Intelligent Agent Transparency in Human–Agent Teaming for Multi-UxV Management

Artificial intelligence: a modern approach

Kumar, D. A., Balasubramanian, S., Byeon, D. H., & Manerkar, P. G. V. (1995) · Choice Reviews Online · doi:10.5860/choice.33-1577 · Cited by 22,191

Development of NASA-TLX (Task Load Index): Results of Empirical and Theoretical Research

(1988) · Advances in Psychology · doi:10.1016/s0166-4115(08)62386-9 · Cited by 15,003

Artificial intelligence: A modern approach

Nilsson, N. J. (1996) · Artificial Intelligence · doi:10.1016/0004-3702(96)00007-0 · Cited by 10,730

Toward a Theory of Situation Awareness in Dynamic Systems

Endsley, M. R. (1995) · Human Factors: The Journal of the Human Factors and Ergonomics Society · doi:10.1518/001872095779049543 · Cited by 8,875

Trust in Automation: Designing for Appropriate Reliance

Lee, J. D., & See, K. A. (2004) · Human Factors: The Journal of the Human Factors and Ergonomics Society · doi:10.1518/hfes.46.1.50_30392 · Cited by 6,605 · cited 8×

Humans and automation: Use, misuse, disuse, abuse

Parasuraman, R., & Riley, V. (1997) · Human Factors: The Journal of the Human Factors and Ergonomics Society · doi:10.1518/001872097778543886 · Cited by 4,554

Usability Evaluation In Industry

(1996) · CRC Press eBooks · doi:10.1201/9781498710411 · Cited by 4,445

A model for types and levels of human interaction with automation

Parasuraman, R., Sheridan, T. B., & Wickens, C. D. (2000) · IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans · doi:10.1109/3468.844354 · Cited by 4,195 · cited 1×

Working memory span tasks: A methodological review and user’s guide

Conway, A. R. A., Kane, M. J., Bunting, M. F., Hambrick, D. Z., Wilhelm, O., & Engle, R. W. (2005) · Psychonomic Bulletin & Review · doi:10.3758/bf03196772 · Cited by 2,882

The 35th Sir Frederick Bartlett Lecture: Eye movements and attention in reading, scene perception, and visual search

Rayner, K. (2009) · Quarterly Journal of Experimental Psychology · doi:10.1080/17470210902816461 · Cited by 2,682

Recommendations for the Empirical Assessment of Human-AI Work Systems: A Contribution to AI Measurement SciencePreprint

Hoffman, R., Klein, G., Mueller, S. T., & Clancey, W. J. (2021) · doi:10.31234/osf.io/z3yek · Cited by 2

Algorithm aversion or appreciation? Three randomized field trials of personalized risk-communication nudges to encourage flu vaccinationPreprint

Rosenbaum, G. M., Goren, A., Shermohammed, M., Wolk, D. M., Tice, A. M., Doyle, J. J., Meyer, M. N., & Chabris, C. F. (2023) · PsyArXiv (OSF Preprints) · doi:10.31234/osf.io/vtxza · Cited by 2

Advanced Driver Assistance Systems: Transparency and Driver Performance Effects

Deng, Y., & KABER, D. B. (2023) · doi:10.1002/9781119863663.ch25 · Cited by 2

Human-Agent Teaming: A System-Theoretic OverviewPreprint

Meimandi, K. J., Bolton, M. L., & Beling, P. A. (2024) · doi:10.36227/techrxiv.170629550.02125312/v1 · Cited by 2

A Potential Teammate?: Understanding How Indie Game Developers Approach Generative AI’s Involvement in Their Small-Scale Creative Teamwork

Panchanadikar, R., & Freeman, G. (2026) · Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3772318.3790869 · Cited by 3

Model Blindness II: Investigating a Model-Based Recommender System’s Impact on Decision Making

Parmar, S., Illingworth, D. A., & Thomas, R. P. (2023) · Proceedings of the Human Factors and Ergonomics Society Annual Meeting · doi:10.1177/21695067231192247 · Cited by 1

Level of detail in visualization for human autonomy teaming: Speed, accuracy, and workload effects

