Interviewing and deception detection techniques for rapid screening and credibility assessment
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Interviewing and Deception Detection Techniques for Rapid Screening and Credibility Assessment. Dr. Jay F. Nunamaker, Jr. Dr. Judee K. Burgoon. Agenda. Introduction Project Phases Project Plan Year One: Unique Datasets Year One: Sensors and Tools Year One: Tasks

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Interviewing and Deception Detection Techniques for Rapid Screening and Credibility Assessment

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Interviewing and Deception Detection Techniques for Rapid Screening and Credibility Assessment

Dr. Jay F. Nunamaker, Jr.

Dr. Judee K. Burgoon


Agenda

  • Introduction

  • Project Phases

  • Project Plan

    • Year One: Unique Datasets

    • Year One: Sensors and Tools

    • Year One: Tasks

      • Analysis Psycho-Physiological Datasets

      • Lexical Analysis

      • Interoperable Video Database

      • Collaborative Credibility Assessment Tools

  • Conclusion


Introduction

  • Identify verbal/non-verbal behaviors and physiological cues that indicate deception and hostile intentions in rapid screening environments

  • Experimental research to evaluate and develop automated deception detection technology

  • Develop questioning and information elicitation strategies for border screeners


Project Phases

  • Experimentation and analysis of credibility assessment tools

    • Test new deception detection technology which incorporate verbal/non-verbal behavior and physiological measures

    • Prototype automated systems and enabling technologies for detecting deception

    • Replicate knowledge learned in experiments in the field

    • Analysis of interviewing techniques in screening scenarios

    • Techniques for information elicitation

    • Behavioral analysis and questioning strategies

  • Screening and border specific analysis of detection methods

    • Unobtrusive methods for behavior monitoring and deception detection

    • Interview and screening techniques


Project Plan


Project Plan – Year 1Unique Datasets

  • Datasets for original analysis:

    • Cultural Benchmarks

      • 220 international participants

      • Professionally interviewed (25 questions)

      • Lie or truth instructions

    • Mock Crime

      • 134 participants

      • Realistic Mock theft

        scenario

  • New Proposed Experiments


Project Plan – Year 1Mock Crime: Experiment Example

Stage 1: Subject arrival at separate building

Stage 2: Subject receives instructions by recording

Stage 4: Subject completes credibility interview about involvement in theft

Stage 3: Subject arrives at secretary’s office to steal ring


Project Plan – Year 1Sensors and Tools

  • PUPILOMETRY

  • EYE-TRACKING

  • KINESIC

Equipment supplied by:


Project Plan – Year 1 Task 1: Analysis Psycho-Physiological Datasets

  • Phase 1: LDV Data Analysis (Year 1)

    • Unintentionally leaked psycho-physiological cues may be indicative of deceptive behavior

    • “Cultural Benchmarks” experiment captured Pulse and Respiration data via LDV

    • Determine if the LDV can provide cues that are indicative of deception

  • Phase 2: Data from multi-sensors (Year 2)

    • Cultural Benchmarks Experiment – sensor data analyzed individually – not looked at collectively

      • Pulse Respiration, Kinesics (Blob, ASM, Gestures, Blinking, Pose), and Pupilometry

  • Phase 3: Data-fusion techniques (Year 2)

    • How do we fuse data from distinct sources?

    • Do fusion techniques provide greater accuracy in detecting deception?


Milestones and Deliverables

*Year one deliverables in green


Project Plan – Year 1Task 2: Lexical Analysis

  • “words whose job it is to make things more or less fuzzy” (Lakoff, 1972)

  • e.g. perhaps, might, maybe, approximately

  • Communicates speaker’s degree of confidence (Hyland, 1998; Coates, 1987)

  • Reduces strength of a statement (Zucker & Zucker, 1986)

  • Expresses tentativeness and probability

  • Theoretically linked to deception use


Milestones and Deliverables

*Year one deliverables in green


Project Plan – Year 1Task 3: Interoperable Video Database

Currently have many large, disparate data sources. Challenges in managing large and diverse data sets include:

  • Integrating the datasets efficiently

  • Querying integrated data sets intelligently

    • Example: Retrieve all data associated w/specific gesture

  • Capturing tacit information

  • Determining the elementary/composite data elements

  • Creating semantic interoperability across the datasets

    In order to begin addressing these

    challenges, we need to begin to create a

    framework which will help us understand

    the datasets and how to manage

    them holistically.

Retrieve all data associated with shrugs

Cultural Benchmarks Interviews

Mock Crime Interviews


Milestones and Deliverables

*Year one deliverables in green


Project Plan – Year 1Task 4: Collaborative Credibility Assessment Tools

Problem: Individuals are not as accurate as machines in credibility assessment

Proposal: Use group collaboration to discover more cues to deception

First phase Deliverable: Determine feasibility of and requirements for collaboration tools for credibility assessment. Create prototype(s)


Milestones and Deliverables

*Year one deliverables in green


Conclusion

  • Identify verbal/non-verbal behaviors and physiological cues that indicate deception and hostile intentions in rapid screening environments

  • Experimental research using unique datasets to evaluate and develop:

    • Automated deception detection technology

    • Experimental research to evaluate and develop automated deception detection technology

  • Four proposed tasks with deliverables in Year One


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