Slide
Centre Interdisciplinaire
de Recherche et d’Innovation
en Cybersécurité et Société
de Recherche et d’Innovation
en Cybersécurité et Société
1.
Côté, L.; Lamontagne, J.; Bellerose, A.; Blais, C.; Fiset, D.
The eyes are central to face detection: revisiting the foundations of face processing Journal Article
In: Vision Research, vol. 243, 2026, ISSN: 00426989 (ISSN).
Abstract | Links | BibTeX | Tags: adult, article, Black person, Bubbles, Categorization, Caucasian, Detection, emotion assessment, Faces, Facial Recognition, facies, female, human, human experiment, Image analysis, information processing, Information use, male, Noise, normal human, perception, Prosopagnosia, spatial frequency discrimination, task performance, visual discrimination, Young Adult
@article{cote_eyes_2026,
title = {The eyes are central to face detection: revisiting the foundations of face processing},
author = {L. Côté and J. Lamontagne and A. Bellerose and C. Blais and D. Fiset},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105030389147&doi=10.1016%2Fj.visres.2026.108785&partnerID=40&md5=752aa5d9923ac60539e36118ad41e1e6},
doi = {10.1016/j.visres.2026.108785},
issn = {00426989 (ISSN)},
year = {2026},
date = {2026-01-01},
journal = {Vision Research},
volume = {243},
abstract = {Face detection feels effortless, yet it requires finely tuned computations to extract socially meaningful signals from the visual stream. Here, we used the Bubbles method to isolate the facial features and spatial frequency information that support face categorization. Across three experiments varying in task demands and visual context, the eye region consistently emerged as the most diagnostic source of information, particularly in high spatial frequencies. This finding held whether participants distinguished faces from noise, from non-face objects, or from real-world categories—suggesting that the eyes serve as an anchor point for categorization across contexts. Strikingly, this diagnostic profile mirrors that found in face identification tasks, implying that detection and recognition may rely on shared perceptual mechanisms rather than sequential, independent processes. This overlap sheds light on longstanding ambiguities in the prosopagnosia literature, indicating that detection impairments found in patients may stem from a broader failure to extract critical eye information. More broadly, our results invite a rethinking of the early stages of face processing, suggesting that detection already involves selective use of diagnostic facial features that supports recognition, emotional decoding, and social perception. © 2026 The Author(s).},
keywords = {adult, article, Black person, Bubbles, Categorization, Caucasian, Detection, emotion assessment, Faces, Facial Recognition, facies, female, human, human experiment, Image analysis, information processing, Information use, male, Noise, normal human, perception, Prosopagnosia, spatial frequency discrimination, task performance, visual discrimination, Young Adult},
pubstate = {published},
tppubtype = {article}
}
Face detection feels effortless, yet it requires finely tuned computations to extract socially meaningful signals from the visual stream. Here, we used the Bubbles method to isolate the facial features and spatial frequency information that support face categorization. Across three experiments varying in task demands and visual context, the eye region consistently emerged as the most diagnostic source of information, particularly in high spatial frequencies. This finding held whether participants distinguished faces from noise, from non-face objects, or from real-world categories—suggesting that the eyes serve as an anchor point for categorization across contexts. Strikingly, this diagnostic profile mirrors that found in face identification tasks, implying that detection and recognition may rely on shared perceptual mechanisms rather than sequential, independent processes. This overlap sheds light on longstanding ambiguities in the prosopagnosia literature, indicating that detection impairments found in patients may stem from a broader failure to extract critical eye information. More broadly, our results invite a rethinking of the early stages of face processing, suggesting that detection already involves selective use of diagnostic facial features that supports recognition, emotional decoding, and social perception. © 2026 The Author(s).
2.
Côté, L.; Lamontagne, J.; Bellerose, A.; Blais, C.; Fiset, D.
The eyes are central to face detection: revisiting the foundations of face processing Journal Article
In: Vision Research, vol. 243, 2026, ISSN: 00426989 (ISSN).
