Intelligence Practitioners Research Articles

Improving intelligence analysis and education in the US with stronger foundations in statistical literacy

ABSTRACT This article argues that coursework in statistical literacy can improve the practice of intelligence analysis in the US. The article describes the gaps in current intelligence education pertaining to statistically literacy, explains how statistical literacy relates to the tasks of intelligence analysis, and offers a series of recommendations for statistical literacy courses specifically designed for future intelligence practitioners. The incorporation of statistical literacy in intelligence studies programs will advance and strengthen the contribution such programs can make to the intelligence workforce, both in the public and private sectors.

An FDA for AI? Pitfalls and Plausibility of Approval Regulation for Frontier Artificial Intelligence

Observers and practitioners of artificial intelligence (AI) have proposed an FDA-style licensing regime for the most advanced AI models, or 'frontier' models. In this paper, we explore the applicability of approval regulation -- that is, regulation of a product that combines experimental minima with government licensure conditioned partially or fully upon that experimentation -- to the regulation of frontier AI. There are a number of reasons to believe that approval regulation, simplistically applied, would be inapposite for frontier AI risks. Domains of weak fit include the difficulty of defining the regulated product, the presence of Knightian uncertainty or deep ambiguity about harms from AI, the potentially transmissible nature of risks, and distributed activities among actors involved in the AI lifecycle. We conclude by highlighting the role of policy learning and experimentation in regulatory development, describing how learning from other forms of AI regulation and improvements in evaluation and testing methods can help to overcome some of the challenges we identify.

The Application of the Devil’s Advocacy Technique to Intelligence Analysis

Understanding evolving situations and predicting future events are significant challenges in the intelligence sphere. These necessitate advanced techniques for intelligence collection and robust evaluation procedures to enhance the accuracy of predictions. The Devil’s Advocacy technique can be employed to improve analysis procedures by challenging prevailing views and mitigating the risk of cognitive biases. This paper examines the effectiveness of the Devil’s Advocacy technique when applied to intelligence analysis, by evaluating its strengths, weaknesses, and applicability, through a comprehensive literature review and empirical research involving experienced practitioners in New Zealand. Previous studies examining the Devil’s Advocacy technique primarily focused on its contribution to decision-making on the final intelligence product and on the perceptions of the devil’s advocate. These are important, but this paper is also concerned with the analysts’ experience of practically applying the technique for intelligence analysis. This paper contends that the Devil’s Advocacy technique is an attractive complementary technique which is effective in specific situations. It also reveals that New Zealand intelligence practitioners define, perceive, and apply the Devil’s Advocacy technique differently across their organisations. It therefore argues that New Zealand practitioners may have an inconsistent understanding of the technique, indicating potential gaps in the training and education of New Zealand intelligence professionals. However, the inherently subjective nature of the technique itself could also be a contributing factor.

“We Have Successfully Neutralised an Attack”—Historical Case Studies in Terrorism Prevention Through Cooperation

ABSTRACT While there is a large body of literature concerned with understanding terrorist attacks and the reasons for why they could not be prevented, this article looks at it from the opposite side: why could terrorist attacks successfully be prevented and what role did intelligence-sharing play? The article analyses three historical cases in depth based on extensive archival records from 18 intelligence agencies. This article traces how intelligence-sharing worked by highlighting the hands-on experiences of intelligence practitioners. The contribution of this article is twofold. First, the article shows how intelligence officers managed to establish successful and effective counterterrorism cooperation in the early 1970s. Second, through the eyes of intelligence reports the article presents new insights about terrorist tactics and terrorism innovation at the time. This included the use of women in terrorist plots and car sales as cover business for terrorism financing. The article concentrates on a peak moment in European terrorism history: it analyses early 1970s Black September attacks and the efforts of intelligence agencies to counter them.

A cyberterrorist behind the keyboard

Abstract Given the diverse backgrounds of people living in modern societies as well as the international nature of cyber-terrorist threats, profiling the type of person behind cyber-mediated crimes has become a norm in terrorist profiling practice. This study contributes to timely efficient terrorist profiling and threat assessment by showcasing an automated content analysis of cyber-mediated terrorist texts, using natural language processing technology and AI-assisted analysis. To characterise the terrorist type of texts and provide clues to threats, the study employs a ‘psycholinguistic profiling’ approach to authorship analysis (Grant 2008). That is, it seeks to describe the likelihood of an author’s engagement in violent extremist activity, identify motives for violence, and provide clues vis-a-vis would-be and actual violent behaviours. The study takes twenty texts produced by international terrorists involved in jihadism and far-right violent extremism as a case study. The findings reveal the investigative value of automated psycholinguistic profiling for security and intelligence practitioners, with the semantic patterns yielding helpful information for an understanding of the criminal nature of terrorist language. Also revealed is the attentional pattern of extremists and their discourse together with clues-based conclusions about text type, as well as ‘warning’ behaviours and motives for aggression which vary according to the authors’ ideological differences.

