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Open research questions in Deception detection and forensic psychology

236 unresolved questions extracted from the limitations and future-work sections of 1,905 Deception detection and forensic psychology papers in our library. Each links back to the study that raised it.

What the literature leaves open

  • The study used a fictitious AI-based deception classifier, - The experimental task was designed to isolate the effects of the model's characteristics, - The study had a limited sample size of 373 participants after exclusions, - The study only examined the role of the model's accuracy and uncertainty for individual predictions

    Humans incorrectly reject confident accusatory AI judgments · 2026 · DOI

  • Further research is needed to understand under which conditions AI-based judgments on statement veracity are endorsed or rejected by human decisionmakers, - Research should investigate the effects of human-AI interaction on machine performance, - Studies should examine the role of other factors influencing human adoption of AI judgments

    Humans incorrectly reject confident accusatory AI judgments · 2026 · DOI

  • The difficulty of judging the veracity of others. The challenge of understanding the psychological mechanisms of modern interrogation methods. The need to recognize a wider range of epistemic agency.

    False confessions, epistemic agency, and repairing self-trust · 2026 · DOI

  • The lack of understanding of why people are compelled to give false confessions. The lack of understanding of how people are treated unjustly as epistemic agents. The need to demystify the mechanisms that manipulate the epistemic agency of all those involved.

    False confessions, epistemic agency, and repairing self-trust · 2026 · DOI

  • Investigate conditions under which individual interview and learning performance between sessions would be optimal, - Examine the impact of prior experience on learning outcomes

    Appraising the Task: A Mega-Analysis of Interviewers’ Challenge-Threat Assessments and Their Performance in Simulated Child Investigative Interviews · 2026 · DOI

  • The gap in the literature is the lack of understanding of how interviewers' subjective appraisals relate to their performance in simulated child investigative interviews. Prior work has shown that training programs have been developed to improve interview quality, but not all trainees benefit from these interventions.

    Appraising the Task: A Mega-Analysis of Interviewers’ Challenge-Threat Assessments and Their Performance in Simulated Child Investigative Interviews · 2026 · DOI

  • There is a lack of research on the timing of evidence disclosure during interrogations. The study aims to address this gap by examining the association between the timing of evidence disclosure and the suspect's confession outcome.

    Evidence Disclosure and Confessions During Interrogations in Japan · 2026 · DOI

  • The study identifies the challenge of low inter-rater reliability in evaluating statements based on SCAN criteria. The study also notes the challenge of potential harm and lack of efficacy in using the SCAN technique for lie detection.

    Inefficacy of the SCAN Technique in Discriminating Between Truthful and Fabricated Statements · 2026 · DOI

  • There is a lack of understanding of the actual and self-reported lie detection performances of professionals. Prior work has focused primarily on police officers, with little attention to other professionals. The study aims to address this gap by investigating the lie detection performances of different groups of professionals.

    Lie Detection Performances and Beliefs in Different Groups of Professionals · 2026 · DOI

  • One challenge is the limited research on nonverbal evidence collection techniques for nonspeaking populations. Another challenge is the need to develop accessible investigative interviewing practices for children and people with disabilities. The paper also notes the difficulty of gathering evidentiary information from minimally speaking and nonspeaking individuals.

    Bridging the Silence: A Scoping Review to Facilitate the Development of an Interview Protocol for Minimally Speaking and Nonspeaking Individuals · 2026 · DOI

  • many of the studies identified did not focus exclusively on minimally speaking or nonspeaking populations, - the role of drawing for individuals with minimal or no expressive language remains underexplored, - limited research specifically examining how these methods apply to populations who are entirely nonspeaking

    Bridging the Silence: A Scoping Review to Facilitate the Development of an Interview Protocol for Minimally Speaking and Nonspeaking Individuals · 2026 · DOI

  • The study only included Chinese laypersons, - The sample size was limited to 156 participants, - The study used a simulated environment with AI suspects

    Using large language model–based artificial intelligence (AI) suspects to train strategic use of evidence: Preliminary evidence of transfer to mock suspect interviews. · 2026 · DOI

  • The gap in prior work is the lack of opportunities for practical application of the strategic use of evidence technique. The paper identifies the need for a more effective training method that can enhance the transfer of skills to real interviews.