Abstract | Links | BibTeX | Tags: adult, article, Black person, Bubbles, Categorization, Caucasian, Detection, emotion assessment, Eye, Face, Faces, Facial Recognition, facies, female, human, human experiment, Humans, Image analysis, information processing, Information use, male, Noise, normal human, Pattern Recognition, perception, Photic Stimulation, photostimulation, physiology, procedures, Prosopagnosia, psychology, recognition, Social Perception, spatial frequency discrimination, task performance, Visual, visual discrimination, visual pattern recognition, Young Adult
@article{coteEyesAreCentral2026,
title = {The eyes are central to face detection: revisiting the foundations of face processing},
author = {L. Côté and J. Lamontagne and A. Bellerose and C. Blais and D. Fiset},
url = {https://www.scopus.com/pages/publications/105030389147?origin=resultslist},
doi = {10.1016/j.visres.2026.108785},
issn = {00426989 (ISSN)},
year = {2026},
date = {2026-01-01},
journal = {Vision Research},
volume = {243},
publisher = {Elsevier Ltd},
abstract = {Face detection feels effortless, yet it requires finely tuned computations to extract socially meaningful signals from the visual stream. Here, we used the Bubbles method to isolate the facial features and spatial frequency information that support face categorization. Across three experiments varying in task demands and visual context, the eye region consistently emerged as the most diagnostic source of information, particularly in high spatial frequencies. This finding held whether participants distinguished faces from noise, from non-face objects, or from real-world categories—suggesting that the eyes serve as an anchor point for categorization across contexts. Strikingly, this diagnostic profile mirrors that found in face identification tasks, implying that detection and recognition may rely on shared perceptual mechanisms rather than sequential, independent processes. This overlap sheds light on longstanding ambiguities in the prosopagnosia literature, indicating that detection impairments found in patients may stem from a broader failure to extract critical eye information. More broadly, our results invite a rethinking of the early stages of face processing, suggesting that detection already involves selective use of diagnostic facial features that supports recognition, emotional decoding, and social perception. © 2026 The Author(s).},
keywords = {adult, article, Black person, Bubbles, Categorization, Caucasian, Detection, emotion assessment, Eye, Face, Faces, Facial Recognition, facies, female, human, human experiment, Humans, Image analysis, information processing, Information use, male, Noise, normal human, Pattern Recognition, perception, Photic Stimulation, photostimulation, physiology, procedures, Prosopagnosia, psychology, recognition, Social Perception, spatial frequency discrimination, task performance, Visual, visual discrimination, visual pattern recognition, Young Adult},
pubstate = {published},
tppubtype = {article}
}
Face detection feels effortless, yet it requires finely tuned computations to extract socially meaningful signals from the visual stream. Here, we used the Bubbles method to isolate the facial features and spatial frequency information that support face categorization. Across three experiments varying in task demands and visual context, the eye region consistently emerged as the most diagnostic source of information, particularly in high spatial frequencies. This finding held whether participants distinguished faces from noise, from non-face objects, or from real-world categories—suggesting that the eyes serve as an anchor point for categorization across contexts. Strikingly, this diagnostic profile mirrors that found in face identification tasks, implying that detection and recognition may rely on shared perceptual mechanisms rather than sequential, independent processes. This overlap sheds light on longstanding ambiguities in the prosopagnosia literature, indicating that detection impairments found in patients may stem from a broader failure to extract critical eye information. More broadly, our results invite a rethinking of the early stages of face processing, suggesting that detection already involves selective use of diagnostic facial features that supports recognition, emotional decoding, and social perception. © 2026 The Author(s).
3.
Côté, L.; Lamontagne, J.; Bellerose, A.; Blais, C.; Fiset, D.
The eyes are central to face detection: revisiting the foundations of face processing Journal Article
In: Vision Research, vol. 243, 2026, ISSN: 00426989 (ISSN).
Abstract | Links | BibTeX | Tags: adult, article, Black person, Bubbles, Categorization, Caucasian, Detection, emotion assessment, Faces, Facial Recognition, facies, female, human, human experiment, Image analysis, information processing, Information use, male, Noise, normal human, perception, Prosopagnosia, spatial frequency discrimination, task performance, visual discrimination, Young Adult
@article{coteEyesAreCentral2026a,
title = {The eyes are central to face detection: revisiting the foundations of face processing},
author = {L. Côté and J. Lamontagne and A. Bellerose and C. Blais and D. Fiset},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105030389147&doi=10.1016%2Fj.visres.2026.108785&partnerID=40&md5=752aa5d9923ac60539e36118ad41e1e6},
doi = {10.1016/j.visres.2026.108785},
issn = {00426989 (ISSN)},
year = {2026},
date = {2026-01-01},
journal = {Vision Research},
volume = {243},
abstract = {Face detection feels effortless, yet it requires finely tuned computations to extract socially meaningful signals from the visual stream. Here, we used the Bubbles method to isolate the facial features and spatial frequency information that support face categorization. Across three experiments varying in task demands and visual context, the eye region consistently emerged as the most diagnostic source of information, particularly in high spatial frequencies. This finding held whether participants distinguished faces from noise, from non-face objects, or from real-world categories—suggesting that the eyes serve as an anchor point for categorization across contexts. Strikingly, this diagnostic profile mirrors that found in face identification tasks, implying that detection and recognition may rely on shared perceptual mechanisms rather than sequential, independent processes. This overlap sheds light on longstanding ambiguities in the prosopagnosia literature, indicating that detection impairments found in patients may stem from a broader failure to extract critical eye information. More broadly, our results invite a rethinking of the early stages of face processing, suggesting that detection already involves selective use of diagnostic facial features that supports recognition, emotional decoding, and social perception. © 2026 The Author(s).},