Wang, T., & Lau, N. K. C. (2023) · Proceedings of the Human Factors and Ergonomics Society Annual Meeting · doi:10.1177/21695067231193673 · Cited by 1

To Split or Not to Split? Evaluating IA Roles Providing Knowledge and Emotional Support

Zhao, J., Rau, P. P., & Liu, Y. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-60901-5_14 · Cited by 1

Research on transparency design based on shared situation awareness in semiautomatic driving

You, F., Deng, H., Hansen, P., & Zhang, J. (2024) · Elsevier eBooks · doi:10.1016/b978-0-443-23606-8.00008-7 · Cited by 1

Do We Use Relatively Bad (Algorithmic) Advice? The Effects of Performance Feedback and Advice Representation on Advice Usage

Daschner, S., & Obermaier, R. (2024) · Journal of Behavioral Decision Making · doi:10.1002/bdm.70001 · Cited by 2

Trust Calibration in Augmented Reality-based Decision Support Systems

Konopka, B., Hönemann, K., & Wiesche, M. (2024) · IEEE Conference on Business Informatics · doi:10.1109/cbi62504.2024.00028 · Cited by 2

Position Paper: Trust, Teamwork and Digital Twins

Pollick, F. E., Bailey, M. E., Kim, J., Freeth, M., Miller, M., & Naidoo, L. (2025) · ACM Workshop on Secure and Trustworthy Cyber-Physical Systems (SaT-CPS) · doi:10.1145/3716816.3727976 · Cited by 1

The benefits of automation transparency are dependent on human attention control capacity

Gegoff, I., Tatasciore, M., Bowden, V. K., & Loft, S. D. (2025) · Applied Ergonomics · doi:10.1016/j.apergo.2025.104619 · Cited by 2

Towards a unified taxonomy for algorithmic transparency: insights from uncrewed air traffic management

Zou, Y.-Y., & Borst, C. (2025) · Cognition, Technology & Work · doi:10.1007/s10111-025-00826-5 · Cited by 2

Exploring the Impact of Transparent Generative AI on Learning Outcomes Through a Human-Machine Trust Model

Wang, F.-H. (2025) · IEEE International Conference on Advanced Learning Technologies (ICALT) · doi:10.1109/icalt64023.2025.00072 · Cited by 1

Understanding Trust and Fatigue Under Transparency Regulation in Air Traffic Control: A Multimodal Approach

Jiang, C., Zhou, T., Shen, H., & Wang, Y. (2025) · IEEE Intelligent Transportation Systems Magazine · doi:10.1109/mits.2025.3636860 · Cited by 1

Neuro-cognitive benefits of high agent transparency on operators’ cognitive and affective emergent states in human-agent teaming

Cai, Y., & Rau, P. P. (2026) · Applied Ergonomics · doi:10.1016/j.apergo.2026.104738 · Cited by 1

Toward Situation Awareness-Supportive In-Vehicle Agent Design for Collaborative Driving: Effects of Transparency and Visual Representation

Lim, Y., Hong, J., Jeon, G., & Lee, S. (2026) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2026.2643367 · Cited by 1

Human–Artificial Intelligence Collaborative Decision-Making in Emergencies: Relative Advantage Theory

Zou, X., & Rau, P. P. (2026) · Human Factors The Journal of the Human Factors and Ergonomics Society · doi:10.1177/00187208261450138 · Cited by 2

How transparency impacts trust in teleoperated autonomous robots under uncertainty

Min, C., Gao, K., Ji, Z., & Xu, X. (2026) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2026.103877 · Cited by 1

Designing for Passenger Trust: Effects of Interface Spatial Layout in Low-Altitude Urban Air Mobility

You, F., Ji, X., Fu, Q., Shu, Y., Hansen, P., & Wang, J. (2026) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2026.2689522 · Cited by 1

Mitigating driver confusion and aggression in mixed traffic: Effects of V2V communication and driving style

Chen, H., & Zhang, Y. (2026) · Accident Analysis & Prevention · doi:10.1016/j.aap.2026.108676 · Cited by 1

The Advanced Exploitation of Mixed Reality (AEMR) Community of Interest

Rodas, M. O., Waters, J., & Rousseau, D. (2016) · Communications in computer and information science · doi:10.1007/978-3-319-40542-1_14 · Cited by 1

