{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,8]],"date-time":"2026-04-08T13:27:58Z","timestamp":1775654878046,"version":"3.50.1"},"reference-count":77,"publisher":"Oxford University Press (OUP)","issue":"4","license":[{"start":{"date-parts":[[2023,6,29]],"date-time":"2023-06-29T00:00:00Z","timestamp":1687996800000},"content-version":"vor","delay-in-days":17,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"California State University, Los Angeles"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,6,12]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Theories and research in human\u2013machine communication (HMC) suggest that machines, when replacing humans as communication partners, change the processes and outcomes of communication. With artificial intelligence (AI) increasingly used to interview and evaluate job applicants, employers should consider the effects of AI on applicants\u2019 psychology and performance during AI-based interviews. This study examined job applicants\u2019 experience and speech fluency when evaluated by AI. In a three-condition between-subjects experiment (N\u2009=\u2009134), college students had an online mock job interview under the impression that their performance would be evaluated by a human recruiter, an AI system, or an AI system with a humanlike interface. Participants reported higher uncertainty and lower social presence and had a higher articulation rate in the AI-evaluation condition than in the human-evaluation condition. Through lowering social presence, AI evaluation increased speech rate and reduced silent pauses. Findings inform theories of HMC and practices of automated recruitment and professional training.<\/jats:p>","DOI":"10.1093\/jcmc\/zmad028","type":"journal-article","created":{"date-parts":[[2023,6,29]],"date-time":"2023-06-29T14:09:30Z","timestamp":1688047770000},"source":"Crossref","is-referenced-by-count":15,"title":["Speech production under uncertainty: how do job applicants experience and communicate with an AI interviewer?"],"prefix":"10.1093","volume":"28","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9019-8521","authenticated-orcid":false,"given":"Bingjie","family":"Liu","sequence":"first","affiliation":[{"name":"Department of Communication Studies, California State University , Los Angeles, CA, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4387-2779","authenticated-orcid":false,"given":"Lewen","family":"Wei","sequence":"additional","affiliation":[{"name":"School of the Arts and Media, University of New South Wales , Sydney, Australia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4312-0486","authenticated-orcid":false,"given":"Mu","family":"Wu","sequence":"additional","affiliation":[{"name":"Department of Communication Studies, California State University , Los Angeles, CA, USA"}]},{"given":"Tianyi","family":"Luo","sequence":"additional","affiliation":[{"name":"Amazon Science, Amazon.com, Inc. , Palo Alto, CA, USA"}]}],"member":"286","published-online":{"date-parts":[[2023,6,29]]},"reference":[{"issue":"4","key":"2023062914020362500_zmad028-B1","doi-asserted-by":"crossref","first-page":"399","DOI":"10.1111\/ijsa.12306","article-title":"Justice perceptions of artificial intelligence in selection","volume":"28","author":"Acikgoz","year":"2020","journal-title":"International Journal of Selection and Assessment"},{"key":"2023062914020362500_zmad028-B2","first-page":"1","volume-title":"2020 IEEE international conference for innovation in technology","author":"Adepu","year":"2020"},{"issue":"3","key":"2023062914020362500_zmad028-B3","doi-asserted-by":"crossref","first-page":"611","DOI":"10.1007\/s00146-019-00931-w","article-title":"In AI we trust? 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