The Asynchronous Video Interview-Artificial Intelligence: A review of current studies and directions for future research
Article Sidebar
Main Article Content
Abstract
Organizations are increasingly adopting video job interview in the era of COVID-19 pandemic. Especially, with screening purposes, the asynchronous video interview powered by artificial intelligence(AVI-AI) is often placed as an additional stage in selection processes. For cost and efficiency reasons, many organizations showed great interest in adopting and expanding the use of AVI-AI. Although research on AVI-AI is steadily increasing, only a few have been published in the field of industrial and organizational psychology. The current research aimed to conceptualize AVI-AI based on the review of current usage and empirical research findings on AVI-AI. Finally, this study discussed the implications for future research on AVI-AI and provided important recommendations for HR managers.
Metrics
Article Details
This work is licensed under a Creative Commons Attribution 4.0 International License.
Funding data
-
National Research Foundation of Korea
Grant numbers NRF-2017S1A6A3A01078538 -
Ministry of Education
References
사람인 (2021, September 27). 기업 47%, “코로나19로 면접 진행 너무 어려워.” https://www.saramin.co.kr/zf_user/help/live/view?idx=108451&list_idx=0&listType=news&category=10&keyword=&menu=1&page=1
잡코리아 (2021, September 1). 기업 67% “비대면으로 직원 뽑는다.”https://www.jobkorea.co.kr/goodjob/Tip/View?News_No=19121&schCtgr=0&Page=1&cmpid=vm_viral_post
김양혁 (2021). ‘면접 연습 VR로 한다’ ... LG유플러스, U+VR모의면접 출시.https://biz.chosun.com/it-science/ict/2021/11/15/D2EQ6JW76VH4ZOCERVRSL5Z32E/
김윤정, 권순희 (2021). AI 면접을 대비하기 위한 화법 교육 방안. 한글, 82(4),1101-1139.
마이다스아이티 (2022, June 24). 역량을 측정하고 성과를 예측하는 가장 강력한 솔루션. https://www.midashri.com/intro/ai
마이다스아이티 (2022, June 24). AI 역량검사 바로 알기. https://www.midashri.com/aicc
마이다스아이티 (2022, August 2). 7. 종합점수의 정확도 검증.https://www.midashri.com/aicc-07
뷰인터 (2022). 나를 위한 AI 면접 연습. https://front.viewinter.ai/#/introduce
이송원 (2022, July 4). [Biz 톡] AI면접 600곳 넘는데 지원자 10명 중 6명은 “대면면접이 더 공정”. 조선일보.https://www.chosun.com/economy/industry-company/2022/07/04/PNFTZJ6VYNGZ5EKFP3LHNUCAHY/?utm_source=naver&utm_medium=referral&utm_campaign=naver-news
이환우, 이새롬, 정경철 (2019). 채용 전형에서 인공지능 기술 도입이 입사 지원의도에 미치는 영향. 정보시스템연구, 28(2), 25- 52.
잡코리아 (2022). AI면접 모의고사.https://www.jobkorea.co.kr/AI/Evaluation
정유미 (2021). 기업 10곳중 5곳 “마스크착용 등 비대면 면접평가 어려워”. 경향신문. https://www.khan.co.kr/economy/economy-general/article/202109270929001
하이버프 (2022). 인공지능 면접 통합 솔루션 하이버프.https://www.highbuff.com/share/img/page/2022_interview_new.pdf
Abrams, M., Abrams, J., Cullen, P., & Goldstein, L. (2019). Artificial intelligence, ethics, and enhanced data stewardship. IEEE Security & Privacy, 17(2), 17‒30.http://doi.org/10.1109/MSEC.2018.2888778
Acikgoz, Y., Davison, K. H., Compagnone, M., & Laske, M. (2020). Justice perceptions of artificial intelligence in selection. International Journal of Selection and Assessment, 28(4), 399-416. https://doi.org/10.1111/ijsa.12306
Basch, J. M., & Melchers, K. G. (2021). The use of technology‐mediated interviews and their perception from the organization's point of view. International Journal of Selection and Assessment, 29(3-4), 495-502.https://doi.org/10.1111/ijsa.12339
Basch, J. M., Melchers, K. G., Kegelmann, J., & Lieb, L. (2020). Smile for the camera! The role of social presence and impression management in perceptions of technology- mediated interviews. Journal of Managerial Psychology, 35(4), 285-299.
