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DTSTAMP:20260626T133123Z
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DTSTART;TZID=Europe/Dublin:20260424T110000
DTEND;TZID=Europe/Dublin:20260424T123000
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CREATED:20260330T123930
DESCRIPTION: Seminar Title: From Opacity to Transparency: Examining the Rol
 e of Transparency in Algorithmic Evaluation \n\n Abstract: Organizations a
 re increasingly integrating artificial intelligence (AI) into traditionall
 y human-driven evaluation processes\, such as recruitment and performance 
 evaluations. Yet the complexity of the underlying AI algorithms often make
 s such processes opaque\, limiting users’ understanding and potentially 
 inducing stress and other behavioral changes. In response to these challen
 ges\, transparency is often advocated as a mitigating measure\; however\, 
 its effects remain somewhat ambiguous. While transparency in algorithmic e
 valuation may mitigate interviewees’ stress during recruitment\, it may 
 also incentivize opportunistic impression management (IM)\, thereby engend
 ering a transparency paradox. Focusing on this tension\, we theorize that 
 while algorithmic evaluation\, relative to human evaluation\, may heighten
  stress and deceptive IM in the recruitment process\, transparency has the
  potential to mitigate these disruptions. We test this in eight studies ar
 ound two main experiments and a quasi-field replication. In Experiment I\,
  we found that while algorithmic evaluation increased interviewees’ stre
 ss and deceptive IM relative to human evaluation\, transparency counteract
 ed these effects\, aligning them closely with human evaluation. In Experim
 ent II\, we investigate how these effects lead to deviations in downstream
  interview performance when such performance is assessed in human-only\, A
 I-augmented (where human decision-makers are assisted by AI scores)\, or f
 ully automated decision-making configurations. Although transparency consi
 stently reduced deviations in stress and IM from human evaluation for inte
 rviewees\, its corrective effect on interview performance was constrained 
 on the evaluative side: when AI scores were present\, evaluators tended to
  anchor on them\, discounting their own judgment\, especially when the AI 
 scores failed to distinguish between honest and deceptive behaviors. Altog
 ether\, our research disentangles the dual-edged effects of transparency i
 n algorithmic evaluation\, demonstrating its capacity to both mitigate dis
 ruptions in socio-behavioral reactions and improve interview performance. 
 We discuss the theoretical implications of algorithmic decision-making and
  socio-technical systems and provide insights for organizations\, policyma
 kers\, and AI developers. \n\n * Joint work with Akshat Lakhiwal (Universi
 ty of Georgia)\, Che-Wei Liu (Arizona State University)\, and Hung-Yue Sue
 n (National Taiwan Normal University) \n\n Bio: Hillol Bala (hbala@iu.edu\
 ; ORCID: 0000-0002-3302-5015) is the Conrad Prebys Professor of Informatio
 n Systems at the Kelley School of Business\, Indiana University\, Blooming
 ton. His PhD is from the Walton College of Business at the University of A
 rkansas. His research interests include the implementation of digital tech
 nologies\, such as enterprise platforms and AI-enabled systems\, digital t
 ransformation in organizations\, and the use\, adaptation\, and impacts of
  technology. His work has appeared in premier academic journals\, such as 
 MIS Quarterly\, Information Systems Research\, Journal of Management Infor
 mation Systems\, Management Science\, Production and Operations Management
 \, Journal of Operations Management\, IEEE Transactions on Software Engine
 ering\, Decision Sciences\, European Journal of Information Systems\, Info
 rmation Systems Journal\, IEEE Transactions on Engineering Management\, Jo
 urnal of Business Research\, Communications of the ACM\, and MISQ Executiv
 e. He has held (or currently holds) editorial roles in major information s
 ystems journals (e.g.\, Information Systems Research\, MIS Quarterly\, and
  the Journal of the Association for Information Systems) and at conference
 s. \n\n Photographs will be taken during this seminar and may be shared on
  social media. If you do not wish to appear\, please notify tbs.research@t
 cd.ie. \n
LAST-MODIFIED:20260622T084545
LOCATION:TBS Room 419 & via Zoom
ORGANIZER:mailto:TBS.Research@tcd.ie
SUMMARY:CDBA Research Seminar: Prof Hillol Bala
URL;VALUE=URI:https://ti.to/trinity-business-school/research-seminar-hillol
 -bala
URL;VALUE=URI:https://ti.to/trinity-business-school/research-seminar-hillol
 -bala
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