keywords = {adult, article, Black person, Bubbles, Categorization, Caucasian, Detection, emotion assessment, Faces, Facial Recognition, facies, female, human, human experiment, Image analysis, information processing, Information use, male, Noise, normal human, perception, Prosopagnosia, spatial frequency discrimination, task performance, visual discrimination, Young Adult},
pubstate = {published},
tppubtype = {article}
}
Face detection feels effortless, yet it requires finely tuned computations to extract socially meaningful signals from the visual stream. Here, we used the Bubbles method to isolate the facial features and spatial frequency information that support face categorization. Across three experiments varying in task demands and visual context, the eye region consistently emerged as the most diagnostic source of information, particularly in high spatial frequencies. This finding held whether participants distinguished faces from noise, from non-face objects, or from real-world categories—suggesting that the eyes serve as an anchor point for categorization across contexts. Strikingly, this diagnostic profile mirrors that found in face identification tasks, implying that detection and recognition may rely on shared perceptual mechanisms rather than sequential, independent processes. This overlap sheds light on longstanding ambiguities in the prosopagnosia literature, indicating that detection impairments found in patients may stem from a broader failure to extract critical eye information. More broadly, our results invite a rethinking of the early stages of face processing, suggesting that detection already involves selective use of diagnostic facial features that supports recognition, emotional decoding, and social perception. © 2026 The Author(s).
4.
Nosrati, S.; Motaghi, H.
The AI Complacency Model: Integrating Bounded Rationality and Information Processing Proceedings Article
In: Am. Conf. Inf. Syst., AMCIS, pp. 4590–4599, Association for Information Systems, 2025, ISBN: 979-833132774-3 (ISBN).
Abstract | Links | BibTeX | Tags: AI complacency, AI systems, Artificial intelligence, Behavioral research, Bounded rationality, Cognitive bias, cognitive biases, decision-making, Decisions makings, Heuristic processing, Human computer interaction, Human-AI interaction, information processing, Information systems, Information use, Perceived AI reliability, Reliability theory, Systematic processing, Vigilance
@inproceedings{nosrati_ai_2025,
title = {The AI Complacency Model: Integrating Bounded Rationality and Information Processing},
author = {S. Nosrati and H. Motaghi},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105025349267&partnerID=40&md5=14d676bedd3ea18921ed24a830889a8b},
isbn = {979-833132774-3 (ISBN)},
year = {2025},
date = {2025-01-01},
booktitle = {Am. Conf. Inf. Syst., AMCIS},
volume = {7},
pages = {4590–4599},
publisher = {Association for Information Systems},
abstract = {This study addresses a critical gap in understanding why users exhibit reduced oversight when interacting with generative AI systems despite their known limitations. While existing research documents AI errors across domains, theoretical frameworks explaining the underlying psychological mechanisms remain underdeveloped. We propose a comprehensive model of AI complacency that extends beyond traditional automation complacency theories by integrating bounded rationality constraints with dual-process information processing models. Our framework demonstrates how Perceived AI Reliability triggers a shift from systematic to heuristic information processing, subsequently reducing vigilance and impairing task performance. The relationship between Perceived AI Reliability and information processing is moderated by three key factors derived from bounded rationality theory: knowledge limitations, cognitive processing capabilities, and time constraints. The proposed conceptual model of this study contributes to the literature by identifying unique psychological mechanisms underlying AI complacency, explaining the processing shifts in human-AI interaction, positioning vigilance as a critical mediating mechanism, and introducing the Vigilance-Reliability Matrix as a diagnostic tool for identifying different interaction patterns. This framework offers both theoretical insights and practical guidance for maintaining appropriate human oversight as AI systems become increasingly sophisticated and widespread across domains. Copyright © 2025 by Association for Information Systems (AIS). All rights reserved.},
keywords = {AI complacency, AI systems, Artificial intelligence, Behavioral research, Bounded rationality, Cognitive bias, cognitive biases, decision-making, Decisions makings, Heuristic processing, Human computer interaction, Human-AI interaction, information processing, Information systems, Information use, Perceived AI reliability, Reliability theory, Systematic processing, Vigilance},
pubstate = {published},
tppubtype = {inproceedings}
}
This study addresses a critical gap in understanding why users exhibit reduced oversight when interacting with generative AI systems despite their known limitations. While existing research documents AI errors across domains, theoretical frameworks explaining the underlying psychological mechanisms remain underdeveloped. We propose a comprehensive model of AI complacency that extends beyond traditional automation complacency theories by integrating bounded rationality constraints with dual-process information processing models. Our framework demonstrates how Perceived AI Reliability triggers a shift from systematic to heuristic information processing, subsequently reducing vigilance and impairing task performance. The relationship between Perceived AI Reliability and information processing is moderated by three key factors derived from bounded rationality theory: knowledge limitations, cognitive processing capabilities, and time constraints. The proposed conceptual model of this study contributes to the literature by identifying unique psychological mechanisms underlying AI complacency, explaining the processing shifts in human-AI interaction, positioning vigilance as a critical mediating mechanism, and introducing the Vigilance-Reliability Matrix as a diagnostic tool for identifying different interaction patterns. This framework offers both theoretical insights and practical guidance for maintaining appropriate human oversight as AI systems become increasingly sophisticated and widespread across domains. Copyright © 2025 by Association for Information Systems (AIS). All rights reserved.