Bauer, T. N., Truxillo, D. M., Paronto, M. E., Weekley, J. A., & Campion, M. A. (2004). Applicant reactions to different selection technology: Face‐to‐face, interactive voice response, and computer‐assisted telephone screening interviews. International Journal of Selection and Assessment, 12(1‐2), 135-148. https://doi.org/10.1111/j.0965-075X.2004.00269.x
Baum, S. D. (2017). On the promotion of safe and socially beneficial artificial intelligence. AI & Society, 32(4), 543-551.https://doi.org/10.1007/s00146-016-0677-0
Berger, C. R. (1979). Beyond initial interaction: Uncertainty, understanding, and the development of interpersonal relationships. Language and Social Psychology, 6, 1-62.
Bhaskaran N, Nwogu I, Frank MG, Govindaraju V (2011) Lie to me: deceit detection via online behavioral learning. In: 2011 IEEE international conference on automatic face & gesture recognition and workshops (FG 2011).
Bhave, D. P., Teo, L. H., & Dalal, R. S. (2020). Privacy at work: A review and a research agenda for a contested terrain. Journal of Management, 46(1), 127-164.https://doi.org/10.1177/0149206319878254
Black, J. S., & van Esch, P. (2020). AI-enabled recruiting: What is it and how should a manager use it?. Business Horizons, 63(2), 215-226.https://doi.org/10.1016/j.bushor.2019.12.001
Blacksmith, N., Willford, J. C., & Behrend, T. S. (2016). Technology in the employment interview: A meta-analysis and future research agenda. Personnel Assessment and Decisions, 2(1), 12-20. https://doi.org/10.25035/pad.2016.002
Brahmana, R. K., & Brahmana, R. (2013). What factors drive job seekers’ attitude in using e-recruitment? South East Asian Journal of Management, 7(2), 123-134.https://doi/org/10.21002/seam.v7i2.2050
Brenner, F. S., Ortner, T. M., & Fay, D. (2016). Asynchronous video interviewing as a new technology in personnel selection: The applicant’s point of view. Frontiers in Psychology, 7, 863.https://doi.org/10.3389/fpsyg.2016.00863
Calders, T., & Žliobaitė, I. (2013). Why unbiased computational processes can lead to discriminative decision procedures. In Discrimination and Privacy in the Information Society (pp. 43-57). Springer.
Canhoto, A. I., & Clear, F. (2020). Artificial intelligence and machine learning as business tools: A framework for diagnosing value destruction potential. Business Horizons, 63(2), 183-193.https://doi.org/10.1016/j.bushor.2019.11.003
Chamorro-Premuzic, T., Winsborough, D., Sherman, R. A., & Hogan, R. (2016). New talent signals: Shiny new objects or a brave new world?. Industrial and Organizational Psychology, 9(3), 621-640.https://doi.org/10.1017/iop.2016.6
Chapman, D. S., & Rowe, P. M. (2002). The influence of videoconference technology and interview structure on the recruiting function of the employment interview: A field experiment. International Journal of Selection and Assessment, 10, 185-197.https://doi.org/10.1111/1468-2389.00208
Chapman, D. S., Uggerslev, K. L., & Webster, J. (2003). Candidate reactions to face-to-face and technology-mediated interviews: A field investigation. Journal of Applied Psychology, 88, 944-953.https://doi.org/10.1037/0021-9010.88.5.944
Connelly, B. L., Certo, S. T., Ireland, R. D., & Reutzel, C. R. (2011). Signaling theory: A review and assessment. Journal of Management, 37(1), 39-67.https://doi.org/10.1177/0149206310388419
Connelly, C. E., Fieseler, C., Černe, M., Giessner, S. R., & Wong, S. I. (2021). Working in the digitized economy: HRM theory & practice. Human Resource Management Review, 31(1), 100762.https://doi.org/10.1016/j.hrmr.2020.100762
Daugherty, P. R., Wilson, H. J., & Chowdhury, R. (2019). Using artificial intelligence to promote diversity. MIT Sloan Management Review, 60(2), 59-63.
