Author
Listed:
- Konstantinos Kalodanis
(Department of Informatics & Telematics, Harokopio University of Athens, 17778 Athens, Greece)
- Panagiotis Rizomiliotis
(Department of Informatics & Telematics, Harokopio University of Athens, 17778 Athens, Greece)
- Georgios Feretzakis
(School of Science and Technology, Hellenic Open University, 26335 Patras, Greece)
- Charalampos Papapavlou
(Department of Electrical & Computer Engineering, University of Patras, 26504 Patras, Greece)
- Dimosthenis Anagnostopoulos
(Department of Informatics & Telematics, Harokopio University of Athens, 17778 Athens, Greece)
Abstract
Integrating artificial intelligence into border control systems may help to strengthen security and make operations more efficient. For example, the emerging application of artificial intelligence for lie detection when inspecting passengers presents significant opportunities for future implementation. However, as it makes use of technology that is associated with artificial intelligence, the system is classified as high risk, in accordance with the EU AI Act and, therefore, must adhere to rigorous regulatory requirements to mitigate potential risks. This manuscript distinctly amalgamates the technical, ethical, and legal aspects, thereby offering an extensive examination of the AI-based lie detection systems utilized in border security. This academic paper is uniquely set apart from others because it undertakes a thorough investigation into the categorization of these emerging technologies in terms of the regulatory framework established by the EU AI Act, which classifies them as high risk. It further makes an assessment of practical case studies, including notable examples such as iBorderCtrl and AVATAR. This in-depth analysis seeks to emphasize not only the enormous challenges ahead for practitioners but also the progress made in this emerging field of study. Furthermore, it seeks to investigate threats, vulnerabilities, and privacy concerns associated with AI, while providing security controls to address difficulties related to lie detection. Finally, we propose a framework that encompasses the EU AI Act’s principles and serves as a foundation for future approaches and research projects. By analyzing current methodologies and considering future directions, the paper aims to provide a comprehensive understanding of the viability and consequences of deploying AI lie detection capabilities in border control.
Suggested Citation
Konstantinos Kalodanis & Panagiotis Rizomiliotis & Georgios Feretzakis & Charalampos Papapavlou & Dimosthenis Anagnostopoulos, 2025.
"High-Risk AI Systems—Lie Detection Application,"
Future Internet, MDPI, vol. 17(1), pages 1-23, January.
Handle:
RePEc:gam:jftint:v:17:y:2025:i:1:p:26-:d:1562381
Download full text from publisher
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jftint:v:17:y:2025:i:1:p:26-:d:1562381. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.