A holistic, risk, and futures based approach to deception: technological convergence and emerging patterns of conflict
Why this work is in the frame
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Bibliographic record
Abstract
Modern challenges in forensic and security domains require greater insight and flexibility into the ways deception can be identified and responded to. Deception is common across interactions and understanding how mindset, motive and context affects deception is critical. Research has focussed upon how deception manifests in interpersonal interactions and has sought to identify behaviours indicative of truth-telling and deceit. The growth of mediated communication has further increased challenges in ensuring information is credible. Deception in military environments has focussed on planning deception, where approaches have been developed to deceive others, but rarely examined from counter-deception perspectives. To address these challenges this thesis advocates a holistic approach to deception detection, whereby strategies will be tailored to match context. In accordance with an in vivo approach to research, a critical review of literature related to deception and related areas was conducted leading to the initial development of a theoretical holistic model of deception detection comprising a deception framework and an individual differences (deceiver and target) framework. Following model development, validation with Subject Matter Experts (SMEs) was conducted. Explanatory thematic analysis of interviews conducted with SMEs (n=19) led to the development of meta-themes related to the ‘deceiver’, their ‘intent; ‘strategies and tactics’ of deception, ‘interpretation’ by the target and ‘target’ decision-making strengths and vulnerabilities. These findings led to the development of the Holistic Model of Deception, an approach where detection strategies are tailored to match the context of an interaction, whether interpersonal or mediated. Understanding the impact of culture on decision-making in deception detection and in particular the cues used to detect deception in interpersonal and mediated environments is required for understanding human behaviour in a globalised world. Interviews were conducted with Western (n=22) and Eastern (n=16) participants before being subject to explanatory and comparative thematic analysis identified twelve cross-cultural strategies for assessing credibility and one culturally specific strategy used by Western participants. Risk assessment and management techniques have been used to assess risks posed in forensic and security environments; however, such approaches have not been applied to deception detection. The Deception Assessment Real-Time Nexus©2015 and Deception Risk Assessment Technique©2015 were developed as an early warning tool and a Structured Professional Judgement risk assessment and management technique. The Deception Risk Assessment Technique©2015 outlines multiple ways of identifying andmanaging threats posed by deception and is employable across individuals and groups. In developing the futures-based approach to deception detection, reactive, active and proactive approaches to deception were reviewed, followed by an examination of scenario planning utility and methodology from futures and strategic forecasting research. Adopting the qualitative ‘intuitive logics’ methodology ten scenarios were developed of potential future threats involving deception. Risk assessment of two scenarios was conducted to show the value of a risk assessment approach to deception detection and management. In conclusion, this thesis has developed a Holistic Model of Deception, explored the links between interpersonal and mediated strategies for detecting deception, formulated a risk assessment and management approach to deception detection and developed future scenarios of threats involving deception.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it