback loops. Getting something to the fleet that addresses today’s problems without having to wait for full deliveries would drastically increase lethality, while real-world operator feedback would improve the end-state acquisition delivery. This is one example solution to address this problem that would complement other solutions such as digital acquisition and open architectures. 

Conclusion

The NIWC has been a cornerstone of every decisive point in every major naval battle in history. Despite this pedigree, GPC has placed an exciting challenge on the NIWC. To deter and win a GPC fight in 2035 and beyond, the NIWC must evolve to meet the challenge. To embrace the problems of the future, the NIWC must build a force that can integrate with the most important disruptive technologies like AI, train the force to quickly integrate and employ those technologies, and to acquire those technologies at the right pace. 

LCDR Gerie Palanca is a Cryptologic Warfare Officer and Information Warfare – Warfare Tactics Instructor specializing in intelligence operations and maritime space operations. His tours include department head at NIOC Colorado, signals warfare officer on USS Lassen (DDG 82), and submarine direct support officer deployed to the western Pacific. LCDR Palanca also attended the Naval Postgraduate School and received a M.Sc. in space system operations.

Endnotes

[1] CAPT W. P. Hughes, RADM R. P. Girrier, and ADM J. Richardson. Fleet Tactics and Naval Operations 3rd Edition, US Naval Institute Press. 2018. Annapolis, Maryland.  

[2] Congressional Research Service. “Intelligence, Surveillance, and Reconnaissance Design for Great Power Competition,” 04 June 2020. Available at: https://crsreports.congress.gov/product/pdf/R/R46389.

Featured image:  USS Gabrielle Giffords (LCS 10) launches a Naval Strike Missile (NSM) during exercise Pacific Griffin.  (U.S. Navy photo by Mass Communication Specialist 3rd Class Josiah J. Kunkle/Released)

Naval Intelligence Topic Week

By Captain Michael Van Liew, USMC

The legendary Coastwatchers of World War II provided some of the most critical intelligence of the entire war. Through preparation and effort in the worst of conditions, these units created a reconnaissance screen throughout the South Pacific that was indispensable in the success of the Allies’ single naval battle. The United States Marine Corps describes the single naval battle concept, “Approaching the maritime domain as a singular battlespace (containing land, sea, air and cyber components) offers opportunities through a single naval battle approach that integrates all elements of sea control and naval power projection into a cohesive whole.”¹ Today’s increasingly dynamic and complex security environment creates an imperative for the implementation of the single naval battle concept. The single naval battle seeks to remove artificial seams and create a multi-domain naval force that outmatches an increasingly sophisticated adversary in the application of naval power.² The Coastwatchers intelligence network is one of the greatest intelligence operations of World War II with multiple lessons for future naval intelligence operations in the single naval battle.

Following World War I, Australia and New Zealand each began building an intelligence network along their coastlines and the archipelagos of the South Pacific. The Royal Australian Navy viewed the chain of islands north of Australia, “as a fence, but a fence with several gates; the straits between the islands.”³ This concept became the reconnaissance screen of the Coastwatchers. The Australian Coastwatchers were known as Operation Ferdinand, after the children’s book character Ferdinand the Bull. The name was, “a reminder to them that it was not their duty to fight, and thus draw attention to themselves… it was their duty to sit, circumspectly and unobtrusively, and gather information. Of course, like Ferdinand, they could fight if they were stung.”⁴ Together, the interlocked Australian and New Zealand Coastwatching networks spanned from New Guinea in the northwest to the Pitcairn Islands in the east.⁵ The tele radios and existing radio stations that connected these locations enabled a time advantage in intelligence communication, contributing to the Allies’ success in many battles. The networks provided the Allies with a vast intelligence capability for naval operations in the Pacific.

The Coastwatchers’ intelligence served as an integral part of the single naval battle. Admiral Halsey, the commander of the South Pacific Area summarized the Coastwatchers’ effectiveness in the single naval battle during the Solomon Islands Campaign when he stated, “The Coastwatchers saved Guadalcanal, and Guadalcanal saved the South Pacific.”⁷ The ingenuity and impact of the Coastwatchers during World War II in the Pacific is profound.

Both the Australian and New Zealand Coastwatcher networks were proactive in establishing themselves during the interwar years. The Australian Coastwatcher network began in 1919 and New Zealand began its Coastwatching program in 1929.⁸ Although the Coastwatchers effort was expanded when war began, the early action taken to create the Coastwatchers proved valuable when war broke out in 1939 and as Japan joined the Axis powers in 1940. Commander Eric Feldt of the Royal Australian Navy served as the Supervising Intelligence Officer of Operation Ferdinand’s Northeast Area for several years.⁹ He summarizes the importance of a proactive intelligence network, “by September 1939, the Coastwatchers were eight hundred strong, the great majority of them, of course, on the Australian mainland. In Australia’s island screen, where Ferdinand was eventually to operate, the system was still very thin and spotty, but at least a nucleus existed, and funds were available. Upon the outbreak of war… the Navy directed the organization, such as it was, to commence functioning.”¹⁰ Predicting the next war has historically been next to impossible, but as the Coastwatchers demonstrate, actively preparing intelligence during periods absent of major conflict assists in preparing for the next major conflict.