    Using large language model–based artificial intelligence (AI) suspects to train strategic use of evidence: Preliminary evidence of transfer to mock suspect interviews. · 2026 · DOI

  • There is a lack of evidence that nonverbal cues are useful in detecting deception. Prior research on lie detection has methodological limitations.

    Inefficacy of the SCAN Technique in Discriminating Between Truthful and Fabricated Statements · 2026 · DOI

  • consider other professions confronted with lies, - examine the impact of professional training on lie detection performances

    Lie Detection Performances and Beliefs in Different Groups of Professionals · 2026 · DOI

  • This variant of the N400 could serve as a useful tool for further research into how people evaluate the veracity of online information.

    An ERP exploration of the perception of text-based deception · 2025 · DOI

  • Despite digital evidence (DE) now being a major component of most criminal investigations, very few studies have examined how police officers themselves evaluate and use DE over the course of an investigation.

    “A Ronin Without a Master”: Exploring Police Perspectives on Digital Evidence in England and Wales · 2025 · DOI

  • There is no consensus in the literature about the role of speech disfluencies and eye contact as cues to deception.

    (Don’t) believe me, I’m telling the truth! Speech disfluency and eye contact as cues to veracity, intention, and truth judgement · 2024 · DOI

  • Existing research suggests that inattentional blindness is a poorly understood concept that violates the beliefs that are commonly held by the public about vision and attention.

    A survey of what legal populations believe and know about inattentional blindness and visual detection · 2024 · DOI

  • Finally, respondents provided strategies for what individuals can do to make themselves more likely to notice of unexpected events, despite a lack of evidence to support them.

    A survey of what legal populations believe and know about inattentional blindness and visual detection · 2024 · DOI

  • INVESTIGATIVE ACTIONS USING ARTIFICIAL TOOLS INCREASING RELIABILITY IN VERBAL INTELLIGENCE Nurmukhammed Tazhigulov (a) Serguei Cheloukhine (e) Yevgeniy Shulgin (b)1 Larissa Kussainova (c) Ainura Omarova (d) (a)PhD Student, Academy of Law Enforcement Agencies at the Prosecutor General’s Office of the Republic of Kazakhstan; E-mail: [email protected] (b)Professor, School of Law, Karaganda Academy of the Ministry of Internal Affairs of the Republic of Kazakhstan named after B.S. Beisenov, Karaganda, Kazakhstan; E-mail: [email protected] (c)Professor, School of Law, Karaganda National Research University named after academician Ye.A.Buketov, Karaganda, Kazakhstan; E-mail: [email protected] (d)Professor, School of Management, Karaganda National Research University named after academician Ye.A.Buketov, Karaganda, Kazakhstan; E-mail: [email protected] (e)Professor, John Jay College of Criminal Justice, New York, USA; E-mail: [email protected] A R T I C L E I N F O A B S T R A C T Article History: Received: 12th October 2025 Reviewed & Revised: 12th October 2025 to 11th April 2026 Accepted: 12th April 2026 Published: 15th April 2026 Keywords: Artificial Intelligence, Blockchain, Evidence Reliability, Verbal Investigative Actions, Digitalization of Justice JEL Classification Codes: K10, K24, K40, K14 Peer-Review Model: External peer review was done through double-blind method. Kazakhstan has prioritised digitalising its criminal justice processes, implementing AI-driven tools such as automated forensic systems and "digital autopsy" platforms to increase efficiency and transparency. However, challenges persist: interrogation recordings can still be falsified or incomplete due to inadequate technical equipment and procedural gaps, undermining evidence integrity. This study investigates a combined AI-blockchain framework to enhance the reliability of verbal investigative actions. It examines an integrated system in which automatic speech recognition (ASR) transcribes interrogation audio, and a private blockchain ledger immutably timestamps each transcript. The study employs a mixed-methods approach: data include recorded criminal interrogation sessions (audio transcripts) and relevant legal documents. A neural ASR model was trained on these transcripts (approximately 50 sessions) to produce digital text, and standard analytical methods were applied to evaluate system performance. Simultaneously, each transcript was recorded on a blockchain registry, and metrics such as transcription accuracy and error rate were measured. Results show the proposed system attains high transcription accuracy (94% word recognition) and significantly reduces manual review time (by about 40%).