5.
Blais, C.; Fiset, D.; Côté, L.; Ledrou-Paquet, V.; Charbonneau, I.
Conducting online visual psychophysics experiments: A replication assessment of two face processing studies Journal Article
In: Vision Research, vol. 233, 2025, ISSN: 00426989 (ISSN), (Publisher: Elsevier Ltd).
Abstract | Links | BibTeX | Tags: adult, article, cultural factor, experiment, Facial Recognition, female, geography, human, human experiment, Humans, information processing, laboratory, male, normal human, online system, Photic Stimulation, photostimulation, physiology, procedures, psychology, Psychophysics, recognition, stimulus response, vision, visual stimulation, Young Adult
@article{blais_conducting_2025,
title = {Conducting online visual psychophysics experiments: A replication assessment of two face processing studies},
author = {C. Blais and D. Fiset and L. Côté and V. Ledrou-Paquet and I. Charbonneau},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105004807446&doi=10.1016%2fj.visres.2025.108617&partnerID=40&md5=771b056e57c4d7a34ff7c56ce39a4bd2},
doi = {10.1016/j.visres.2025.108617},
issn = {00426989 (ISSN)},
year = {2025},
date = {2025-01-01},
journal = {Vision Research},
volume = {233},
publisher = {Elsevier Ltd},
abstract = {In vision sciences, researchers rigorously control the testing environment and the physical properties of stimuli, making it challenging to conduct visual perception experiments online. However, online research offers key advantages, including access to larger and more diverse participant samples, helping to address the problem of underpowered studies and to enhance the generalizability of results. In face recognition research, increasing diversity is essential, especially considering evidence that cultural and geographical factors influence basic visual face processing. The present study tested a new online platform, Pack & Go from VPixx Technologies, that supports experiments written in MATLAB and Python. Two face recognition experiments based on a data-driven psychophysical method involving real-time stimulus manipulation and relying on functions from the Psychtoolbox were tested. In Experiment 1, the visual information used for face recognition was compared across four conditions that gradually reduced experimental control over the testing environment and stimulus properties. In Experiment 2, the association between face recognition abilities and information utilization was measured online and compared to lab-based results. In both experiments, results obtained in the lab and online were highly similar, demonstrating the potential of online research for vision science. © 2025 The Author(s)},
note = {Publisher: Elsevier Ltd},
keywords = {adult, article, cultural factor, experiment, Facial Recognition, female, geography, human, human experiment, Humans, information processing, laboratory, male, normal human, online system, Photic Stimulation, photostimulation, physiology, procedures, psychology, Psychophysics, recognition, stimulus response, vision, visual stimulation, Young Adult},
pubstate = {published},
tppubtype = {article}
}
In vision sciences, researchers rigorously control the testing environment and the physical properties of stimuli, making it challenging to conduct visual perception experiments online. However, online research offers key advantages, including access to larger and more diverse participant samples, helping to address the problem of underpowered studies and to enhance the generalizability of results. In face recognition research, increasing diversity is essential, especially considering evidence that cultural and geographical factors influence basic visual face processing. The present study tested a new online platform, Pack & Go from VPixx Technologies, that supports experiments written in MATLAB and Python. Two face recognition experiments based on a data-driven psychophysical method involving real-time stimulus manipulation and relying on functions from the Psychtoolbox were tested. In Experiment 1, the visual information used for face recognition was compared across four conditions that gradually reduced experimental control over the testing environment and stimulus properties. In Experiment 2, the association between face recognition abilities and information utilization was measured online and compared to lab-based results. In both experiments, results obtained in the lab and online were highly similar, demonstrating the potential of online research for vision science. © 2025 The Author(s)
6.
Blais, C.; Fiset, D.; Côté, L.; Ledrou-Paquet, V.; Charbonneau, I.
Conducting online visual psychophysics experiments: A replication assessment of two face processing studies Journal Article
In: Vision Research, vol. 233, 2025, ISSN: 00426989 (ISSN).