Naval intelligence must be proactive to be effective across the competition continuum. In other words, the naval force must always be collecting intelligence. Just as conflict is continuous in its different forms so is the single naval battle and the necessity for continuous intelligence. The United States Marine Corps states, “The integrated single naval battle begins with the Phase 0 battle for influence, allowing discriminating force application based on understanding gained from forward presence.”¹¹ Proactive intelligence achieves this “understanding gained from forward presence.”¹² Continuous intelligence collection is necessary for a navy in performing its functions across the range of enduring competition, whether that be in relative peace or relative war.

The Coastwatchers network was effective in serving as a deep sensor by providing multi-domain intelligence collection of the sea, air, and land through human intelligence.¹³ The value of this multi-domain intelligence collection was demonstrated when the Coastwatchers provided strategic intelligence of the Japanese building an airfield on Guadalcanal. This intelligence focused the United States’ first major naval offensive toward the Solomon Islands Campaign because the airfield posed a threat to the sea lines of communication leading to Australia. During the execution of the campaign, Henderson Field on Guadalcanal provided an “unsinkable aircraft carrier” that kept the Japanese from mounting an effective counterattack.¹⁴ The Coastwatchers were so well positioned to observe Japanese ship movements and air raids toward Guadalcanal that their intelligence enabled the Allied naval forces to rarely be caught off guard. Regarding Japanese attacks against Guadalcanal in 1943, “the Coastwatchers were placed to check on the entire sequence of movements.”¹⁵ Because of this fidelity, Allied ships and aircraft were able to repeatedly outmatch the Japanese attacks. The reporting of these threats communicated a multi-domain intelligence picture to the naval fleet.

Naval intelligence must be multi-domain just as the single naval battle addresses the multi-domain operating environment. The single naval battle seeks to, “link the elements of naval power projection into a seamless web of integrated capabilities across air, maritime (surface and subsurface), land, space, cyber and cognitive domains.”¹⁷ The Coastwatchers collected intelligence from the sea, air, and land, and so must modern naval forces. Furthermore, new technologies now enable navies to collect intelligence from new domains and old domains in new ways. The space and cyberspace domains were not available to the Coastwatchers, but are becoming increasingly important today. The number of satellites in orbit is expected to increase five times in the next ten years.¹⁸ In the cyber domain, CISCO forecasts that the number of networked devices globally will be three times that of the number of humans on earth by 2023.¹⁹ Analyzing threats through multiple domains is imperative in preparation for the future single naval battle. Naval intelligence collection must occur in all domains to prepare for these threats.

The Coastwatchers capitalized on access to the archipelagos of the South Pacific and the knowledge of individuals who were familiar with the environment. The Coastwatcher organizations were comprised of islanders, settlers of European descent, who knew how to survive on these islands and were familiar with the natives. The title of islander was earned once a settler had spent four or five years living on one of the islands, ensuring their knowledge of the environment. These islanders had various occupations such as administrative officers, miners, prospectors, missionaries, planters, or patrol officers.²⁰ Additionally, island natives were an essential part of the Coastwatcher networks. They provided assistance that was not otherwise available by serving as scouts, spies, couriers, radio operators, medics, porters, and navigators.²¹ Natives also provided force protection from Japanese patrols. Some natives had an unwavering commitment to the Coastwatchers effort, while others allied with the Japanese as they began occupying islands. The allegiance of the natives often determined the success of the Coastwatchers on a particular island. Commander Eric Feldt stated, “There was no possibility of any European posing as a native. Concealment was our only hope and this meant mobility… In other countries, however, it might be very different and the best concealment might be in the slums of a large city. Anywhere, the natives of the country will be the best operators.”²² The Coastwatchers were fortunate to have had access and local support in these island locations, but the end of colonial empires makes access and local support much less certain in the present day.

Access and local support are essential to effective intelligence during the single naval battle. The proactive multi-domain intelligence operations of the single naval battle require diplomatic partnerships and agreements to provide placement and access. Furthermore, host nation or local support is important for the variety of tasks and knowledge that only natives can provide in maintaining such a network. Proactive naval intelligence requires access and support from partners and allies.

The historic success of the Coastwatchers provides valuable insight for naval intelligence in the future single naval battle. Proactive intelligence, multi-domain intelligence, and local access and support remain necessary for an effective naval intelligence operation. Naval forces will grow stronger through these lessons as the world’s security environment becomes more complex and dynamic. The future challenge is to harmonize these lessons into a single integrated naval force. As the naval force tackles this and other challenges, remember the Coastwatchers.