UI-Design and Evaluation for Human-Robot-Teaming in Infantry Platoons

Westhoven, M., Lassen, C., Trautwein, I., Remmersmann, T., & Brüggemann, B. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-58475-1_12 · Cited by 2

Operator Trust Function for Predicted Drone Arrival

Trujillo, A. (2018) · Advances in intelligent systems and computing · doi:10.1007/978-3-319-94346-6_1 · Cited by 1

ART-GCS: An Adaptive Real-Time Multi-Agent Ground Control Station

Bonache-Seco, J. A., Orozco, J. A. L., Besada-Portas, E., & Risco‐Martín, J. L. (2019) · Spring Simulation Multiconference · doi:10.23919/springsim.2019.8732874 · Cited by 1

Transparent Shepherding: A Rule-Based Learning Shepherd for Human Swarm Teaming

Debie, E., Rojas, R. F., Fidock, J. J. T., Barlow, M., Kasmarik, K., Anavatti, S. G., Garratt, M., & Abbass, H. A. (2020) · Unmanned system technologies · doi:10.1007/978-3-030-60898-9_12 · Cited by 1

New teams on the flight deck: Humans and context-sensitive information automation

Burian, B. K., Mosier, K. L., Fischer, U. M., & Kochan, J. A. (2022) · Elsevier eBooks · doi:10.1016/b978-0-12-420139-2.00008-3 · Cited by 2

A Vision Inference Action Model for Shared Situational Awareness in Autonomous Agents: Approaches, Challenges, & Future Directions

King, J. M., Hough, A. R., & Collins, M. G. (2022) · Proceedings of the Human Factors and Ergonomics Society Annual Meeting · doi:10.1177/1071181322661238 · Cited by 1

‘Try this Because’: The Effect of Positive Framing in Robo-Advisors

Kim, E., Heo, J., & Lee, J. (2022) · [ ] With Design: Reinventing Design Modes · doi:10.1007/978-981-19-4472-7_189 · Cited by 1

Necessity of Self-explainability in AI: Insights from the Existing Social Projects

Jadhav, M., Laddha, S., & Kabra, S. M. (2023) · Lecture notes in networks and systems · doi:10.1007/978-981-99-0483-9_20 · Cited by 1

Fundamental Study on Effects of Provision of “Neither-Good-Nor-Bad” Information in Negative Advice on User’s Trustworthiness of Agents

Amino, K. I. T. A., & Imai, J. (2023) · Transactions of Japan Society of Kansei Engineering · doi:10.5057/jjske.tjske-d-23-00004 · Cited by 1

A Computational Interface to Translate Strategic Intent from Unstructured Language in a Low-Data Setting

Tambwekar, P., Dodeja, L., Vaska, N., Xu, W., & Gombolay, M. (2023) · Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP) · doi:10.18653/v1/2023.findings-emnlp.853 · Cited by 1

Towards a Framework for Interdisciplinary Studies in Explainable Artificial Intelligence

Ziethmann, P., Stieler, F., Pfrommer, R., Schlögl-Flierl, K., & Bauer, B. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-60606-9_18 · Cited by 1

Between Trust and Identity: Form, Function, and Presentation

Lee, M., McMillan, D., Torre, I., Fischer, J. E., & Ruitenburg, Y. (2024) · ACM Conference on Conversational User Interfaces (CUI) · doi:10.1145/3640794.3669999 · Cited by 1

Exploring human autonomy teaming methods in challenging environments: the case of uncrewed system (UxS) solutions—challenges and opportunities with artificial intelligence

Stensrud, R., Nummedal, O. R., & Valaker, S. (2024) · Human-Intelligent Systems Integration · doi:10.1007/s42454-024-00058-4 · Cited by 1

Trust in Sensing Technologies and Human Wingmen: Analogies for Human-Machine Teams

Lyons, J. B., Ho, N., Hoffmann, L. C., Sadler, G. G., Abel, A. L. V., & Wilkins, M. A. (2018) · Lecture notes in computer science · doi:10.1007/978-3-319-91470-1_13 · Cited by 1

