新冠疫情來襲，全球人類生活方式已隨之改變；吸引和留住合適的候選人已成為全球大多數組織人力資源管理中最關鍵和戰術性的問題之一，企業為了維持招募作業正常運作，具高度接觸風險的面對面的面
試，已不再是唯一或主流模式；就像遠距工作一樣，人工智慧有望改變每個行業和每個公司，展望未來，在 Covid-19 之後，幾乎不可避免地加
速我們在遠距面試模式的導入。
解決遠距問題的非同步視訊面試成為後疫情時代不可或缺的方式，僅是非同步面試仍無法解決後疫情時代人力不穩定的狀況，必須透過人工智慧的評鑑來增加面試效度，；本研究旨在探討求職者在實際使用非
同步視頻面試系統時，求職者得知有 AI 評鑑輔助功能下，是否會影響求職者在非同步視頻面試系統下對科技的信任度。
本研究透過 146 位求職者發現，求職者對具 AI 評鑑的非同步錄影面試相較於沒有 AI 評鑑的面試的錄影面試，有較高的認知信任，但對於認知情感則無顯著性的差異。本研究根據統計調查及分析結果，提供雇主及應徵者使用非同步視頻面試系統的教育指南，同時作導入非同步視頻面試結合人工智慧評鑑功能輔助科技的評估與相關使用者招募的參考依據。

With the advent of the Artificial Intelligence (AI) era, this research aims
to explore whether candidates know if the AI assist function will affect the applicants’ trust in technology when they interviewed by an asynchronous video interview system. This study solicited 146 applicants aged between 19 and 55 years old, through a snowball sampling method, and voluntarily participate in the asynchronous video interview system. Upon completion, applicants are required to complete an online questionnaire.
Through correlation coefficient analysis and multivariate analysis of
covariance, the study found that AI significantly boosted job applicants’ cognitive trust toward the interview technology; however their affective trust were not singianat difference between AI and Non-AI function in asynchronous video interviews. Based on the results of statistical surveys and analysis, this research provides some implications for employers and application developer when they use the AI-based asynchronous video
interview system.

一、 中文部分
水沐由之（2021，9 月 20 日）。信任是認知與情感上的付出。簡書。https://www.twblogs.net/a/614dc32c07f6b160774111a0
周維忠（2021，11 月 30 日）。人資招募掀起智慧化風潮 AI 徵才面試時代來臨。網管人。https://www.netadmin.com.tw/netadmin/zh-tw/trend/4F195ADA589943618DB430D2FB8404DB
翁芊儒（2021，3 月 3 日)。AI 面試有新工具！臺師大開發微表情 AI 辨識技術，即時預測應徵者職場性格與溝通能力，輔助 HR 聘雇決策。
iThome。https://www.ithome.com.tw/news/143000
陳鼎文（2016，4 月 26 日）。理財：你願意相信人還是機器人？科技橘報。https://buzzorange.com/techorange/2016/04/26/would-you-believe-human-or-robot-in-financial-management/
陳建鈞（2022，5 月 26 日）。AI 面試官，怎麼知道你的發展潛力？從這 86 個微表情可看出。數位時代。https://www.bnext.com.tw/article/57846/ai-interview-aurora-anymind
錢國倫、陳怡靜、陳建丞（2013）。工作與組織特性與求職者人格特質之交互作用對組織人才吸引力的影響。人力資源管理學報，13（1），1-32。http://rportal.lib.ntnu.edu.tw/handle/20.500.12235/36409HRDA（2022）。HRDA 智能視頻面試系統 https://hrda.pro
二、 英文部分
Allal-Chérif, O., Aránega, A. Y., & Sanchez, R. C. (2021). Intelligent recruitment: How to identify, select, and retain talents from around the world using artificial intelligence. ScienceDirect, 169.
doi.org/10.1016/j.techfore.2021.120822
Anderson, N. (2003). Applicant and recruiter reactions to new technology in
selection: A critical review and agenda for future research. International Journal of Selection and Assessment, 11, 121-136.