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982-1003. https://doi.org/10.1287/mnsc.35.8.982
Day M. (2016). How LinkedIn’s search engine may reflect a gender bias. The Seattle Times. https://www.seattletimes.com/business/microsoft/how-linkedins-search-engine-may-reflect-a-bias/
Dineen, B. R., Noe, R. A., & Wang, C. (2004). Perceived fairness of web‐based applicant screening procedures: Weighing the rules of justice and the role of individual differences. Human Resource Management: Published in Cooperation with the School of Business Administration, The University of Michigan and in alliance with the Society of Human Resources Management, 43(2-3), 127-145.https://doi.org/10.1002/hrm.20011
Duchessi, P., O'Keefe, R., & O'Leary, D. (1993). A research perspective: Artificial intelligence, management and organizations. Intelligent Systems in Accounting, Finance and Management, 2(3), 151-159.https://doi.org/10.1002/j.1099-1174.1993.tb00039.x
Duffy, B. R., & Zawieska, K. (2012, September). Suspension of disbelief in social robotics. In 2012 IEEE RO-MAN: The 21st IEEE International Symposium on Robot and Human Interactive Communication.
Fischer, K., Foth, K., Rohlfing, K. J., & Wrede, B. (2011). Mindful tutors: Linguistic choice and action demonstration in speech to infants and a simulated robot. Interaction Studies, 12(1), 134-161.https://doi.org/10.1075/is.12.1.06fis
Fountaine, T., McCarthy, B., Saleh, T. (2019). Building the AI-powered organization. Harvard Business Review, 97, 62-73.
Ghosh, B., Daugherty, P., Wilson, J., & Burden, A. (2019). Taking a systems approach to AI. Harvard Business Review,https://hbr.org/2019/05/taking-a-systems-approach-to-adopting-ai.
Gonzalez, M. F., Capman, J. F., Oswald, F. L., Theys, E. R., & Tomczak, D. L. (2019). “Where’s the IO?” Artificial intelligence and machine learning in talent management systems. Personnel Assessment and Decisions, 5(3), 33-44.https://doi.org/10.25035/pad.2019.03.005
Gonzalez, M. F., Liu, W., Shirase, L., Tomczak, D. L., Lobbe, C. E., Justenhoven, R., & Martin, N. R. (2022). Allying with AI? Reactions toward human-based, AI/ML-based, and augmented hiring processes. Computers in Human Behavior, 130, 107179.https://doi.org/10.1016/j.chb.2022.107179
Goretzko, D., & Finja Israel, L. S. (2022). Pitfalls of machine learning-based personnel selection: Fairness, transparency, and data quality. Journal of Personnel Psychology, 21(1), 37-47. https://doi.org/10.1027/1866-5888/a000287
Gorman, C. A., Robinson, J., & Gamble, J. S. (2018). An investigation into the validity of asynchronous web-based video employment- interview ratings. Consulting Psychology Journal: Practice and Research, 70(2), 129-146. https://doi.org/10.1037/cpb0000102
Gunkel, D. J. (2012). The machine question: Critical perspectives on AI, robots, and ethics. MIT Press.
Hausknecht, J. P., Day, D. V., & Thomas, S. C. (2004). Applicant reactions to selection procedures: An updated model and meta-analysis. Personnel Psychology, 57(3), 639-683.https://doi.org/10.1111/j.1744-6570.2004.00003.x
Hebl, M. R., & Skorinko, J. L. (2005). Acknowledging one's physical disability in the interview: Does “when” make a difference? Journal of Applied Social Psychology, 35, 2477-2492.https://doi.org/10.1111/j.1559-1816.2005.tb02111.x
Helberger, N., Araujo, T., & de Vreese, C. H. (2020). Who is the fairest of them all? Public attitudes and expectations regarding automated decision-making. Computer Law & Security Review, 39, 105456.https://doi.org/10.1016/j.clsr.2020.105456
Hemamou, L., Felhi, G., Vandenbussche, V., Martin, J. C., & Clavel, C. (2019). HireNet: A hierarchical attention model for the automatic analysis of asynchronous video job interviews. Proceedings of the AAAI Conference on Artificial Intelligence, 33(1), 573-581.https://doi.org/10.1609/aaai.v33i01.3301573
Hess, R. (2022). Applicant Reactions to Artificial Intelligence in Selection (Doctoral dissertation, University of Georgia).