Interrogating the Black Box: Transparency through Information-Seeking Dialogues

Tubella, A. A., Theodorou, A. A., & Nieves, J. C. (2021) · Adaptive Agents and Multi-Agents Systems · doi:10.65109/onbl7454 · Cited by 1

Evaluating a virtual human storyteller for improved decision support

Blackmore, K., Smith, S., Nesbitt, K., North, L., Wark, S., & Nowina-Krowicki, M. (2019) · MODSIM · doi:10.36334/modsim.2019.b2.blackmore · Cited by 1

Tangibilité et engagement dans un comportement environnemental : Vers une étude longitudinale

Bouzékri, E., & Rivière, G. (2022) · doi:10.1145/3502178.3529110 · Cited by 1

Explanation of Reinforcement Learning Model in Dynamic Multi-Agent SystemPreprint

Wang, X., Li, H., Zhang, H., Lewis, M. A., & Sycara, K. P. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2008.01508 · Cited by 6

Do eyes say it all? Assessing the utility of physiological signals for predicting systemic cognitive statesPreprint

Aygun, A., Nguyen, T. D., & Scheutz, M. J. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.02.29.582708 · Cited by 1

Developing human-autonomy teaming characteristics and guidance in aerospace operations

Tokadlı, G. (2021) · doi:10.31274/td-20240329-223 · Cited by 1

Niveaux d'automatisation adaptables pour une coopération homme-robots

Habib, L. (2019) · doi:10.70675/61fe21a5z7e1fz442cza48bzac1a19d65a16 · Cited by 1

Human-Agent Collaborative Decision-Making Framework for Naval Systems

Rodas, M. O., Waters, J., & Putnam, C. (2018) · Lecture notes in computer science · doi:10.1007/978-3-319-91584-5_29

Reducción de la carga de trabajo del operador en un centro de control adaptativo multi-vehículo

Bonache-Seco, J. A., Orozco, J. A. L., Besada-Portas, E., Jiménez-Castellanos, J. F., & Girón-Sierra, J. M. (2019) · Jornadas de Automática · doi:10.17979/spudc.9788497497169.016

Enhancing autonomy transparency: an option-centric rationale approachPreprint

Luo, R., Du, N., & Yang, X. J. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2008.01051

Infraestructura para estudiar adaptabilidad y transparencia en el centro de control versatil

Seco, J. A. B., Orozco, J. A. L., Besada-Portas, E., & García, J. M. D. L. C. (2017) · Consultation of the Doctoral Thesis Database (TESEO) (Ministerio de Educación, Cultura y Deporte) · doi:10.17979/spudc.9788497497749.0203

A Measure of All Minds: A Classification of the Artificial Intelligence Strengths and Virtues & the Creation of the THETIS Dimensions of Cybernetic Wellbeing

Norman, S. R. (2020) · ScholarlyCommons (University of Pennsylvania)

Human-Autonomy Teaming Essential Research Program Project 2: Transparent Multimodal Crew Interface Designs Technical Note 1: General Overview

Perelman, B. S., Lakhmani, S. G., & Wright, J. L. (2020)

Model of Technological, Managerial and Marketing Infrastructure for Intelligent Technology Efficiency in Telecommunication Industry - Case Study: Telecommunication Infrastructure Company of Ilam Province1

Moradhaseli, H., & Monfared, J. H. (2020) · Journal of Information Systems and Telecommunication (JIST) · doi:10.29252/jist.8.30.105 · Cited by 1

Identifying and Overcoming Attention Limitations in the Detection and Identification of Alarms in Close Temporal Proximity

Wan, Y. (2019) · Deep Blue (University of Michigan)

An Approach to Modeling Simulated Military Human-agent Teaming

Hidalgo, M. (2020) · Journal of International Crisis and Risk Communication Research

Centro de control versátil para equipos de vehículos heterogéneos: estado actual y mejoras futuras

Bonache-Seco, J. A., Orozco, J. A. L., Besada-Portas, E., & García, J. M. D. L. C. (2022) · Jornadas de Automática · doi:10.17979/spudc.9788497498081.0979

ART-GCS : an Adaptive Real-Time Multi-Agent Ground Control Station

Bonache-Seco, J. A., Lopez-Orozco, J. A., Besada-Portas, E., & Risco-Martín, J. L. (2019) · Annual Simulation Symposium (ANSS) · doi:10.22360/springsim.2019.anss.013

IA, robotique, automatisation : quelles évolutions pour l’activité humaine ?