https://onlinelibrary.wiley.com/doi/10.1111/1468-2389.00235
Barrick, M. R., Shaffer, J. A., & DeGrassi, S. W. (2009). What you see may not be what you get: relationships among self-presentation tactics and
ratings of interview and job performance. Journal of Applied Psychology, 94(6), 1394. doi.org/10.1037/a0016532
Bigman, Y. E., Gray, K., Waytz, A., Arnestad, M., & Wilson, D. (2020). Algorithmic discrimination causes less moral outrage than human discrimination. Journal of Experimental Psychology: General, 1-24.
doi.org/10.31234/osf.io/m3nrp
Blacksmith, N., Willford, J., & Behrend, T. (2016). Technology in the Employment Interview: A Meta-Analysis and Future Research Agenda. Personnel Assessment and Decisions, 2(1). 12-20.
doi.org/10.25035/pad.2016.002
Bonaccio, S., & Dalal, R. S. (2006). Advice taking and decision-making: An integrative literature review, and implications for the organizational sciences. Organizational Behavior and Human Decision Processes, 101(2), 127–151. doi.org/10.1016/j.obhdp.2006.07.001
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 [Original Research]. Frontiers in Psychology, 7, 1-11. doi.org/10.3389/fpsyg.2016.00863
Borzykowski, B. (2016). Truth be told, we’re just more honest with machines. BBC. https://www.bbc.com/worklife/article/20160412-truth-be-told-were-more-honest-with-robots?ocid=twcptl
Chamorro, T., Akhtar, R., Winsborough, D., & Sherman, R. A. (2017). The datafication of talent: How technology is advancing the science of human potential at work. Current Opinion in Behavioral Sciences, 18,
13–16. Doi.org/10.1016/j.cobeha 2017.04.007
Chong, L., Zhang, G., Goucher-Lambert, K., Kotovsky, K., & Cagan, J. (2022). Human confidence in artificial intelligence and in themselves: The evolution and impact of confidence on adoption of AI advice. Computers in Human Behavior, 127, 1-10. doi.org/10.1016/j.chb.2021.107018
Chua, R. Y. J., Ingram, P., & Morris, M. W. (2008). From the head and the heart: Locating cognition-and affect-based trust in managers’ professional networks. Academy of Management journal, 51(3), 436-452. doi.org/10.5465/amj.2008.32625956
Christoforakos, L., Gallucci, A., Surmava-Große, T., Ullrich, D., & Diefenbach, S. (2021). Can Robots Earn Our Trust the Same Way Humans Do? A Systematic Exploration of Competence, Warmth, an
d Anthropomorphism as Determinants of Trust Development in HRI. Frontiers in Robotics and AI, 8, 79. doi.org/10.3389/frobt.2021.640444
Cheng, M., & Hackett, R. D. (2021). A critical review of algorithms
in HRM: Definition, theory, and practice. Human Resource Management Review, 31(1), 1-14. Doi.org/10.1016/j.hrmr.2019.100698Derek S. Chapman. & Webster, J. (2003). The Use of Technologies in the Recruiting, Screening, and Selection Processes for Job Candidates. International Journal of Selection and Assessment 11(2). 113-119.
doi:10.1111/1468-2389.00234
Dzindolet, M.T., Pierce, L.G., Beck, H.P., & Dawe, L.A. (2002). The perceived utility of human and automated aids in a visual detection task. Human Factors, 2002, 79-94. Doi.org/10.1518/00187200244
94856
Endsley, M. R. (2017). From here to autonomy: Lessons learned from human–automation research. Human Factors, 59(1), 5–27. doi.org/10.1177/0018720816681350
Epley, N., Waytz, A., Cacioppo, J. T. (2007). On seeing human: A three-factor theory of anthropomorphism. Psychological Review, 114, 864–886. doi:10.1037/0033-295X.114.4.864
Escalante, H. J., Kaya, H., Salah, A., Escalera, S., Gucluturk, Y., Guclu,
U., . . . Madadi, M. (2018). Explaining first impressions: modeling, recognizing, and explaining apparent personality from videos. Cornell University. https://arxiv.org/abs/1802.00745
Esch, P., & Stewart Black, J., (2019). Factors that influence new generation
candidates to engage with and complete digital, AI-enabled recruiting.Business Horizons, 62(6), 729-739.