Book Review – Intelligence Overview: The Watchers and the Watchdog

Book Review by Dr Peter Grace Didier Bigo, Emma Mc Cluskey, Felix Tréguer (eds), (2024), Intelligence Oversight in Times of Transnational Impunity. Who will Watch the Watchers? Oxon: Routledge. ISBN 9781032406541. 310 pages. This book focuses on two important issues in intelligence oversight: the long-standing acceptance of raison d’état, and the increasing relations between intelligence agencies transnationally and how much those should come under scrutiny and legal restraint. It is not a book that is designed to be read comfortably by intelligence practitioners, and indeed there are priors that suggest practitioners would much prefer it if there was no oversight of their activities at all. Whether framing the enquiry in this way provokes some degree of urgency or simply divides opinion, the questions of raison d’état and transnational oversight are important.

Optimising intelligence operations for international law enforcement: harnessing THRIVE for national intelligence model advancement

ABSTRACT THRIVE (Threat, Harm, Risk, Investigation, Vulnerability, and Engagement) represents a decision-making framework introduced by the United Kingdom’s (UK) National Police Chiefs’ Council in 2017, with a particular focus on vulnerability. Alongside THRIVE other intelligence-led policing models such as the National Intelligence Model (NIM), have become integral to policing practices. While THRIVE is widely adopted as a primary analysis and decision-making framework in UK police services, its examination remains limited, including its impact on the NIM and its use by intelligence personnel. Interviews with 15 police personnel from operation intelligence units within a specific English service were conducted to ascertain its level of adoption. A series of Freedom of Information (FOI) requests to all 43 UK police services in England and Wales were then initiated, to understand if the THRIVE model is adopted and, if so, where within their respective units. The findings indicate widespread acceptance and integration of THRIVE among intelligence practitioners, without immediate adverse effects on the application of the NIM. The use of heuristic naturalistic decision-making processes in THRIVE assessments, suggests a need for further research. Though, there is a risk of reduced decision-making capacity among frontline intelligence workers using THRIVE within the constraints of the NIM.

Everybody Needs Help Sometimes: Facilitators of Soviet Defectors’ Publications

Soviet intelligence officer defectors arrived in their new countries lacking skills that translated easily into postdefection jobs. To earn money, they often turned to the one asset they had—their stories. To publish their stories, they had to work with a variety of facilitators who connected them with publishing companies and distributed their works. Those helpers can be characterized into four categories: activists/dissidents, academics, journalists, and intelligence practitioners. Helpers were sometimes connected to and supported by a Western government, particularly the United States or United Kingdom, and the resulting work reflected the Cold War ideological competition. However, government sponsorship was not always the case, and some helpers expressed views that extended beyond the receiving government’s policy or that criticized the handling agency. In any case, most defectors could not have published their works without the helpers’ support.

Reclaiming artificial intelligence accounts: A plea for a participatory turn in artificial intelligence inquiries

How to participate in artificial intelligence otherwise? Put simply, when it comes to technological developments, participation is either understood as public debates with non-expert voices to anticipate risks and potential harms, or as a way to better design technical systems by involving diverse stakeholders in the design process. We advocate for a third path that considers participation as crucial to problematise what is at stake and to get a grip on the situated developments of artificial intelligence technologies. This study addresses how the production of accounts shape problems that arise with artificial intelligence technologies. Taking France as a field of study, we first inspected how media narratives account for the entities and issues of artificial intelligence, as reported by the national press over the last decade. From this inspection, we identified four genres and described their performative effects. We then conducted a participatory inquiry with 25 French artificial intelligence practitioners’ to ground artificial intelligence in situated experiences and trajectories. These experiential accounts enabled a plural problematisation of artificial intelligence, playing with the geometries of artificial intelligence and its constituencies, while diversifying and thickening its problems. To conclude, we discuss how participatory inquiries, through experiential and plural accounts offer a refreshing weaving of artificial intelligence problems into the fabric of its deployments. Our participatory approach seeks to re-politicise artificial intelligence from practitioners’ situated experiences, by making the ongoing relationships between past trajectories, current frictions and future developments tangible and contestable, opening avenues to contribute otherwise.

Developing a narrative theory of deception for the analysis of mock-Covert Human Intelligence Source (CHIS) accounts

Human source intelligence (HUMINT) practitioners are concerned with detecting informant deception, and previous research indicates that the verbal content of an informant’s narrative can be used to identify potential deceit. The current study extends previous research by analysing the narrative structure and narrative identity of accounts provided by 22 participants undertaking the role of a mock-informant. Results indicate that deception affects the structure of a mock-informant narrative, with deceptive mock-informants employing abstract introductions and evaluative remarks to withhold information and to distract their listeners with emotional content. Additionally, deceptive mock-informants are more likely to express a low potency narrative role, such as a victim or tragic hero. Furthermore, there is tentative evidence to suggest that an analysis of narrative identity can also provide an indication of varying levels of motivation and cooperation among truthful mock-informants. These findings have implications for HUMINT practitioners in the field and add to the wider body of deception detection research.

