Details
| Original language | English |
|---|---|
| Title of host publication | Computational Intelligence |
| Subtitle of host publication | International Joint Conference, IJCCI 2018, Revised Selected Papers |
| Editors | Christophe Sabourin, Juan Julián Merelo, Alejandro Linares Barranco, Kurosh Madani, Kevin Warwick |
| Pages | 19-45 |
| Number of pages | 27 |
| ISBN (electronic) | 978-3-030-64731-5 |
| Publication status | Published - 23 Mar 2021 |
| Event | 10th International Joint Conference on Computational Intelligence, IJCCI 2018 - Seville, Spain Duration: 18 Sept 2018 → 20 Sept 2018 Conference number: 10 |
Publication series
| Name | Studies in Computational Intelligence |
|---|---|
| Volume | 893 |
| ISSN (Print) | 1860-949X |
| ISSN (electronic) | 1860-9503 |
Abstract
Adaptive Psychological Profiling systems use artificial intelligence algorithms to analyze a person’s non-verbal behavior in order to determine a specific mental state such as deception. One such system known as, Silent Talker, combines image processing and artificial neural networks to classify multiple non-verbal signals mainly from the face during a verbal exchange i.e. interview, to produce an accurate and comprehensive time-based profile of a subject’s psychological state. Artificial neural networks are typically black-box algorithms; hence, it is difficult to understand how the classification of a person’s behaviour is obtained. The new European Data Protection Legislation (GDPR), states that individuals who are automatically profiled, have the right to an explanation of how the “machine” reached its decision and receive meaningful information on the logic involved in how that decision was reached. This is practically difficult from a technical perspective, whereas from a legal point of view, it remains unclear whether this is sufficient to safeguard the data subject’s rights. This chapter is an extended version of a previous published paper in IJCCI 2019 [35] which examines the new European Data Protection Legislation and how it impacts on an application of psychological profiling within an Automated Deception Detection System (ADDS) which is one component of a smart border control system known as iBorderCtrl. ADDS detects deception through an avatar border guard interview, during a participants’ pre-registration, to demonstrate the challenges faced in trying to obtain explainable decisions from models derived through computational intelligence techniques. The chapter concludes by examining the future of explainable decision making through proposing a new Hierarchy of Explainability and Empowerment that allows information and decision-making complexity to be explained at different levels depending on a person’s abilities.
Keywords
- Artificial neural networks, Deception detection, Decision trees, GDPR, Psychological profiling
ASJC Scopus subject areas
- Computer Science(all)
- Artificial Intelligence
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Computational Intelligence: International Joint Conference, IJCCI 2018, Revised Selected Papers. ed. / Christophe Sabourin; Juan Julián Merelo; Alejandro Linares Barranco; Kurosh Madani; Kevin Warwick. 2021. p. 19-45 (Studies in Computational Intelligence; Vol. 893).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Reconciling Adapted Psychological Profiling with the New European Data Protection Legislation
AU - Crockett, Keeley
AU - Stoklas, Jonathan
AU - O’Shea, James
AU - Krügel, Tina
AU - Khan, Wasiq
N1 - Conference code: 10
PY - 2021/3/23
Y1 - 2021/3/23
N2 - Adaptive Psychological Profiling systems use artificial intelligence algorithms to analyze a person’s non-verbal behavior in order to determine a specific mental state such as deception. One such system known as, Silent Talker, combines image processing and artificial neural networks to classify multiple non-verbal signals mainly from the face during a verbal exchange i.e. interview, to produce an accurate and comprehensive time-based profile of a subject’s psychological state. Artificial neural networks are typically black-box algorithms; hence, it is difficult to understand how the classification of a person’s behaviour is obtained. The new European Data Protection Legislation (GDPR), states that individuals who are automatically profiled, have the right to an explanation of how the “machine” reached its decision and receive meaningful information on the logic involved in how that decision was reached. This is practically difficult from a technical perspective, whereas from a legal point of view, it remains unclear whether this is sufficient to safeguard the data subject’s rights. This chapter is an extended version of a previous published paper in IJCCI 2019 [35] which examines the new European Data Protection Legislation and how it impacts on an application of psychological profiling within an Automated Deception Detection System (ADDS) which is one component of a smart border control system known as iBorderCtrl. ADDS detects deception through an avatar border guard interview, during a participants’ pre-registration, to demonstrate the challenges faced in trying to obtain explainable decisions from models derived through computational intelligence techniques. The chapter concludes by examining the future of explainable decision making through proposing a new Hierarchy of Explainability and Empowerment that allows information and decision-making complexity to be explained at different levels depending on a person’s abilities.
AB - Adaptive Psychological Profiling systems use artificial intelligence algorithms to analyze a person’s non-verbal behavior in order to determine a specific mental state such as deception. One such system known as, Silent Talker, combines image processing and artificial neural networks to classify multiple non-verbal signals mainly from the face during a verbal exchange i.e. interview, to produce an accurate and comprehensive time-based profile of a subject’s psychological state. Artificial neural networks are typically black-box algorithms; hence, it is difficult to understand how the classification of a person’s behaviour is obtained. The new European Data Protection Legislation (GDPR), states that individuals who are automatically profiled, have the right to an explanation of how the “machine” reached its decision and receive meaningful information on the logic involved in how that decision was reached. This is practically difficult from a technical perspective, whereas from a legal point of view, it remains unclear whether this is sufficient to safeguard the data subject’s rights. This chapter is an extended version of a previous published paper in IJCCI 2019 [35] which examines the new European Data Protection Legislation and how it impacts on an application of psychological profiling within an Automated Deception Detection System (ADDS) which is one component of a smart border control system known as iBorderCtrl. ADDS detects deception through an avatar border guard interview, during a participants’ pre-registration, to demonstrate the challenges faced in trying to obtain explainable decisions from models derived through computational intelligence techniques. The chapter concludes by examining the future of explainable decision making through proposing a new Hierarchy of Explainability and Empowerment that allows information and decision-making complexity to be explained at different levels depending on a person’s abilities.
KW - Artificial neural networks
KW - Deception detection
KW - Decision trees
KW - GDPR
KW - Psychological profiling
UR - http://www.scopus.com/inward/record.url?scp=85104732517&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-64731-5_2
DO - 10.1007/978-3-030-64731-5_2
M3 - Conference contribution
AN - SCOPUS:85104732517
SN - 978-3-030-64730-8
T3 - Studies in Computational Intelligence
SP - 19
EP - 45
BT - Computational Intelligence
A2 - Sabourin, Christophe
A2 - Merelo, Juan Julián
A2 - Barranco, Alejandro Linares
A2 - Madani, Kurosh
A2 - Warwick, Kevin
T2 - 10th International Joint Conference on Computational Intelligence, IJCCI 2018
Y2 - 18 September 2018 through 20 September 2018
ER -