Doi.org/10.1016/j.bushor.2019.07.004
Gilmore, D.C., & Ferris, G.R. (1989). The effects of applicant impression management tactics on interviewer judgments. Journal of Management, 15(4), 557-564.doi.org10.1177/014920638901500405
Glikson, E., & Williams, A., (2020) Human trust in artificial intelligence: Review of empirical research. Academy of Management Annals (in press). The Academy of Management Annals. https://www.res earchgate.net/publication/340605601
Hancock, P. A., Billings, D. R., Schaefer, K. E., Chen, J. Y., De Visser, E. J., and Parasuraman, R. (2011). A meta-analysis of factors affecting trust in human-robot interaction. Human Fact, 53, 517–527.
doi.org/10.1177%2F0018720811417254
Huffcutt,A., Culbertson,C., & Weyhrauch,W. (2014). Moving Forward Indirectly: Reanalyzing the validity of employment interviews with indirect range restriction methodology. International Journal of
Selection and Assessment, 22(3), 297-309. dio:10.1111/ijsa.12078
Hoff, K. A., & Bashir, M. (2015). Trust in automation: Integrating empirical
evidence on factors that influence trust. Human Factors, 57(3), 407–
434. Doi.org/10.1177/0018720814547570
Horn, R. G., & Behrend, T. S. (2016). Video killed the interview star:Does picture-in-picture affect interview performance? Personnel assessment. https://scholarworks.bgsu.edu/cgi/viewcontent.cgi?article=1035&context=pad
Jenny S. Wesche., & Andreas Sonderegger. (2021). Repelled at first sight?
Expectations and intentions of job-seekers reading about AI selection in
job advertisements. Computers in Human Behavior, 125, 1-15.
doi.org/10.1016/j.chb.2021.106931
Jordan, M. I., & Mitchell, T. M. (2015). Machine learning: Trends, perspectives, and prospects. Science, 349(6245), 255-260.
Kaiser, H. F. (1960). The application of electronic computers to factor analysis. Educational and psychological measurement, 20(1), 141-151.
doi.org/10.1177/001316446002000116
Kulms, P., and Kopp, S. (2018). A social cognition perspective on human–
computer trust: the effect of perceived warmth and competence on trust
in decision-making with computers. Front. Digital Humanit, 5, 14. doi: 10.3389/fdigh.2018.00014
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.
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.
doi.org/10.1111/ijsa.12246
Langer, M., König, C. J., Back, C., & Hemsing, V. (2021). Trust in Artificial
Intelligence: Comparing trust processes between human and automated
trustees in light of unfair bias. PsyArXiv Preprints. https://psyarxiv.com/r9y3t/
LeCun, Y., Bengio, Y., & Hinton, G. (2015). Deep learning. Nature, 521, 436-444. https://www.nature.com/articles/nature14539
Lee, J. D., & See, K. A. (2004). Trust in automation: Designing for a
ppropriate reliance. Human Factors, 46(1), 50–80. doi.org/10.1518/hfes.46.1.50.30392
Lee, M. K. (2018). Understanding perception of algorithmic decisions:
Fairness, trust, and emotion in response to algorithmic management. Big Data & Society, 5(1), 1-16. doi.org/10.1177/2053951718756684
Lewis, M., Sycara, K., & Walker, P. (2018). The role of trust in human-robot
interaction. In Hussein A. Abbass, Jason Scholz, Darryn J. Reid, Foundations of trusted autonomy (pp.135-159). Berlin: Springer.doi.org10.1007/978-3-319-64816-3
Levashina, J., Hartwell, C. J., Morgeson, F. P., & Campion, M. A. (2014). The structured employment interview: Narrative and quantitative review of the research literature. Personnel Psychology, 67(1), 241-293. doi.org/10.1111/peps.12052
Liem, C. C., Langer, M., Demetriou, A., Hiemstra, A. M., Wicaksana, A. S., Born, M. P., & König, C. J. (2018). Psychology meets machine learning: Interdisciplinary perspectives on algorithmic job candidate screening. In Hugo Jair Escalante, Sergio Escalera, Isabelle
Guyon, Xavier Baró, Yağmur Güçlütürk, Umut Güçlü, Marcel van Gerven, Explainable and interpretable models in computer vision and machine learning (pp.197-253). Berlin: Springer. doi.org/10.