Auditory and Olfactory Copying in Intelligence: Brain and Thought Modifications Beyond the Word

For those who command the machine, regulate the satellite, or handle operations in the field, everything depends on the brain, on the human being. According to the North Atlantic Treaty Organization, the sixth domain where conflict will occur and peace will have to be managed is the cognitive one, made official in 2021. It becomes the most important of all. In the end, the match will be won by whoever will have practitioners, analysts, or those deployed in the field with the best brain. Experiments are being carried out in some countries where the human brain gets physically connected to the machine so that the machine can learn how the human brain works. However, a machine will learn from that person’s brain, with all their limitations, biases, and fears, therefore already having numerous flaws in its system, without considering the ethical disputableness of this kind of thing. There is a way to win in the sixth domain: enhancing the intelligence practitioners’ capabilities, which is doable thanks to the latest studies and techniques developed. It is, therefore, possible, without medicines, drugs, or electrical and electronic equipment, to augment the mental capability and plasticity of those who will have to win these challenges.

Characteristics, prospects and limitations of ChatGPT

In November 2022, Chat Generative Pre-trained Transformer (ChatGPT) released by OpenAI attracted worldwide attention as soon as it was released. Both artificial intelligence practitioners and the public are scrambling to try this latest chatbot. This paper mainly studies what ChatGPT is, and the remarkable characteristics of ChatGPT compared with other chatbots, as well as the prospect and limitations of ChatGPT. The main purpose of writing this paper is to provide some references for students or practitioners in the direction of artificial intelligence, and to make people who do not know ChatGPT and other large-scale language chat models more systematic understanding. The latest large-scale language model ChatGPT is studied by literature analysis and summary. This paper finds that although ChatGPT has indeed brought shock to the global people in the field of machine learning in the field of artificial intelligence, the hidden dangers and defects behind it (academic integrity, privacy, etc.) are gradually exposed, and relevant practitioners still need to propose measures to improve and develop new uses of chatbots.

The Possibility of Artificial Qualia

The discussions about qualia are mind-body problems. If artificial intelligence provides a functionally identical body, will it possess the same conscious experience? The possibility of artificial qualia, which is on the cutting edge of the development of artificial intelligence, will be the main topic of this essay. This paper argues the presupposition of the possibility of artificial qualia is the possibility of strong AI. Searl was the first person to question the possibility of strong AI by formulating the Chinese Room Argument. This paper introduces common objections from artificial intelligence practitioners and the development of modern AI, proving the invalid of the objection and claiming the possibility of strong AI. Next, this paper follows David Chalmers argument about the principle of organizational invariance and reconstructs Chalmers two Reductio ad Absurdum arguments to rebut objections. By formulating fading qualia argument and dancing qualia argument, the absent qualia argument and the inverted qualia argument are proved wrong. The principle can support the possibility of artificial qualia.

Exploiting noise as a resource for computation and learning in spiking neural networks

Networks of spiking neurons underpin the extraordinary information-processing capabilities of the brain and have become pillar models in neuromorphic artificial intelligence. Despite extensive research on spiking neural networks (SNNs), most studies are established on deterministic models, overlooking the inherent non-deterministic, noisy nature of neural computations. This study introduces the noisy SNN (NSNN) and the noise-driven learning (NDL) rule by incorporating noisy neuronal dynamics to exploit the computational advantages of noisy neural processing. The NSNN provides a theoretical framework that yields scalable, flexible, and reliable computation and learning. We demonstrate that this framework leads to spiking neural models with competitive performance, improved robustness against challenging perturbations compared with deterministic SNNs, and better reproducing probabilistic computation in neural coding. Generally, this study offers a powerful and easy-to-use tool for machine learning, neuromorphic intelligence practitioners, and computational neuroscience researchers.

Revisiting the Psychology of Structured Analytical Techniques

Structured analytic techniques (SATs) are considered the gold standard for intelligence practitioners to mitigate judgmental biases. On the other hand, recent psychological research has challenged the effectiveness of SATs. Here, these seemingly irreconcilable standpoints will, to some extent, be reunited. To this end, the empirical evidence of three prominent SATs is reviewed: empirical research provides support for brainstorming and devil’s advocacy. The analysis of competing hypotheses, however, does not have empirical support. Based on the literature review and conceptual criticism of SATs, implications are discussed: the Intelligence Community (IC) must discard its antiempiricism. To this end, intelligence studies programs should regularly incorporate quantitative research methods courses in their curricula. The research community, on the other hand, should seek more frequent collaboration with the IC, to support the IC in improving the empirical foundations of their work. This could improve judgmental processes in intelligence analysis as well—possibly both within and beyond SATs. Moreover, other tasks in the IC (e.g., human intelligence) would benefit from a sound empirical approach as well.