Hickman, L., Bosch, N., Ng, V., Saef, R., Tay, L., & Woo, S. E. (2021). Automated video interview personality assessments: Reliability, validity, and generalizability investigations. Journal of Applied Psychology. Advance online publication. https://doi.org/10.1037/apl0000695
HireVue (2021, June 7). Creating AI-driven pre-hire assessments 2021.https://www.hirevue.com/blog/hiring/creating-ai-driven-pre-employment-assessments
HireVue Discontinues Facial Analysis Screening: Decision reflects re-examination of AI hiring toolhttps://www.shrm.org/resourcesandtools/hr-topics/talent-acquisition/pages/hirevue-discontinues-facial-analysis-screening.aspx
Holtrop, D., Oostrom, J. K., van Breda, W. R. J., Koutsoumpis, A., & de Vries, R. E. (2022). Exploring the application of a text-to-personality technique in job interviews. European Journal of Work and Organizational Psychology, 1-18.https://doi.org/10.1080/1359432X.2022.2051484
Hudson, L. (2017, July 20). Technology is biased too. How do we fix it? https://fivethirtyeight. com/features/technology-is-biased-too-how-do-we-fix-it/ amp/
Hunkenschroer, A. L., & Lütge, C. (2021). How to improve fairness perceptions of AI in hiring: the crucial role of positioning and sensitization. AI Ethics Journal, 2(2)-3. https://doi.org/10.47289/AIEJ20210716-3
Junior JCSJ, Güçlütürk Y, Pérez M, Güçlü U, Andujar C, Baró X, Escalante HJ, Guyon I, Van Gerven MA, Van Lier R (2019) First impressions: a survey on vision-based apparent personality trait analysis. IEEE Transactions on Affective Computing, 1-20.https://doi.org/10.1109/TAFFC.2019.2930058
Karatop, B., Kubat, C., & Uygun, Ö. (2015). Talent management in manufacturing system using fuzzy logic approach. Computers & Industrial Engineering, 86, 127-136.https://doi.org/10.1016/j.cie.2014.09.015
Kaushal, N., Kaurav, R. P. S., Sivathanu, B., & Kaushik, N. (2021). Artificial intelligence and HRM: identifying future research Agenda using systematic literature review and bibliometric analysis. Management Review Quarterly, 1-39.
Khan, I., Gadalla, C., Mitchell-Keller, L., & Goldberg, M. S. (2016, March 2). Algorithms: The new means of production. Digitalist. Available at https://www.digitalistmag.com/ executive-research/algorithms-the-new-means-ofproduction
Köchling, A., Riazy, S., Wehner, M. C., & Simbeck, K. (2021). Highly accurate, but still discriminatory. Business & Information Systems Engineering, 63(1), 39-54.https://doi.org/10.1007/s12599-020-00673-w
Kolbjørnsrud, V., Amico, R., & Thomas, R. J. (2016, November 2). How artificial intelligence will redefine management. Harvard Business Review.https://hbr.org/2016/11/how-artificial-intelligence-will-redefine-management
Kutcher, E. J., & Bragger, J. D. (2004). Selection interviews of overweight job applicants: Can structure reduce the bias? Journal of Applied Social Psychology, 34(10), 1993-2022.https://doi.org/10.1111/j.1559-1816.2004.tb02688.x
Langer, M., König, C. J., Gebhard, P., & André, E. (2016). Dear computer, teach me manners: Testing virtual employment interview training. International Journal of Selection and Assessment, 24(4), 312-323.https://doi.org/10.1111/ijsa.12150
Langer, M., König, C. J., & Hemsing, V. (2020). Is anybody listening? The impact of automatically evaluated job interviews on impression management and applicant reactions. Journal of Managerial Psychology, 35(1), 271-284.https://doi.org/10.1108/JMP-03-2019-0156
Langer, M., König, C. J., & Krause, K. (2017). Examining digital interviews for personnel selection: Applicant reactions and interviewer ratings. International Journal of Selection and Assessment, 25(4), 371-382.https://doi.org/10.1111/ijsa.12191