1007/978-3-319-98131-4_9
Langer., M., König, C. J., Back, C., & 8 Hemsing, V. Trust in Artificial Intelligence: Comparing trust processes between human and automated trustees in light of unfair bias. Journal of Business and
Psychology.122(1) 1-16. .http://dx.doi.org/10.31234/osf.io/r9y3t
Longoni, C.,& Cian, L., (2021). When Do We Trust AI’s Recommendations More Than People’s?. Harvard Business Review Home. https://hbr.org/2020/10/when-do-we-trust-ais-recommendations-more-than-p
eoples
Mary T.Dzindolet., Scott Petersona Regina ., Pomranky., Linda G. Pierce., Hall P. Beck.(2003) The role of trust in automation reliance.
ScienceDirect. 58(6), 697-718. doi.org/10.1016/S1071-5819(03)00038-
7
Mara, M., Keshmir,S., Pomranky., & Perugia, G.,(2021) Can Robots Earn
Our Trust the Same Way Humans Do? A Systematic Exploration of Competence, Warmth, and Anthropomorphism as Determinants of Trust Development in HRI. Frontiers in Robotics and AI. 1-15.
doi.org/10.3389/frobt.2021.640444
Mayer, R. C., Davis, J. H., and Schoorman, F. D. (1995). An integrative model of organizational trust. The Academy of Management Review, 20(3), 709–734. doi: 10.5465/amr.1995.9508080335
Mejia, C., & Torres, E. N. (2018). Implementation and normalization process of asynchronous video interviewing practices in the hospitality industry. International Journal of Contemporary Hospitality Management, 30(2), 685-701. doi.org/10.1108/ijchm-07-2016-0402
Meyer, E. (2015). Building Trust Across Cultures. 74nstead Knowledge,
https://knowledge.insead.edu/blog/74nstead-blog/building-trust-across-cultures-3844
Nestler, S., & Back, M. D. (2013). Applications and extensions of the lens
model to understand interpersonal judgments at zero acquaintance.
Current Directions in Psychological Science, 22(5), 374-379.
doi.org/10.1177/0963721413486148
Nestler, S., Egloff, B., Küfner, A. C., & Back, M. D. (2012). An integrative lens model approach to bias and accuracy in human inferences: Hindsight effects and knowledge updating in personality judgments. Journal of personality and social psychology, 103(4), 689.
doi.org/10.1037/a0029461
Ö tting, 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.
doi.org/10.1016/j.chb.2018.07.022
Pathak, A., & Rana, S. (2021). Transforming Human Resource Functions
with Automation. Pennsylvania : IGI Global, 192.
https://www.igi-global.com/gateway/book/244371
Pessach, D., Singer, G., Avrahami, D, Chalutz, H., Shmueli, E., & Ben-Gal,
I., (2020). Employees recruitment: A prescriptive analytics approach via
machine learning and mathematical programming. ScienceDirect, 134,
11-18. doi.org/10.1016/j.dss.2020.113290
Potosky, D. (2008). A conceptual framework for the role of the administration medium in the personnel assessment process. Academy of Management Review, 33(3), 629- 648.
https://www.jstor.org/stable/20159428
Powers, S. R., Rauh, C., Henning, R. A., Buck, R. W., & West, T. V. (2011).