Haradji, Y., Zouinar, M., Delgoulet, C., & Morais, A. (2020) · Activites · doi:10.4000/activites.4929

Measures of Attention in Autonomous and Semi-Autonomous Multi-Vehicle Supervision

Glavan, J. J., Bass, E. J., Adams, J. A., & Sanchez, C. A. (2022) · IEEE International Conference on Human-Machine Systems (ICHMS) · doi:10.1109/ichms56717.2022.9980754 · Cited by 1

Estimating Causal Responsibility for Explaining Autonomous Behavior

Mahmud, S., Nashed, S. B., Goldman, C. V., & Zilberstein, S. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-40878-6_5

Towards a Comprehensive Model of Military Human-Agent Teaming

Hidalgo, M., & Jones, L.-R. (2023) · Proceedings of the Human Factors and Ergonomics Society Annual Meeting · doi:10.1177/21695067231192436

Dynamic Strategy Selection under Bounded Rationality in Constrained Optimization ProblemsPreprint

Diego‐Rosell, P., Thomas, R. P., & Maese, E. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4648062

Human-Robot Collaboration: From the Perspective of Systems and Control

Yamauchi, J., & Hatanaka, T. (2024) · Journal of the Robotics Society of Japan · doi:10.7210/jrsj.42.99

Decision support improves information integration and criterion placement in a multi-cue signal-identification task

McCarley, J. S., Knight, M., & Fletcher, K. I. (2024) · Ergonomics · doi:10.1080/00140139.2024.2386562

Robot transparency and anthropomorphic attribute effects on human-robot interactions

Wang, J., Liu, Y., Yue, T., Wang, C., Mao, J., Wang, Y., & You, F. (2024) · Elsevier eBooks · doi:10.1016/b978-0-443-23606-8.00020-8

Design of proactive interaction of in-vehicle robots based transparency

Wang, J., Yue, T., Liu, Y., Wang, Y., Wang, C., Yan, F., & You, F. (2024) · Elsevier eBooks · doi:10.1016/b978-0-443-23606-8.00021-x

Decision-Making Aid for Human-Machine Teaming in Multiplayer Pursuit-Evasion Games

Sachidanandam, S. O., Honarvar, S., Elliott, D. S., Hicks, G., & Diaz-Mercado, Y. J. (2025) · AIAA SciTech Forum · doi:10.2514/6.2025-2272

Trends of Artificial Intelligence in Human Resources Management Using Bibliometric Analysis

Ng, W. C., Ravesangar, K., Toh, G. G., & Soong, Y. Q. (2025) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3693-9395-6.ch016

Willingness to work as a predictor of human-agent team success

Gurney, N., Pynadath, D. V., & Miller, J. H. (2025) · Frontiers in Computer Science · doi:10.3389/fcomp.2025.1405436

Transparency-Based Action (TBA) Model for a Simulated Teleoperated Mobile Robot

Aharony, N., Arie, T., Oron-Gilad, T., & Edan, Y. (2025) · Lecture notes in computer science · doi:10.1007/978-981-96-3522-1_36

Communication Dynamics and Team Performance in Multiple-Operator-Multiple-Agent (MOMA) Team

Chung, H., & Yang, X. J. (2025) · IEEE International Conference on Human-Machine Systems (ICHMS) · doi:10.1109/ichms65439.2025.11154362

How Should Your Artificial Teammate Tell You How Much It Trusts You?

