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Looking for Lies An Exploratory Analysis for Automated Detection of Deception / MAREK N. POSARD, CHRISTIAN JOHNSON, JULIA L. MELIN, EMILY ELLINGER, HILARY REININGER.
- Format:
- Book
- Author/Creator:
- Posard, Marek
- Language:
- English
- Subjects (All):
- Machine learning--Technique.
- Machine learning.
- Deception--United States.
- Deception.
- Natural language processing (Computer science).
- Security clearances--United States.
- Security clearances.
- United States.
- Physical Description:
- x, 81 pages : illustrations ; 26 cm
- Place of Publication:
- Santa Monica, CA : RAND, 2022
- System Details:
- Mode of access: internet via WWW.
- Summary:
- Security clearance investigations are onerous for both the applicants and investigators, and such investigations are expensive for the U.S. government. In this report, the authors present results from an exploratory analysis that tests automated tools for detecting when some of these applicants attempt to deceive the government during the interview portion of this process. How interviewees answer interview questions could be a useful signal to detect when they are trying to be deceptive.
- Contents:
- CHAPTER ONE: Introduction
- CHAPTER TWO: Relevant Background Literature
- CHAPTER THREE: Description of Data
- CHAPTER FOUR: Results from Analysis of Interview Data
- CHAPTER FIVE: Potential Sources of Bias
- CHAPTER SIX: Limitations, Conclusions, and Recommendations
- APPENDIX A: Modified Cognitive Interviewing
- APPENDIX B: Study Materials
- APPENDIX C: Example Output from Amazon Web Services Transcribe
- APPENDIX D: Proof of Concept: Deep Learning Contradiction Model.
- Notes:
- Title from PDF document (title page; viewed October 19, 2022)
- "RAND NATIONAL DEFENSE RESEARCH INSTITUTE"
- "Prepared for the Performance Accountability Council Program Management Office"
- Includes bibliographical references (pages 77-81)
- See also RAND/RB-A873-1
- Description based on electronic resource
- ISBN:
- 1977409520
- 9781977409522
- OCLC:
- 1350383416
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