The effect of video feedback delay on frustration and emotion communication accuracy. Computers in Human Behavior, 27(5), 1651–
1657. doi.org/10.1016/j.chb.2011.02.003
Raisch, S., & Krakowski, S. (2021). Artificial intelligence and managemen
t: The automation–augmentation paradox. Academy of Management Rev
iew, 46(1), 192-210. https://www.igi-global.com/gateway/chapter/269762
Rao, A., & Cameron, E. (2018). The Future of Artificial Intelligence
Depends on Trust. If it is to drive business success, AI cannot hide in a black box. Strategy+ business.https://www.strategy-business.com/article/The-Future-of-Artificial-Intelligence-Depends-on-Trust
Roth, P. L., & Huffcutt, A. I. (2013). A meta-analysis of interviews and cognitive ability: Back to the future? Personnel Psychology, 12, 157-169. doi:10.1027/1866-5888/a000091
Komiak, & Benbasat. (2006). The Effects of Personalization and Familiarity on Trust and Adoption of Recommendation Agents. MIS Quarterly, 30(4), 941-960. https://doi.org/10.2307/25148760
Sheridan Wall & Hilke Schellmann. (2021). Archive page, Looking for
work? Here’s how to write a résumé that an AI will love. MIT Technology Review. https://www.technologyreview.com/about/
Shijiao (Joseph) Chen., DoniaWaseem., Zhenhua (Raymond) Xia., Khai Trieu Tran., YiLi., & Jun Yaoa1(2021). To disclose or to falsify: The effects of cognitive trust and affective trust on customer cooperation in
contact tracing. International Journal of Hospitality Management, 94.&Doi.org/10.1016/j.ijhm.2021.102867
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.
doi:org/10.1016/j.cviu.2016.01.009
Suen, H.-Y., Hung, K.-E., & Lin, C.-L. (2019). TensorFow-based auto matic personality recognition used in asynchronous video interviews. IEEE Access, 7, 61018-61023. Doi.org/10.1109/ACCESS.2019.29
02863
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.Doi.org/10.1186/s13673-020-0208-3
Swider, B. W., Barrick, M. R., & Harris, T. B. (2016). Initial impressions:
What they are, what they are not, and how they influence structured
interview outcomes. Journal of Applied Psychology, 101(5), 625.
Doi.org/10.1037/apl0000077
Stanton ,B.& Jensen, T. (2021). Trust and Artificial Intelligence. Maryl
and: National Institute of Standards and Technology. Tambe, P., Cappelli, P., & Yakubovich, V. (2019). Artificial Intelligen
ce in Human Resources Management: Challenges and a path forward. California Management Review, 61(4), 15-42. doi.org/10.1177/0008125619867910
Tschöpe, N., & Brandt, O. (2020). The Impact of AI on Asynchronous
Video Interviews. AON Talent Assessment Blog. https://insights.hum
ancapital.aon.com/talent-assessment-blog/the-impact-of-ai-on-asynchronous-video-interviews
Wang, L. (2019). Breaking the AI black box, what is the Trustable AI that governments are striving to develop. Tech Orange AppWorks Accelerator. https://buzzorange.com/techorange/2019/06/06/trustable-ai/
Wang, W., Qiu, L., Kim, D., & Benbasat, I. (2016). Effects of rational and social appeals of online recommendation agents on cognition- and affect-based trust. Decision Support Systems, 86, 48–60.
doi.org/10.1016/j.dss.2016.03.007
Whitener, E. M. (1997). The impact of human resource activities on employee trust. Human Resource Management Review, 7(4), 389-404. https://doi.org/10.1016/S1053-4822(97)90026-7
Yagoda, R. E., & Gillan, D. J. (2012). You want me to trust a ROBOT? The development of a human–robot interaction trust scale. International Journal of Social Robotics, 4(3), 235-248. doi.org/10.1007/s12369-012-0144-0