Langer, M., König, C. J., & Papathanasiou, M. (2019). Highly automated job interviews: Acceptance under the influence of stakes. International Journal of Selection and Assessment, 27(3), 217-234.https://doi.org/10.1111/ijsa.12246
Lee, B. C., & Kim, B. Y. (2021). Development of an AI-based interview system for remote hiring. International Journal of Advanced Research in Engineering and Technology, 12(3), 654-663. https://doi.org/10.34218/IJARET.12.3.2021.060
Lee, M. K. (2018). Understanding perception of algorithmic decisions: Fairness, trust, and emotion in response to algorithmic management. Big Data & Society, 5(1), 2053951718756684.https://doi.org/10.1177/2053951718756684
Liem, C. C. S., Langer, M., Demetriou, A., Hiemstra, A. M. F., Achmadnoer Sukma Wicaksana, S., Born, M. ., & König, C. J. (2018). Psychology Meets Machine Learning: Interdisciplinary Perspectives on Algorithmic Job Candidate Screening. In H. Jair Escalante, S. Escalera, I. Guyon, X. Baró, & Y. Güçlütürk (Eds.), Explainable and Interpretable Models in Computer Vision and Machine Learning (pp. 197-253). (The Springer Series on Challenges in Machine Learning). Springer. https://doi.org/10.1007/978-3-319-98131-4_9
Lievens, F., Harris, M. M., Van Keer, E., & Bisqueret, C. (2003). Predicting cross-cultural training performance: The validity of personality, cognitive ability, and dimensions measured by an assessment center and a behavior description interview. Journal of Applied Psychology, 88, 476-489.https://doi.org/10.1037/0021-9010.88.3.476
Lievens, F., Highhouse, S., & De Corte, W. (2005). The importance of traits and abilities in supervisors' hirability decisions as a function of method of assessment. Journal of Occupational and Organizational Psychology, 78, 453-470. https://doi.org/10.1348/096317905X26093
Lukacik, E.R., Bourdage, J. S., & Roulin, N. (2020). Into the void: A conceptual model and research agenda for the design and use of asynchronous video interviews. Human Resource Management Review, 32(1), 100789.https://doi.org/10.1016/j.hrmr.2020.100789
Maurer, R. (2021, Feb. 3). HireVue Discontinues Facial Analysis Screening. Decision Reflects Re-Examination of AI Hiring Tools. https://www.shrm.org/resourcesandtools/hr-topics/talent-acquisition/pages/hirevue-discontinues-facial-analysis-screening.aspx.
McColl, R., & Michelotti, M. (2019). Sorry, could you repeat the question? Exploring video‐interview recruitment practice in HRM. Human Resource Management Journal, 29(4), 637-656. https://doi.org/10.1111/1748-8583.12249
Mirowska, A., & Mesnet, L. (2022). Preferring the devil you know: Potential applicant reactions to artificial intelligence evaluation of interviews. Human Resource Management Journal, 32(2), 364-383.https://doi.org/10.1111/1748-8583.12393
Morelli, N., Potosky, D., Arthur, W., & Tippins, N. (2017). A call for conceptual models of technology in IO psychology: An example from technology-based talent assessment. Industrial and Organizational Psychology, 10(4), 634-653.
Mou, Y., & Xu, K. (2017). The media inequality: Comparing the initial human-human and human-AI social interactions. Computers in Human Behavior, 72, 432-440.https://doi.org/10.1016/j.chb.2017.02.067
Mujtaba, D. F., & Mahapatra, N. R. (2021, December). Multi-Task Deep Neural Networks for Multimodal Personality Trait Prediction. In 2021 International Conference on Computational Science and Computational Intelligence (CSCI) (pp. 85-91). IEEE.
