Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems

Possessions and the Extended Self

Belk, R. W. (1988) · Journal of Consumer Research · doi:10.1086/209154 · Cited by 9,064 · see citing works

Extended Self in a Digital World: Table 1.

Belk, R. W. (2013) · Journal of Consumer Research · doi:10.1086/671052 · Cited by 1,698 · see citing works

The power of gifts: organizing social relationships in open source communities

Bergquist, M., & Ljungberg, J. (2001) · Information Systems Journal · doi:10.1046/j.1365-2575.2001.00111.x · Cited by 480 · see citing works

Gifts, commodities, and social relations: A Maussian view of exchange

Carrier, J. (1991) · Sociological Forum · doi:10.1007/bf01112730 · Cited by 248 · see citing works

Demanding by Design: Supporting Effortful Communication Practices in Close Personal Relationships

Kelly, R., Gooch, D., Patil, B., & Watts, L. (2017) · Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing · doi:10.1145/2998181.2998184 · Cited by 61 · see citing works

The Role of Live Streaming in Building Consumer Trust and Engagement with Social Commerce Sellers

Wongkitrungrueng, A., & Assarut, N. (2020) · Journal of Business Research · doi:10.1016/j.jbusres.2018.08.032 · Cited by 1,477 · see citing works

Taxonomy of Risks posed by Language Models

Weidinger, L., Uesato, J., Rauh, M., Griffin, C., Huang, P.-S., Mellor, J., Glaese, A., Cheng, M., Balle, B., Kasirzadeh, A., et al. (2022) · 2022 ACM Conference on Fairness Accountability and Transparency · doi:10.1145/3531146.3533088 · Cited by 764 · see citing works

“Chatting with ChatGPT”: Analyzing the factors influencing users' intention to Use the Open AI's ChatGPT using the UTAUT model

Menon, D., & Shilpa, K. (2023) · Heliyon · doi:10.1016/j.heliyon.2023.e20962 · Cited by 359 · see citing works

Trusting Automation: Designing for Responsivity and Resilience

Chiou, E. K., & Lee, J. D. (2023) · Human Factors: The Journal of the Human Factors and Ergonomics Society · doi:10.1177/00187208211009995 · Cited by 301 · see citing works

Comprehension, apprehension, and acceptance: Understanding the influence of literacy and anxiety on acceptance of artificial Intelligence

Schiavo, G., Businaro, S., & Zancanaro, M. (2024) · Technology in Society · doi:10.1016/j.techsoc.2024.102537 · Cited by 284 · see citing works

Using digital story writing as a pedagogy to develop AI literacy among primary students

Ng, D. T. K., Luo, W., Chan, H. M. Y., & Chu, S. K. W. (2022) · Computers and Education Artificial Intelligence · doi:10.1016/j.caeai.2022.100054 · Cited by 266 · see citing works

Uncertainty as a Form of Transparency: Measuring, Communicating, and Using Uncertainty

Bhatt, U., Antorán, J., Zhang, Y., Liao, Q. V., Sattigeri, P., Fogliato, R., Melançon, G., Krishnan, R., Stanley, J., Tickoo, O., et al. (2021) · Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society · doi:10.1145/3461702.3462571 · Cited by 225 · see citing works

Designing interpretable ML system to enhance trust in healthcare: A systematic review to proposed responsible clinician-AI-collaboration framework

Nasarian, E., Alizadehsani, R., Acharya, U. R., & Tsui, K.-L. (2024) · Information Fusion · doi:10.1016/j.inffus.2024.102412 · Cited by 207 · see citing works

Exploring older adults' perception and use of smart speaker-based voice assistants: A longitudinal study

Kim, S., & Choudhury, A. (2021) · Computers in Human Behavior · doi:10.1016/j.chb.2021.106914 · Cited by 200 · see citing works

Effects of Explainable Artificial Intelligence on trust and human behavior in a high-risk decision task

Leichtmann, B., Humer, C., Hinterreiter, A., Streit, M., & Mara, M. (2023) · Computers in Human Behavior · doi:10.1016/j.chb.2022.107539 · Cited by 200 · see citing works

How the Design of YouTube Influences User Sense of Agency

Lukoff, K., Lyngs, U., Zade, H., Liao, J. V., Choi, J., Fan, K., Munson, S. A., & Hiniker, A. (2021) · Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3411764.3445467 · Cited by 190 · see citing works

Evaluating the use of interactive virtual reality technology with older adults living in residential aged care

Baker, S., Waycott, J., Robertson, E., Carrasco, R., Neves, B. B., Hampson, R., & Vetere, F. (2020) · Information Processing & Management · doi:10.1016/j.ipm.2019.102105 · Cited by 161 · see citing works

Do VR and AR versions of an immersive cultural experience engender different user experiences?