Abstract | Links | BibTeX | Tags: adult, article, cultural factor, experiment, Facial Recognition, female, geography, human, human experiment, Humans, information processing, laboratory, male, normal human, online system, Photic Stimulation, photostimulation, physiology, procedures, psychology, Psychophysics, recognition, stimulus response, vision, visual stimulation, Young Adult
@article{blaisConductingOnlineVisual2025a,
title = {Conducting online visual psychophysics experiments: A replication assessment of two face processing studies},
author = {C. Blais and D. Fiset and L. Côté and V. Ledrou-Paquet and I. Charbonneau},
url = {https://www.scopus.com/pages/publications/105004807446?origin=resultslist},
doi = {10.1016/j.visres.2025.108617},
issn = {00426989 (ISSN)},
year = {2025},
date = {2025-01-01},
journal = {Vision Research},
volume = {233},
publisher = {Elsevier Ltd},
abstract = {In vision sciences, researchers rigorously control the testing environment and the physical properties of stimuli, making it challenging to conduct visual perception experiments online. However, online research offers key advantages, including access to larger and more diverse participant samples, helping to address the problem of underpowered studies and to enhance the generalizability of results. In face recognition research, increasing diversity is essential, especially considering evidence that cultural and geographical factors influence basic visual face processing. The present study tested a new online platform, Pack & Go from VPixx Technologies, that supports experiments written in MATLAB and Python. Two face recognition experiments based on a data-driven psychophysical method involving real-time stimulus manipulation and relying on functions from the Psychtoolbox were tested. In Experiment 1, the visual information used for face recognition was compared across four conditions that gradually reduced experimental control over the testing environment and stimulus properties. In Experiment 2, the association between face recognition abilities and information utilization was measured online and compared to lab-based results. In both experiments, results obtained in the lab and online were highly similar, demonstrating the potential of online research for vision science. © 2025 The Author(s)},
keywords = {adult, article, cultural factor, experiment, Facial Recognition, female, geography, human, human experiment, Humans, information processing, laboratory, male, normal human, online system, Photic Stimulation, photostimulation, physiology, procedures, psychology, Psychophysics, recognition, stimulus response, vision, visual stimulation, Young Adult},
pubstate = {published},
tppubtype = {article}
}
In vision sciences, researchers rigorously control the testing environment and the physical properties of stimuli, making it challenging to conduct visual perception experiments online. However, online research offers key advantages, including access to larger and more diverse participant samples, helping to address the problem of underpowered studies and to enhance the generalizability of results. In face recognition research, increasing diversity is essential, especially considering evidence that cultural and geographical factors influence basic visual face processing. The present study tested a new online platform, Pack & Go from VPixx Technologies, that supports experiments written in MATLAB and Python. Two face recognition experiments based on a data-driven psychophysical method involving real-time stimulus manipulation and relying on functions from the Psychtoolbox were tested. In Experiment 1, the visual information used for face recognition was compared across four conditions that gradually reduced experimental control over the testing environment and stimulus properties. In Experiment 2, the association between face recognition abilities and information utilization was measured online and compared to lab-based results. In both experiments, results obtained in the lab and online were highly similar, demonstrating the potential of online research for vision science. © 2025 The Author(s)
7.
Nosrati, S.; Motaghi, H.
The AI Complacency Model: Integrating Bounded Rationality and Information Processing Proceedings Article
In: Am. Conf. Inf. Syst., AMCIS, pp. 4590–4599, Association for Information Systems, 2025, ISBN: 979-833132774-3 (ISBN), (Journal Abbreviation: Am. Conf. Inf. Syst., AMCIS).
