Research Seminar: Professor Hillol Bala

Dear all,

Join us in welcoming Professor Hillol Bala from Indiana University to Trinity Business School on Friday, 24th of April 2026.

The seminar will take place in room 419 and via Zoom between 11 – 12:30 am.

Please REGISTER HERE.

Seminar Title: From Opacity to Transparency: Examining the Role of Transparency in Algorithmic Evaluation

Abstract: Organizations are increasingly integrating artificial intelligence (AI) into traditionally human-driven evaluation processes, such as recruitment and performance evaluations. Yet the complexity of the underlying AI algorithms often makes such processes opaque, limiting users’ understanding and potentially inducing stress and other behavioral changes. In response to these challenges, transparency is often advocated as a mitigating measure; however, its effects remain somewhat ambiguous. While transparency in algorithmic evaluation may mitigate interviewees’ stress during recruitment, it may also incentivize opportunistic impression management (IM), thereby engendering 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 around two main experiments and a quasi-field replication. In Experiment I, we found that while algorithmic evaluation increased interviewees’ stress and deceptive IM relative to human evaluation, transparency counteracted these effects, aligning them closely with human evaluation. In Experiment II, we investigate how these effects lead to deviations in downstream interview performance when such performance is assessed in human-only, AI-augmented (where human decision-makers are assisted by AI scores), or fully automated decision-making configurations. Although transparency consistently reduced deviations in stress and IM from human evaluation for interviewees, 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. Altogether, our research disentangles the dual-edged effects of transparency in algorithmic evaluation, demonstrating its capacity to both mitigate disruptions 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, policymakers, and AI developers.

* Joint work with Akshat Lakhiwal (University of Georgia), Che-Wei Liu (Arizona State University), and Hung-Yue Suen (National Taiwan Normal University)

Bio: Hillol Bala (hbala@iu.edu; ORCID: 0000-0002-3302-5015) is the Conrad Prebys Professor of Information Systems at the Kelley School of Business, Indiana University, Bloomington. His PhD is from the Walton College of Business at the University of Arkansas. His research interests include the implementation of digital technologies, such as enterprise platforms and AI-enabled systems, digital transformation 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 Information Systems, Management Science, Production and Operations Management, Journal of Operations Management, IEEE Transactions on Software Engineering, Decision Sciences, European Journal of Information Systems, Information Systems Journal, IEEE Transactions on Engineering Management, Journal of Business Research, Communications of the ACM, and MISQ Executive. He has held (or currently holds) editorial roles in major information systems journals (e.g., Information Systems Research, MIS Quarterly, and the Journal of the Association for Information Systems) and at conferences.

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@tcd.ie.