Verhulst, I., Woods, A., Whittaker, L., Bennett, J., & Dalton, P. (2021) · Computers in Human Behavior · doi:10.1016/j.chb.2021.106951 · Cited by 150 · see citing works

Luminate: Structured Generation and Exploration of Design Space with Large Language Models for Human-AI Co-Creation

Suh, S., Chen, M., Min, B., Li, T. J.-J., & Xia, H. (2024) · Proceedings of the CHI Conference on Human Factors in Computing Systems · doi:10.1145/3613904.3642400 · Cited by 148 · see citing works

AI chatbots cannot replace human interactions in the pursuit of more inclusive mental healthcare

Brown, J. E. H., & Halpern, J. (2021) · SSM - Mental Health · doi:10.1016/j.ssmmh.2021.100017 · Cited by 139 · see citing works

The experiences, needs and barriers of people with impairments related to usability and accessibility of digital health solutions, levels of involvement in the design process and strategies for participatory and universal design: a scoping review

Henni, S. H., Maurud, S., Fuglerud, K. S., & Moen, A. (2022) · BMC Public Health · doi:10.1186/s12889-021-12393-1 · Cited by 141 · see citing works

The explainability paradox: Challenges for xAI in digital pathology

Evans, T., Retzlaff, C. O., Geißler, C., Kargl, M., Plass, M., Müller, H., Kiehl, T.-R., Zerbe, N., & Holzinger, A. (2022) · Future Generation Computer Systems · doi:10.1016/j.future.2022.03.009 · Cited by 135 · see citing works

Algorithm-mediated social learning in online social networks

Brady, W. J., Jackson, J. C., Lindström, B., & Crockett, M. J. (2023) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2023.06.008 · Cited by 132 · see citing works

Why are smartphones disruptive? An empirical study of smartphone use in real-life contexts

Heitmayer, M., & Lahlou, S. (2021) · Computers in Human Behavior · doi:10.1016/j.chb.2020.106637 · Cited by 108 · see citing works

Trustworthy AI: Closing the gap between development and integration of AI systems in ophthalmic practice

González-Gonzalo, C., Thee, E. F., Klaver, C. C. W., Lee, A. Y., Schlingemann, R. O., Tufail, A., Verbraak, F., & Sánchez, C. I. (2022) · Progress in Retinal and Eye Research · doi:10.1016/j.preteyeres.2021.101034 · Cited by 103 · see citing works

Use Cases for Design Personas: A Systematic Review and New Frontiers

Salminen, J., Wenyun Guan, K., Jung, S.-G., & Jansen, B. (2022) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3491102.3517589 · Cited by 96 · see citing works

DeepThInk: Designing and probing human-AI co-creation in digital art therapy

Du, X., An, P., Leung, J., Li, A., Chapman, L. E., & Zhao, J. (2024) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2023.103139 · Cited by 95 · see citing works

A Checklist to Combat Cognitive Biases in Crowdsourcing

Draws, T., Rieger, A., Inel, O., Gadiraju, U., & Tintarev, N. (2021) · Proceedings of the AAAI Conference on Human Computation and Crowdsourcing · doi:10.1609/hcomp.v9i1.18939 · Cited by 86 · see citing works

Explainability pitfalls: beyond dark patterns in explainable AI

Ehsan, U., & Riedl, M. O. (2024) · Patterns · doi:10.1016/j.patter.2024.100971 · Cited by 72 · see citing works

Personalized models of physical activity responses to text message micro-interventions: A proof-of-concept application of control systems engineering methods

Conroy, D. E., Hojjatinia, S., Lagoa, C. M., Yang, C.-H., Lanza, S. T., & Smyth, J. M. (2019) · Psychology of Sport and Exercise · doi:10.1016/j.psychsport.2018.06.011 · Cited by 71 · see citing works

Artificial Intelligence for Academic Purposes (AIAP): Integrating AI literacy into an EAP module

Ngo, T. N., & Hastie, D. (2025) · English for Specific Purposes · doi:10.1016/j.esp.2024.09.001 · Cited by 72 · see citing works

Beyond self-diagnosis: how a chatbot-based symptom checker should respond

You, Y., Tsai, C.-H., Li, Y., Ma, F., Heron, C., & Gui, X. (2023) · ACM Transactions on Computer-Human Interaction · doi:10.1145/3589959 · Cited by 60 · see citing works

Lessons Learned from Designing an AI-Enabled Diagnosis Tool for Pathologists

Gu, H., Huang, J., Hung, L., & Chen, X. '. (2021) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3449084 · Cited by 56 · see citing works