Captain Michael Van Liew is a United States Marine Corps Intelligence Officer who, at the time of original publication, was assigned as a student at Expeditionary Warfare School in Quantico, VA.

Endnotes

1. Amphibious Capabilities Working Group, Naval Amphibious Capability in the 21st Century: Strategic Opportunity and a Vision for Change (Washington, DC: United States Marine Corps, April 27, 2012), 4, https://defenseinnovationmarketplace.dtic.mil/wp-content/uploads/2018/02/MC_Amphibious_Capabilites.pdf.

2. Amphibious Capabilities Working Group, 33.

3. Eric A. Feldt, The Coastwatchers (Coppell, TX: The War Vault, 2019), 12.

4. Feldt, The Coastwatchers, 7.

5. David Oswald William Hall, The Official History of New Zealand in the Second World War 1939-1945: Coastwatchers Episodes and Studies Volume 2 (Wellington, NZ: War History Branch of the Department of Internal Affairs, 1951), 4 and 28–29, http://nzetc.victoria.ac.nz/tm/scholarly/tei-WH2-2Epi.html; Justin Haynes, “Human Intelligence as a Deep Sensor in Multi-Domain Operations: Australia’s World War II Coastwatchers,” Military Intelligence Professional Bulletin 45, no. 3 (July-September 2019), 35, https://www.ikn.army.mil/apps/MIPBW/MIPB_ Features/HumanIntelligenceasaDeepSensorinMulti-DomainOperations.pdf.

6. Sources used to create this depiction include Central Intelligence Agency, Oceania, map, in The World Factbook (Washington, DC: Central Intelligence Agency, March 4, 2021), https://www.cia.gov/the-world-factbook/static/97fb508232ccc526320d30d41033ca09/oceania_phy.jpg; Hall, 4–5 and 28–29; Feldt, The Coastwatchers, 8, 12, and 138–143; John Brown, “Coast Watchers in the Solomons,” Warfare History Network, last modified August 29, 2016, https://warfarehistorynetwork.com/2016/08/29/coast-watchers-in-the-solomons/; Madison Pine and Geraldine Warren, “Our Coastwatchers,” Auckland War Memorial Museum, last modified August 11, 2020, https://www.aucklandmuseum.com/war-memorial/online-cenotaph/features/coastwatchers.

7. Peter Djokovic, “The Coastwatchers and Ferdinand the Bull,” Semaphore 4 (2014), 2, https://www.navy.gov.au/media-room/publications/semaphore-coastwatchers-and-ferdinand-bull.

8. Feldt, The Coastwatchers, 8; Hall, 3.

9. Eric A. Feldt, “Coastwatching in World War II,” Proceedings 87, no. 9 (September 1961), 72, https://www.usni.org/magazines/proceedings/1961/september/coastwatching-world-war-ii.

10.  Feldt, The Coastwatchers, 9.

11.  Amphibious Capabilities Working Group, 5.

12. Amphibious Capabilities Working Group, 5.

13.  Haynes, 34 and 38.

14. James D. Hornfischer, Neptune’s Inferno: The U.S. Navy at Guadalcanal (New York: Bantam Books, 2011), 4–5, 124.

15. Feldt, The Coastwatchers, 85, 102.

16. Douglas MacArthur’s General Headquarters Staff, Reports of General MacArthur: The Campaigns of MacArthur in the Pacific (1994, Washington, DC: Library of Congress, 2006), 81-84, https://history.army.mil/books/wwii/macarthur%20reports/macarthur%20v1/ch04.htm.

17. Amphibious Capabilities Working Group, 5.

18. Konstantin Kakaes, Tate Ryan-Mosely, and Erin Winnick, “The Number of Satellites Orbiting Earth Could Quintuple in the Next Decade,” MIT Technology Review, June 26, 2019, https://www.technologyreview.com/2019/06/26/755/satellite-constellations-orbiting-earth-quintuple/.

19. Kelly Hill, “Connected devices will be 3x the global population by 2023, Cisco says,” RCR Wireless News, February 18, 2020, https://www.rcrwireless.com/20200218/internet-of-things/connected-devices-will-be-3x-the-global-population-by-2023-cisco-says#:~:text=Cisco’s%20new%20annual%20forecast%20predicts,Internet%20Report%20analysis%20and%20forecast.

20.  Feldt, The Coastwatchers, 27–31.

21. Anna Annie Kwai, Solomon Islanders in World War II: An Indigenous Perspective, State, Society and Governance in Melanesia Series (Acton, ACT, Australia: Australian National University Press, 2017), 3, 17-19, 22, 27, 29, 37–40, and 43–44, https://press-files.anu.edu.au/downloads/press/n4039/pdf/book.pdf.

22. Feldt, “Coastwatching in World War II,” 75.

Featured Image: A local wireless telegraphist operator operating an AWA 3BZ teleradio at Segi Coastwatchers station, British Solomon Islands. (Photo courtesy of the Australian War Museum)