Jorge, C. C., Dumitrescu, E., Jonker, C. M., Loghin, R., Marossi, S., Uleia, E., & Tielman, M. L. (2025) · ACM International Conference on Intelligent Virtual Agents (IVA) · doi:10.1145/3717511.3747086 · Cited by 1

Adaptive and User-Centered HCI for Intelligent Technologies: A Global Perspective

Abdurrohman (2024) · Digitus : Journal of Computer Science Applications · doi:10.61978/digitus.v2i4.854

VirTLab-Eval: Human-Agent Team and Digital Twin Performance Evaluation Demonstration

Volkova, S., Kao, H.-T., Penafiel, L., Nguyen, D., Cohen, M. C., McCormack, R., & Cassani, L. (2025) · Proceedings of the Human Factors and Ergonomics Society Annual Meeting · doi:10.1177/10711813251369797 · Cited by 1

WO: Menschen, Technologie und humane Technologie

Walther, C. C. (2025) · Springer eBooks · doi:10.1007/978-3-031-95463-4_2

Effect of Information Transparency and Color on Human-Machine Trust and Work Performance in Autonomous DrivingPreprint

Tohti, Y., Huang, X., Zhang, J., Li, J., shi, L., & Huang, Y. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5611783

Lost in Transparency? Exploring Uni- and Multimodal Transparency Declarations in Human-Robot Interaction*

Helgert, A., Erle, L., Dittmann, A., Eimler, S. C., & Straßmann, C. (2025) · IEEE RO-MAN · doi:10.1109/ro-man63969.2025.11217627

Artificial Intelligence Applications in Finance

Ram, V. S., Sukirno, S., & Rao, S. G. R. (2025) · IGI Global eBooks · doi:10.4018/979-8-3373-3725-8.ch009

(work)Flow bots vs. No bots: Workflow dynamics and AI utilization in teams

Fitzhugh, S. M. (2026) · Computers in Human Behavior Artificial Humans · doi:10.1016/j.chbah.2026.100264

User Reliance on AI Support for Collaborative Partner Selection

Hrkalović, T. M., Dudzik, B., Hao, C., & Willemsen, M. C. (2026) · ACM International Conference on Intelligent User Interfaces (IUI) · doi:10.1145/3742413.3789082

Beyond Information Amount: Rethinking Transparency through Active Reasoning Demand

Zhang, X., Ye, Y., Ma, Y., Zhang, Z. T., & Butz, A. M. (2026) · ACM/IEEE International Conference on Human-Robot Interaction (HRI) · doi:10.1145/3757279.3785623

Conception d'une interface avec réalité augmentée pour la conduite automobile autonome

Meguia, R. P. (2018) · doi:10.70675/037f8b81z28efz4fa9z810cz1e448ed63c29

Rôle de l’acceptabilité dans l’interaction entre un véhicule conventionnel et un véhicule automatisé

Pottier, G. (2020) · theses.fr (ABES) · doi:10.70675/93ac0316z1d1bz4a77zb811za63aa5f8d98e

Notation et processus outillé pour la description, l'analyse et la compréhension de l'automatisation dans les systèmes de commande et contrôle

Bouzékri, E. (2021) · doi:10.70675/1a3b92f1zcdd6z420ez8289z6a5d0468e002

Evaluation de la perception des consommateurs à l’aide du protocole sensoriel Free JAR : une nouvelle méthodologie de collecte et d'analyse statistique des données

Luc, A. (2022) · theses.fr (ABES) · doi:10.70675/8c635497ze4c1z40b1z9796za3a20d1d6df6

Explanation of the artificial agent : exploring the content and format of human interaction with AI

Guillou, M. L. (2023) · theses.fr (ABES) · doi:10.70675/31fa6b72z3709z4eb3z81c7z566d1b6cb118

Understanding Human-AI Teaming and Engagement Behaviors in Critical Mission Scenarios in Virtual Environments

Schwalb, J., Sung, E., Menon, V., Weger, K., & Mesmer, B. L. (2026) · IEEE SoutheastCon · doi:10.1109/southeastcon63549.2026.11476024

Impact of AI Transparency Levels on Human Performance, Trust, and Workload in Collaborative Tasks

Park, G., & Kim, S.-H. (2026) · Theoretical and Applied Ergonomics · doi:10.3390/tae2020009

Worker-Centered AI: Transparent Explanations for Trustworthy Task Recommendation in Crowd Work

Mazdarani, F., Hernandez, A. C., & Toxtli, C. (2026) · IEEE Conference on Artificial Intelligence (CAI) · doi:10.1109/cai68641.2026.11536153 · Cited by 1

Adaptable and Hybrid Automation for Human–AI Task Allocation: Application to Call Center Supervision