Victors’ history: Chinese retrospectives on the Hugh Redmond case

ABSTRACT In 1954, a Shanghai court sentenced US national Hugh Redmond to life imprisonment on espionage charges. Found guilty of directing an extensive agent network against Chinese political, economic and military intelligence targets, he remained in custody until his alleged suicide in 1970. Since then, Redmond’s life has been the subject of several Western publications, but detail has been scarce about his reporting requirements, collection methods and the security operation that culminated in his arrest. Drawing on Chinese accounts of the case, this paper addresses these gaps. A picture emerges of non-official cover arrangements flawed from the outset at a time when the US demand for Korean War-related intelligence was at its height. Alerted by doctrine and success against another local CIA operation, Shanghai’s security apparatus moved cautiously against Redmond’s network, obtaining evidence that made the guilty verdict of 1954 inevitable. To Chinese intelligence practitioners, the case provides an exemplary example of how counter-espionage work against the US should proceed in the 21st century. In July 2019, CIA would ‘neither confirm nor deny the existence or non-existence’ of records related to Redmond’s activities in China, and the 50th anniversary of his death in 2020 passed without public official acknowledgement.

Introducing DynaPTI-constructing a dynamic patent technology indicator using text mining and machine learning.

Patent data is an established source of information for both scientific research and corporate intelligence. Yet, most patent-based technology indicators fail to consider firm-level dynamics regarding their technological quality and technological activity. Accordingly, these indicators are unlikely to deliver an unbiased view on the current state of firm-level innovation and are thus incomplete tools for researchers and corporate intelligence practitioners. In this paper, we develop DynaPTI, an indicator that tackles this particular shortcoming of existing patent-based measures. Our proposed framework extends the literature by incorporating a dynamic component and is built upon an index-based comparison of firms. Furthermore, we use machine-learning techniques to enrich our indicator with textual information from patent texts. Together, these features allow our proposed framework to provide precise and up-to-date assessments about firm-level innovation activities. To present an exemplary implementation of the framework, we provide an empirical application to companies from the wind energy sector and compare our results to alternatives. Our corresponding findings suggest that our approach can generate valuable insights that are complementary to existing approaches, particularly regarding the identification of recently emerging, innovation-overperformers in a particular technological field.

There Is No Such Thing as Open Source Intelligence

This article argues that “open source intelligence (OSINT)” is a fundamentally incoherent concept that should be abandoned. It does so in two steps. First, by challenging the underlying criteria used to demarcate it as a separate “INT” among its more traditional peers. Second, through a historical critique that argues that “OSINT” as a conceptual category served a transitionary stage that has long passed. That is, it helped intelligence practitioners and scholars appreciate the influx of valuable unclassified information made newly available by the World Wide Web in the 1990s, but the advantages gained from this notion have now declined, and the concept is now a liability. By discarding the term altogether, and recategorizing openly derived sources of information back into their traditional homes, significant conceptual and analytical benefits can be attained.

Advancing intelligence analysis: using natural language processing on East Pakistani intelligence documents

ABSTRACT This article demonstrates how natural language processing (NLP) can be used by intelligence practitioners and scholars to analyse text. Using decades of unredacted East Pakistani intelligence reports declassified and released by the Government of Bangladesh, the article shows how machine learning can provide insight into intelligence documents. In particular, it provides a case study for how NLP can provide quantitative analysis that complements the work of qualitative analysis. Simultaneously, this article also demonstrates how NLP can provide historians with a quantitative methodology to better understand historical government records.

Mobile Applications Adoption and Use in Strategic Competitive Intelligence: A Structural Equation Modelling Approach

This article examined the key determinants of mobile applications’ adoptionand use in strategic competitive intelligence. A quantitative research based on a survey of150 participants drawn from strategic competitive intelligence practitioners and analysts wasused to examine and validate the extended UTAUT2 Model to identify the key determinantsof mobile applications` adoption and use in SCI. PLS-SEM algorithm was used to analysedata. Findings show that PE, SI, HT, SE, and BI had significant influence over UB while EE,HM, PV, SN, and PR had an insignificant influence. Adoption and use of mobile applicationswas considered a planned behaviour. Perhaps the most important findings for SCIPs relateto the importance-performance map analysis that showed the greater absolute importance ofself-efficacy on use behaviour. Previous empirical studies have largely ignored the influence ofcognitive psychological perceptive which this study addressed by examining key determinantsof behaviour intention and user behaviour.