Naim, I., Tanveer, M. I., Gildea, D., & Hoque, M. E. (2016). Automated analysis and prediction of job interview performance. IEEE Transactions on Affective Computing, 9(2), 191-204.http://doi.org/10.1109/TAFFC.2016.2614299
Nass, C., & Moon, Y. (2000). Machines and mindlessness: Social responses to computers. Journal of Social Issues, 56(1), 81-103. https://doi.org/10.1111/0022-4537.00153
Newman, D. T., Fast, N. J., & Harmon, D. J. (2020). When eliminating bias isn’t fair: Algorithmic reductionism and procedural justice in human resource decisions. Organizational Behavior and Human Decision Processes, 160, 149-167.https://doi.org/10.1016/j.obhdp.2020.03.008
Oracle (2019). Report of the 2019 state of artificial intelligence in talent acquisition.http://www.oracle.com/a/ocom/docs/artificial- intelligence-in-talent-acquisition.pdf
Oswald, F. L., Behrend, T. S., Putka, D. J., & Sinar, E. (2020). Big data in industrial-organizational psychology and human resource management: Forward progress for organizational research and practice. Annual Review of Organizational Psychology and Organizational Behavior, 7, 505-533.https://doi.org/10.1146/annurev-orgpsych-032117-104553
Ötting, S. K., & Maier, G. W. (2018). The importance of procedural justice in human–machine interactions: Intelligent systems as new decision agents in organizations. Computers in Human Behavior, 89, 27-39.https://doi.org/10.1016/j.chb.2018.07.022
Qamar, Y., Agrawal, R. K., Samad, T. A., & Jabbour, C. J. C. (2021). When technology meets people: the interplay of artificial intelligence and human resource management. Journal of Enterprise Information Management, 34(5), 1339-1370.http://doi.org/10.1108/JEIM-11-2020-0436
Persson, A. (2016). Implicit bias in predictive data profiling within recruitments. In A. Lehmann, D. Whitehouse, S. Fischer-Hübner, L. Fritsch, & C. Raab (Eds.), Privacy and identity management. Facing up to next steps (Vol. 498, pp. 212-230). Cham: Springer.
Posthuma R. A., Morgeson F. P., Campion M. A. (2002). Beyond employment interview validity: A comprehensive narrative review of recent research and trends over time. Personnel Psychology, 55, 1-81.https://doi.org/10.1111/j.1744-6570.2002.tb00103.x
Purkiss, S. L., Segrest, Perrewe, P. L., Gillespie, T. L., Mayes, B. T., & Ferris, G. R. (2006). Implicit sources of bias in employment interview judgments and decisions. Organizational Behavior and Human Decision Processes, 101, 152-167.https://doi.org/10.1016/j.obhdp.2006.06.005
Rastegarpanah, B., Gummadi, K. P., & Crovella, M. (2019, February). Fighting fire with fire: Using antidote data to improve polarization and fairness of recommender systems. WSDM 2019. Proceedings of the 12th ACM International Conference on Web Search and Data Mining (pp. 231-239). New York, NY: ACM
Robert, L. P., Pierce, C., Marquis, L., Kim, S., & Alahmad, R. (2020). Designing fair AI for managing employees in organizations: A review, critique, and design agenda. Human-Computer Interaction, 35(5-6), 545-575. https://doi.org/10.1080/07370024.2020.1735391
Roberts, L. L., & Macan, T. H. (2006). Disability disclosure effects on employment interview ratings of applicants with nonvisible disabilities. Rehabilitation Psychology, 51, 239-246.https://doi.org/10.1037/0090-5550.51.3.239
Russell, S. J., & Norvig, P. (2016). Artificial intelligence: A modern approach (3rd ed.). Pearson.
Salin, E. D., & Winston, P. H. (1992). Machine learning and artificial intelligence: an introduction. Analytical Chemistry (Washington, DC), 64(1), 49A-60A.