Exploring the effects of human-centered AI explanations on trust and reliance

Scharowski, N., Perrig, S. A. C., Svab, M., Opwis, K., & Brühlmann, F. (2023) · Frontiers in Computer Science · doi:10.3389/fcomp.2023.1151150 · Cited by 57 · see citing works

Psychological Traits and Appropriate Reliance: Factors Shaping Trust in AI

Küper, A., & Krämer, N. (2024) · International Journal of Human–Computer Interaction · doi:10.1080/10447318.2024.2348216 · Cited by 49 · see citing works

Meta AI literacy scale: Further validation and development of a short version

Koch, M. J., Carolus, A., Wienrich, C., & Latoschik, M. E. (2024) · Heliyon · doi:10.1016/j.heliyon.2024.e39686 · Cited by 44 · see citing works

Large language models meet user interfaces: The case of provisioning feedback

Pozdniakov, S., Brazil, J., Abdi, S., Bakharia, A., Sadiq, S., Gašević, D., Denny, P., & Khosravi, H. (2024) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2024.100289 · Cited by 43 · see citing works

Can robots elicit empathy? The effects of social robots’ appearance on emotional contagion

Yang, W., & Xie, Y. (2024) · Computers in Human Behavior: Artificial Humans · doi:10.1016/j.chbah.2024.100049 · Cited by 42 · see citing works

"It would work for me too": How Online Communities Shape Software Developers' Trust in AI-Powered Code Generation Tools

Cheng, R., Wang, R., Zimmermann, T., & Ford, D. (2024) · ACM Transactions on Interactive Intelligent Systems · doi:10.1145/3651990 · Cited by 47 · see citing works

A comparative evaluation of direct hand and wand interactions on consumer devices

Figueiredo, L., Rodrigues, E., Teixeira, J., & Teichrieb, V. (2018) · Computers & Graphics · doi:10.1016/j.cag.2018.10.006 · Cited by 39 · see citing works

“Can I have the scan on Tuesday?” User repair in interaction with a task-oriented chatbot and the question of communication skills for AI

Dippold, D. (2023) · Journal of Pragmatics · doi:10.1016/j.pragma.2022.12.004 · Cited by 37 · see citing works

Potential and Pitfalls of Digital Voice Assistants in Older Adults With and Without Intellectual Disabilities: Relevance of Participatory Design Elements and Ecologically Valid Field Studies

Schlomann, A., Wahl, H.-W., Zentel, P., Heyl, V., Knapp, L., Opfermann, C., Krämer, T., & Rietz, C. (2021) · Frontiers in Psychology · doi:10.3389/fpsyg.2021.684012 · Cited by 36 · see citing works

Stress and productivity patterns of interrupted, synergistic, and antagonistic office activities

Zaman, S., Wesley, A., Silva, D. R. D. C., Buddharaju, P., Akbar, F., Gao, G., Mark, G., Gutierrez-Osuna, R., & Pavlidis, I. (2019) · Scientific Data · doi:10.1038/s41597-019-0249-5 · Cited by 17 · see citing works

Scrolling in the Deep: Analysing Contextual Influences on Intervention Effectiveness during Infinite Scrolling on Social Media

Meinhardt, L.-M., Elhaidary, M., Colley, M., Rietzler, M., Rixen, J. O., Purohit, A. K., & Rukzio, E. (2025) · Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3706598.3713187 · Cited by 16 · see citing works

The Barriers to Online Clothing Websites for Visually Impaired People: An Interview and Observation Approach to Understanding Needs

Alluqmani, A., Harvey, M. A., & Zhang, Z. (2023) · Proceedings of the 2023 ACM Designing Interactive Systems Conference · doi:10.1145/3563657.3595978 · Cited by 14 · see citing works

InSupport: Proxy Interface for Enabling Efficient Non-Visual Interaction with Web Data Records

Ferdous, J., Lee, H.-N., Jayarathna, S., & Ashok, V. (2022) · 27th International Conference on Intelligent User Interfaces · doi:10.1145/3490099.3511126 · Cited by 11 · see citing works

Is prompt engineering the future of screenwriting? Views of professional screenwriters and commissioners about the impact of AI technologies on their profession

Vainikka, E., Soronen, A., & Kallio, S.-M. (2025) · Critical Studies in Television: The International Journal of Television Studies · doi:10.1177/17496020241269277 · Cited by 9 · see citing works

Failing with Grace: Exploring the Role of Repair Costs in Conversational Breakdowns with in-Car Voice Assistants

Meck, A.-M., Draxler, C., & Vogt, T. (2024) · International Journal of Human–Computer Interaction · doi:10.1080/10447318.2023.2266791 · Cited by 3 · see citing works