Donat-Bouillud, L., & Amokrane, K. (2026) · Electronics · doi:10.3390/electronics15112452

Rethinking Aviation Safety in the Age of Autonomy: From Tools to Cognitive Partners

Letouze, T. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-29456-2_15

The Role of Transparency in Takeover Information for Trust Calibration in Automated Driving Systems

Liu, X., Wan, L., & Ge, Y. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-29459-3_2

Bias in Physiology-Based Cognitive State Detection for Human–Autonomy Teaming: A Comprehensive Survey

Tiwari, A., Arrabito, R., Davoust, A., & Falk, T. H. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-30015-7_9

Designing Collaborative Intelligence

Ravikumar, R. N., & Aarthi, S. (2026) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-8217-3.ch002

The impact of AI transparency and AI authorization on human performance in AI-to-human delegation

Tang, J., Wang, Y., Zhou, X., Zhao, Y. C., & Jiang, Y. (2026) · Electronic Commerce Research · doi:10.1007/s10660-026-10166-9

Calibrating Trust in ChatGPT for L2 Writers

유혜빈, Pecsok, M., & Pals, C. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-30784-2_10

Too Much, Too Little, Just Right? Towards Dimensions of Trust Calibration in Human–AI Interaction

Börsting, I., & Hesenius, M. (2026) · ACM Conference on Conversational User Interfaces (CUI) · doi:10.1145/3816046.3816283

Looking into Pandora’s Black Box: A Systematic Literature Review to Understand Transparency in Human-Agent Interaction

Pithayarungsarit, P., Tafesse, H., Kannan, N., Henley, J. M., Saad, L., Trafton, J. G., & Roesler, E. (2026) · Proceedings of the Human Factors and Ergonomics Society Annual Meeting · doi:10.1177/10711813261475167

Enhancing Situation Awareness in Multi-Robot Supervision: The Role of Adaptive Interfaces for Multiple Displays

Park, S., Lee, S., Park, S., & Nam, C. (2026) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2026.2706905

Identifying factors that underpin human-machine teamwork for joint crewed-uncrewed aerial vehicle operations: application of the grounded theory approach

Hart, S., Steane, V., Parnell, K. J., Plant, K. L., Soorati, M. D., & Young, M. S. (2026) · Theoretical Issues in Ergonomics Science · doi:10.1080/1463922x.2026.2718460

Designing a tool to assess design-related drivers of cognitive workload in collaborative assembly systems: a Delphi study

Mezentseva, A., Fraboni, F., Kiplangat, S. G., Gualtieri, L., & Angelis, M. D. (2026) · Ergonomics · doi:10.1080/00140139.2026.2729414

Effects of Agent Transparency on human-autonomy teaming effectiveness

Chen, J. Y. C., Barnes, M., Selkowitz, A. R., & Stowers, K. (2016) · IEEE International Conference on Systems, Man and Cybernetics · doi:10.1109/smc.2016.7844505 · Cited by 34

Insights into Human-Agent Teaming: Intelligent Agent Transparency and Uncertainty

Stowers, K., Kasdaglis, N., Rupp, M., Chen, J., Barber, D., & Barnes, M. (2017) · Advances in Intelligent Systems and Computing · doi:10.1007/978-3-319-41959-6_13 · Cited by 28

Agent transparency in mixed-initiative multi-UxV control: How should intelligent agent collaborators speak their minds?

Wohleber, R. W., Stowers, K. L., Barnes, M., & Chen, J. Y. C. (2023) · Computers in Human Behavior · doi:10.1016/j.chb.2023.107866 · Cited by 19

The IMPACT of Agent Transparency on Human Performance

Stowers, K. L., Kasdaglis, N., Rupp, M. A., Newton, O. B., Chen, J. Y. C., & Barnes, M. J. (2020) · IEEE Transactions on Human-Machine Systems · doi:10.1109/thms.2020.2978041 · Cited by 72

Intelligent Agent Transparency

Stowers, K. L., Kasdaglis, N., Newton, O. B., Lakhmani, S. G., Wohleber, R. W., & Chen, J. Z.-J. (2016) · Proceedings of the Human Factors and Ergonomics Society Annual Meeting · doi:10.1177/1541931213601392 · Cited by 42