Autonomous Scientifically Controlled Screening Systems for Detecting Information Purposely Concealed by Individuals

Twyman, Nathan W.; Lowry, Paul Benjamin; Burgoon, Judee K.; Nunamaker, Jay F.

doi:10.1080/07421222.2014.995535

Cited by 49 publications

(47 citation statements)

References 59 publications

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“…Therefore, we need to deal with the inevitable error resulting from making uncertain decisions. ADD researchers have turned mainly to SDT (Biros, George, & Zmud, ; Burgoon et al, , ; Elaad, ; Ho, Hancock, Booth, & Liu, ; Meijer, Selle, Elber, & Ben‐Shakhar, ; Twyman, Lowry, Burgoon, & Nunamaker, ) to help explain the trade‐offs inherent in uncertain decision‐making. SDT mainly concerns itself with two aspects of decision‐making under uncertainty for comparing different detection mechanisms, the accuracy of the classifier and the decision threshold.…”

Section: Introductionmentioning

confidence: 99%

“…Since then, authors have studied additional tools, software features, and perhaps most importantly, real‐world samples. Among those additional tools are ocular‐motor measures of deception, which were also the focus of multiple studies (Cook et al, ; Kircher & Raskin, ; Twyman et al, ). Brain fingerprinting (Farwell et al, ), vocal cognitive‐dissonance measures (Hobson et al, ), the polygraph (Honts & Amato, ), temperature signals (Tsiamyrtzis et al, ), and thermal skin imaging studies have also been conducted.…”

Section: Introductionmentioning

confidence: 99%

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Advancing the assessment of automated deception detection systems: Incorporating base rate and cost into system evaluation

Twitchell

Fuller

2018

Information Systems Journal

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In the last two decades, there has been an increased interest in automated deception detection systems (ADDs) for use in screening, although little attention has been paid to the usefulness of these systems. ADDs use various means, both invasive and non-invasive, to ascertain individual intent to deceive or engage in malicious behaviour. Many papers introducing ADDs use signal detection theory to compare a technique's ability to detect malicious intent with other techniques, but in doing so, they do not include contextual information such as base rate and cost. In this paper, we aim to improve future research by showing how the inclusion of contextual information provides a more realistic picture of the research. Through both theoretical arguments and a real-data example, we show that especially for those contexts where malicious intent is infrequent (ie, with low base rates of deception) that not factoring in the base rate overestimates the accuracy and therefore usefulness. We conclude with recommendations for how future research should provide a fuller picture of the accuracy and usefulness of ADDs.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Advancing the assessment of automated deception detection systems: Incorporating base rate and cost into system evaluation

Twitchell

Fuller

2018

Information Systems Journal

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“…Such studies include [2], [3], [4], [5], [6], [7], [8], [9], [10], [11]. All of these studies mention "prediction," "predictor," "predicting," or "predict," but not one of them describes or reports the actual test of any prediction.…”

Section: Figurementioning

confidence: 99%

Three Roles for Statistical Significance and the Validity Frontier in Theory Testing

Lee¹,

Mohajeri²,

Hubona

2017

Proceedings of the 50th Hawaii International Conference on System Sciences (2017)

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“…Recently proposed credibility assessment systems are capable of detecting individuals' purposely hidden information (Twyman et al, 2014). These systems synthesize the understanding of orienting and defensive responses, structured interviewing, and non-invasive psychophysiological and behavioral measurements (Twyman et al, 2014). Whereas many promising methods can assist deception detection, selecting valuable input variables remains unavoidable in enhancing their performance.…”

Section: Deception and Technologymentioning

confidence: 99%

“…Proposals have also been made for automated deception detection (Zhou et al, 2004). Recently proposed credibility assessment systems are capable of detecting individuals' purposely hidden information (Twyman et al, 2014). These systems synthesize the understanding of orienting and defensive responses, structured interviewing, and non-invasive psychophysiological and behavioral measurements (Twyman et al, 2014).…”

Section: Deception and Technologymentioning

confidence: 99%

Manipulative Imputation in Distributed Decision Support Settings: The Implications of Information Asymmetry and Aggregation Complexity

Malekovic¹,

Sutanto

Goutas

2016

Decision Support Systems

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According to earlier research, distributed decision support structures are susceptible to deception. We complement the existing works by analyzing group members' attempts to manipulate group decisions supported by distributed communications. Experimentally, we manipulated two systemic features of a distributed support structure: the members' information asymmetry and decision rule complexity. Both of these features refer to structural properties of aggregated information exchange. We confirmed several hypothesized effects: An increase in the information asymmetry in the aggregation of information increases the incidence of the members' manipulative tendency. It also increases the effectiveness of the members' manipulative imputations. However, the complexity of a decision rule negatively moderates both of these effects. We point out the theoretical relevance and managerial implications of our findings. We conclude that managing team members' information asymmetry and complexity of issues under their practical consideration may result in valuable disclosures.

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Autonomous Scientifically Controlled Screening Systems for Detecting Information Purposely Concealed by Individuals

Cited by 49 publications

References 59 publications

Advancing the assessment of automated deception detection systems: Incorporating base rate and cost into system evaluation

Advancing the assessment of automated deception detection systems: Incorporating base rate and cost into system evaluation

Three Roles for Statistical Significance and the Validity Frontier in Theory Testing

Manipulative Imputation in Distributed Decision Support Settings: The Implications of Information Asymmetry and Aggregation Complexity

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