    PROSPECTS FOR INCREASING RELIABILITY IN VERBAL INVESTIGATIVE ACTIONS USING ARTIFICIAL INTELLIGENCE TOOLS · 2026 · DOI

  • The study identifies a gap in the current understanding of online harm and its impact on children and teenagers. The study highlights the need for a more nuanced understanding of the risks facing younger audiences on social media.

    Catching Dark Signals in Algorithms: Unveiling Audiovisual and Thematic Markers of Unsafe Content Recommended for Children and Teenagers · 2026 · DOI

  • This study is not without limitations. First, the multimodal feature analysis relies on 16 basic multimodal features, which may not fully capture the audiovisual elements in short videos. Future research may expand the scope of this study and incorporate more platform-specific features and filters to provide a more comprehensive understanding of multimodal features of unsafe content. Second, the generalizability of the study’s findings is lim- ited by the dataset in two ways: (a) some short videos be- came unavailable during the study due to takedowns resul- tant from internal content moderation or changes in privacy settings, and (b) thematic analysis was conducted only on English-language captions. On the first point, only 4.1% (n = 186/4,496 URLs) of videos were inaccessible. Because the purpose of the study was to identify multimodal features of unsafe videos that may lead to subsequent negative impacts over time, we think this limitation is a minor point. On the second point, only 5.5% (n = 93/1,696 captions) of the cap- tions are in non-English languages. Future work needs to take into consideration all languages in texts, and culture- or language-specific multimodal features to expand the global relevance and generalizability of this work (Lai, Qie, and Rau 2021). Third, although this study analyzes short video content within the context of an algorithm auditing experiment, this study is observational in nature. As such, it provides correla- tional evidence linking multimodal features of short videos to unsafe content, without addressing the question of how such features influence subsequent information processing and psychological or behavioral changes. Future research can build on these findings using longitudinal designs or ex- perimental approaches to better understand how unsafe mul- timodal contents evolve and affect children and teenagers. Lastly, engagement with short videos was measured as the number of views, likes, and comments, but the data on dis- likes or downvotes was unavailable. This is because only YouTube Shorts allows dislikes but the platform does not report them separately. The like count reflects the net value after subtracting dislikes. This lack of negative engagement metrics limits our ability to capture more nuanced audi- ence responses, especially for unsafe content that is widely viewed but potentially negatively received. Future research could incorporate alternative metrics, such as watch dura- tions and shares, to better evaluate audience engagement at the individual level.

    Catching Dark Signals in Algorithms: Unveiling Audiovisual and Thematic Markers of Unsafe Content Recommended for Children and Teenagers · 2026 · DOI

  • Future research should investigate the phenomenon of superposition and its effects on model behavior. The study suggests exploring the use of Feature 20989 in AI monitoring and early warning systems.

    Deconstructing Deceptive Circuits: Uncovering Activation Patterns in Superposition (Version 2) · 2026 · DOI

  • The gap is in understanding the internal representation of deceptive behavior in small-scale language models. The study addresses the lack of empirical methodology for mechanistic interpretability research.

    Deconstructing Deceptive Circuits: Uncovering Activation Patterns in Superposition (Version 2) · 2026 · DOI

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236 open questions have been extracted from the limitations and future-work passages of 1,905 Deception detection and forensic psychology papers in our 4.5M-paper local library. Each one below links back to the study that raised it, so you can read the original claim in context.

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