Abstract | Links | BibTeX | Tags: AI complacency, AI systems, Artificial intelligence, Behavioral research, Bounded rationality, Cognitive bias, cognitive biases, decision-making, Decisions makings, Heuristic processing, Human computer interaction, Human-AI interaction, information processing, Information systems, Information use, Perceived AI reliability, Reliability theory, Systematic processing, Vigilance
@inproceedings{nosratiAIComplacencyModel2025,
title = {The AI Complacency Model: Integrating Bounded Rationality and Information Processing},
author = {S. Nosrati and H. Motaghi},
url = {https://www.scopus.com/pages/publications/105025349267?origin=resultslist},
isbn = {979-833132774-3 (ISBN)},
year = {2025},
date = {2025-01-01},
booktitle = {Am. Conf. Inf. Syst., AMCIS},
volume = {7},
pages = {4590–4599},
publisher = {Association for Information Systems},
abstract = {This study addresses a critical gap in understanding why users exhibit reduced oversight when interacting with generative AI systems despite their known limitations. While existing research documents AI errors across domains, theoretical frameworks explaining the underlying psychological mechanisms remain underdeveloped. We propose a comprehensive model of AI complacency that extends beyond traditional automation complacency theories by integrating bounded rationality constraints with dual-process information processing models. Our framework demonstrates how Perceived AI Reliability triggers a shift from systematic to heuristic information processing, subsequently reducing vigilance and impairing task performance. The relationship between Perceived AI Reliability and information processing is moderated by three key factors derived from bounded rationality theory: knowledge limitations, cognitive processing capabilities, and time constraints. The proposed conceptual model of this study contributes to the literature by identifying unique psychological mechanisms underlying AI complacency, explaining the processing shifts in human-AI interaction, positioning vigilance as a critical mediating mechanism, and introducing the Vigilance-Reliability Matrix as a diagnostic tool for identifying different interaction patterns. This framework offers both theoretical insights and practical guidance for maintaining appropriate human oversight as AI systems become increasingly sophisticated and widespread across domains. Copyright © 2025 by Association for Information Systems (AIS). All rights reserved.},
note = {Journal Abbreviation: Am. Conf. Inf. Syst., AMCIS},
keywords = {AI complacency, AI systems, Artificial intelligence, Behavioral research, Bounded rationality, Cognitive bias, cognitive biases, decision-making, Decisions makings, Heuristic processing, Human computer interaction, Human-AI interaction, information processing, Information systems, Information use, Perceived AI reliability, Reliability theory, Systematic processing, Vigilance},
pubstate = {published},
tppubtype = {inproceedings}
}
This study addresses a critical gap in understanding why users exhibit reduced oversight when interacting with generative AI systems despite their known limitations. While existing research documents AI errors across domains, theoretical frameworks explaining the underlying psychological mechanisms remain underdeveloped. We propose a comprehensive model of AI complacency that extends beyond traditional automation complacency theories by integrating bounded rationality constraints with dual-process information processing models. Our framework demonstrates how Perceived AI Reliability triggers a shift from systematic to heuristic information processing, subsequently reducing vigilance and impairing task performance. The relationship between Perceived AI Reliability and information processing is moderated by three key factors derived from bounded rationality theory: knowledge limitations, cognitive processing capabilities, and time constraints. The proposed conceptual model of this study contributes to the literature by identifying unique psychological mechanisms underlying AI complacency, explaining the processing shifts in human-AI interaction, positioning vigilance as a critical mediating mechanism, and introducing the Vigilance-Reliability Matrix as a diagnostic tool for identifying different interaction patterns. This framework offers both theoretical insights and practical guidance for maintaining appropriate human oversight as AI systems become increasingly sophisticated and widespread across domains. Copyright © 2025 by Association for Information Systems (AIS). All rights reserved.
8.
Linnaranta, O.; Cardona, L. G.; Seon, Q.; Tukkiapik, A.; Outerbridge, J.; Bouchard, S.
In: Cognitive and Behavioral Practice, vol. 32, no. 4, pp. 513–525, 2025, ISSN: 10777229 (ISSN).
Abstract | Links | BibTeX | Tags: Adaptation, adult, article, behavior therapy, clinical article, cognitive behavioral therapy, cultural adaptation, cultural safety, emotion regulation, Environment, environmental exposure, female, health care quality, health service, human, information processing, Inuit, male, manipulative medicine, Mental health, mental health care access, participatory co-design, Problem solving, psychotherapist, psychotherapy, Quebec, software, virtual reality
@article{linnarantaViewsCulturallySafe2025,
title = {Views on a Culturally Safe Psychotherapeutic Treatment by Inuit in Quebec: Co-Design of Cognitive Behavioral Therapy Manual and Virtual Exposure Environments},
author = {O. Linnaranta and L. G. Cardona and Q. Seon and A. Tukkiapik and J. Outerbridge and S. Bouchard},
url = {https://www.scopus.com/pages/publications/85199212719?origin=resultslist},
doi = {10.1016/j.cbpra.2024.04.006},
issn = {10777229 (ISSN)},
year = {2025},
date = {2025-01-01},
journal = {Cognitive and Behavioral Practice},
volume = {32},
number = {4},
pages = {513–525},
publisher = {Elsevier Inc.},
abstract = {Cognitive-behavioral psychotherapy (CBT) can be combined with virtual reality (VR) to provide culturally safe and remotely delivered emotion regulation interventions. We conducted a co-design process of a CBT treatment manual and complementary VR environments for the Inuit populations from Nunavik. Here, we describe the knowledge gained during the adaptation process on the approach to mental well-being and psychotherapy. We followed qualitative, participatory, and research co-design methods. After an initial concept of VR-CBT, an advisory group made up of 7 adults identifying as or working with Inuit participated in 4 focus group meetings. A thematic analysis of the discussions was carried out. A non-symptom-focused approach with the therapist guiding the individual in empowerment and emotion management was accepted in the advisory group, replacing a symptom-focus. Several CBT in- and between-session techniques were seen critically or rejected, and time for working on a certain theme was increased. Some elements in the proposed landscape were rejected as unsafe, other elements added as culture-specific to increase safety. Future work should confirm broader acceptance and utility. Culturally specific factors play an essential role in acceptance of concepts and approaches used in psychotherapy. Accordingly, they can have an impact on acceptance and attendance in therapy. © 2024 Association for Behavioral and Cognitive Therapies. Published by Elsevier Ltd. This is an open access article under the CC BY license. http://creativecommons.org/licenses/by/4.0/},