Shin, J. E., & Lee, H. (2021). Happy Applicants Achieve More: Expressed Positive Emotions Captured Using an AI Interview Predict Performances. Science of Emotion and Sensibility, 24(2), 75-80.https://doi.org/10.14695/KJSOS.2021.24.2.75
Sitzmann, T., & Weinhardt, J. M. (2019). Approaching evaluation from a multilevel perspective: A comprehensive analysis of the indicators of training effectiveness. Human Resource Management Review, 29(2), 253-269. https://doi.org/10.1016/j.hrmr.2017.04.001
Spencer, S. J., Steele, C. M., & Quinn, D. (1999). Stereotype threat and women’s math performance. Journal of Experimental Social Psychology, 35, 4-28.https://doi.org/10.1006/jesp.1998.1373
Steele, C. M., & Aronson, J. (1997). A threat in the air: How stereotypes shape intellectual identity and performance. American Psychologist, 52(6), 613-629.https://doi.org/10.1037/0003-066X.52.6.613
Su, Y. S., Suen, H. Y., & Hung, K. E. (2021). Predicting behavioral competencies automatically from facial expressions in real-time video-recorded interviews. Journal of Real-Time Image Processing, 18(4), 1011-1021. https://doi.org/10.1007/s11554-021-01071-5
Suen, H. Y., Hung, K. E., & Lin, C. L. (2020). Intelligent video interview agent used to predict communication skill and perceived personality traits. Human-centric Computing and Information Sciences, 10(1), 1-12.
Suen, H. Y., Chen, M. Y. C., & Lu, S. H. (2019). Does the use of synchrony and artificial intelligence in video interviews affect interview ratings and applicant attitudes? Computers in Human Behavior, 98, 93-101. https://doi.org/10.1016/j.chb.2019.04.012
Topor, D. J., Colarelli, S. M., & Han, K. (2007). Influences of traits and assessment methods on human resource practitioners' evaluations of job applicants. Journal of Business and Psychology, 21, 361-376.https://doi.org/10.1007/s10869-006-9033-6
Twyman, N. W., Pentland, S. J., & Spitzley, L. (2018, July). Deception detection in online automated job interviews. In International Conference on HCI in Business, Government, and Organizations (pp. 206-216). Springer.
Uggerslev, K. L., Fassina, N. E., & Kraichy, D. (2012). Recruiting through the stages: A meta‐analytic test of predictors of applicant attraction at different stages of the recruiting process. Personnel Psychology, 65(3), 597-660. https://doi.org/10.1111/j.1744-6570.2012.01254.x
van Esch, P., Black, J. S., & Arli, D. (2021). Job candidates’ reactions to AI-enabled job application processes. AI and Ethics, 1(2), 119-130.https://doi.org/10.1007/s43681-020-00025-0
Van Iddekinge, C. H., Raymark, P. H., Roth, P. L., & Payne, H. S. (2006). Comparing the psychometric characteristics of ratings of face to‐face and videotaped structured interviews. International Journal of Selection and Assessment, 14(4), 347-359.https://doi.org/10.1111/j.1468-2389.2006.00356.x
Venkatesh, V., & Bala, H. (2008). Technology acceptance model 3 and a research agenda on interventions. Decision Sciences, 39(2), 273-315. doi: 10.1111/j.1540-5915.2008.00192.x
Vima. (2021, Sep. 23). Computational technologies and AI for automated behaviour analysis: White paper series part 4.https://vima-swiss.com/computational-technologies-and-ai-for-automated-behaviour-analysis/
Wall, S., & Schellmann, H.(2021). Linkedin’s job-matching AI was biased. The company’s solution? More AI.https://www.google.com/amp/s/www.technologyreview.com/2021/06/23/1026825/linkedin-ai- bias-ziprecruiter-monster-artificial-intelligence/amp/
Wilson, H. J., Daugherty, P., & Morini-Bianzino, N. (2017). The jobs that artificial intelligence will create. Mit Sloan Management Review (Summer 2017).
Yang, J., Im, M., Choi, S., Kim, J., & Ko, D. H. (2021). Artificial Intelligence-Based Hiring: An Exploratory Study of Hiring Market Reactions. Japan Labor Issues, 5(32), 41-55.