keywords = {Adaptation, adult, article, behavior therapy, clinical article, cognitive behavioral therapy, cultural adaptation, cultural safety, emotion regulation, Environment, environmental exposure, female, health care quality, health service, human, information processing, Inuit, male, manipulative medicine, Mental health, mental health care access, participatory co-design, Problem solving, psychotherapist, psychotherapy, Quebec, software, virtual reality},
pubstate = {published},
tppubtype = {article}
}
Cognitive-behavioral psychotherapy (CBT) can be combined with virtual reality (VR) to provide culturally safe and remotely delivered emotion regulation interventions. We conducted a co-design process of a CBT treatment manual and complementary VR environments for the Inuit populations from Nunavik. Here, we describe the knowledge gained during the adaptation process on the approach to mental well-being and psychotherapy. We followed qualitative, participatory, and research co-design methods. After an initial concept of VR-CBT, an advisory group made up of 7 adults identifying as or working with Inuit participated in 4 focus group meetings. A thematic analysis of the discussions was carried out. A non-symptom-focused approach with the therapist guiding the individual in empowerment and emotion management was accepted in the advisory group, replacing a symptom-focus. Several CBT in- and between-session techniques were seen critically or rejected, and time for working on a certain theme was increased. Some elements in the proposed landscape were rejected as unsafe, other elements added as culture-specific to increase safety. Future work should confirm broader acceptance and utility. Culturally specific factors play an essential role in acceptance of concepts and approaches used in psychotherapy. Accordingly, they can have an impact on acceptance and attendance in therapy. © 2024 Association for Behavioral and Cognitive Therapies. Published by Elsevier Ltd. This is an open access article under the CC BY license. http://creativecommons.org/licenses/by/4.0/
9.
Blais, C.; Fiset, D.; Côté, L.; Ledrou-Paquet, V.; Charbonneau, I.
Conducting online visual psychophysics experiments: A replication assessment of two face processing studies Journal Article
In: Vision Research, vol. 233, 2025, ISSN: 00426989 (ISSN).
Abstract | Links | BibTeX | Tags: adult, article, cultural factor, experiment, Facial Recognition, female, geography, human, human experiment, Humans, information processing, laboratory, male, normal human, online system, Photic Stimulation, photostimulation, physiology, procedures, psychology, Psychophysics, recognition, stimulus response, vision, visual stimulation, Young Adult
@article{blaisConductingOnlineVisual2025b,
title = {Conducting online visual psychophysics experiments: A replication assessment of two face processing studies},
author = {C. Blais and D. Fiset and L. Côté and V. Ledrou-Paquet and I. Charbonneau},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105004807446&doi=10.1016%2Fj.visres.2025.108617&partnerID=40&md5=6f27d81d289529b733b5aa0b03634f27},
doi = {10.1016/j.visres.2025.108617},
issn = {00426989 (ISSN)},
year = {2025},
date = {2025-01-01},
journal = {Vision Research},
volume = {233},
abstract = {In vision sciences, researchers rigorously control the testing environment and the physical properties of stimuli, making it challenging to conduct visual perception experiments online. However, online research offers key advantages, including access to larger and more diverse participant samples, helping to address the problem of underpowered studies and to enhance the generalizability of results. In face recognition research, increasing diversity is essential, especially considering evidence that cultural and geographical factors influence basic visual face processing. The present study tested a new online platform, Pack & Go from VPixx Technologies, that supports experiments written in MATLAB and Python. Two face recognition experiments based on a data-driven psychophysical method involving real-time stimulus manipulation and relying on functions from the Psychtoolbox were tested. In Experiment 1, the visual information used for face recognition was compared across four conditions that gradually reduced experimental control over the testing environment and stimulus properties. In Experiment 2, the association between face recognition abilities and information utilization was measured online and compared to lab-based results. In both experiments, results obtained in the lab and online were highly similar, demonstrating the potential of online research for vision science. © 2025 The Author(s)},
keywords = {adult, article, cultural factor, experiment, Facial Recognition, female, geography, human, human experiment, Humans, information processing, laboratory, male, normal human, online system, Photic Stimulation, photostimulation, physiology, procedures, psychology, Psychophysics, recognition, stimulus response, vision, visual stimulation, Young Adult},
pubstate = {published},
tppubtype = {article}
}
In vision sciences, researchers rigorously control the testing environment and the physical properties of stimuli, making it challenging to conduct visual perception experiments online. However, online research offers key advantages, including access to larger and more diverse participant samples, helping to address the problem of underpowered studies and to enhance the generalizability of results. In face recognition research, increasing diversity is essential, especially considering evidence that cultural and geographical factors influence basic visual face processing. The present study tested a new online platform, Pack & Go from VPixx Technologies, that supports experiments written in MATLAB and Python. Two face recognition experiments based on a data-driven psychophysical method involving real-time stimulus manipulation and relying on functions from the Psychtoolbox were tested. In Experiment 1, the visual information used for face recognition was compared across four conditions that gradually reduced experimental control over the testing environment and stimulus properties. In Experiment 2, the association between face recognition abilities and information utilization was measured online and compared to lab-based results. In both experiments, results obtained in the lab and online were highly similar, demonstrating the potential of online research for vision science. © 2025 The Author(s)
10.
Nosrati, S.; Motaghi, H.
The AI Complacency Model: Integrating Bounded Rationality and Information Processing Proceedings Article
In: Am. Conf. Inf. Syst., AMCIS, pp. 4590–4599, Association for Information Systems, 2025, ISBN: 979-833132774-3 (ISBN).
Abstract | Links | BibTeX | Tags: AI complacency, AI systems, Artificial intelligence, Behavioral research, Bounded rationality, Cognitive bias, cognitive biases, decision-making, Decisions makings, Heuristic processing, Human computer interaction, Human-AI interaction, information processing, Information systems, Information use, Perceived AI reliability, Reliability theory, Systematic processing, Vigilance
@inproceedings{nosratiAIComplacencyModel2025a,
title = {The AI Complacency Model: Integrating Bounded Rationality and Information Processing},
author = {S. Nosrati and H. Motaghi},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105025349267&partnerID=40&md5=14d676bedd3ea18921ed24a830889a8b},
isbn = {979-833132774-3 (ISBN)},
year = {2025},
date = {2025-01-01},
booktitle = {Am. Conf. Inf. Syst., AMCIS},
volume = {7},
pages = {4590–4599},
publisher = {Association for Information Systems},
abstract = {This study addresses a critical gap in understanding why users exhibit reduced oversight when interacting with generative AI systems despite their known limitations. While existing research documents AI errors across domains, theoretical frameworks explaining the underlying psychological mechanisms remain underdeveloped. We propose a comprehensive model of AI complacency that extends beyond traditional automation complacency theories by integrating bounded rationality constraints with dual-process information processing models. Our framework demonstrates how Perceived AI Reliability triggers a shift from systematic to heuristic information processing, subsequently reducing vigilance and impairing task performance. The relationship between Perceived AI Reliability and information processing is moderated by three key factors derived from bounded rationality theory: knowledge limitations, cognitive processing capabilities, and time constraints. The proposed conceptual model of this study contributes to the literature by identifying unique psychological mechanisms underlying AI complacency, explaining the processing shifts in human-AI interaction, positioning vigilance as a critical mediating mechanism, and introducing the Vigilance-Reliability Matrix as a diagnostic tool for identifying different interaction patterns. This framework offers both theoretical insights and practical guidance for maintaining appropriate human oversight as AI systems become increasingly sophisticated and widespread across domains. Copyright © 2025 by Association for Information Systems (AIS). All rights reserved.},
keywords = {AI complacency, AI systems, Artificial intelligence, Behavioral research, Bounded rationality, Cognitive bias, cognitive biases, decision-making, Decisions makings, Heuristic processing, Human computer interaction, Human-AI interaction, information processing, Information systems, Information use, Perceived AI reliability, Reliability theory, Systematic processing, Vigilance},
pubstate = {published},
tppubtype = {inproceedings}
}
This study addresses a critical gap in understanding why users exhibit reduced oversight when interacting with generative AI systems despite their known limitations. While existing research documents AI errors across domains, theoretical frameworks explaining the underlying psychological mechanisms remain underdeveloped. We propose a comprehensive model of AI complacency that extends beyond traditional automation complacency theories by integrating bounded rationality constraints with dual-process information processing models. Our framework demonstrates how Perceived AI Reliability triggers a shift from systematic to heuristic information processing, subsequently reducing vigilance and impairing task performance. The relationship between Perceived AI Reliability and information processing is moderated by three key factors derived from bounded rationality theory: knowledge limitations, cognitive processing capabilities, and time constraints. The proposed conceptual model of this study contributes to the literature by identifying unique psychological mechanisms underlying AI complacency, explaining the processing shifts in human-AI interaction, positioning vigilance as a critical mediating mechanism, and introducing the Vigilance-Reliability Matrix as a diagnostic tool for identifying different interaction patterns. This framework offers both theoretical insights and practical guidance for maintaining appropriate human oversight as AI systems become increasingly sophisticated and widespread across domains. Copyright © 2025 by Association for Information Systems (AIS). All rights reserved.