MIS Distinguished Speaker Series

Temple University

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Human vs AI

April 3 – Detmar Straub to present “A Dark Future for AI: The Looming Spectre of SkyNet?”

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A Dark Future for AI: The Looming Spectre of SkyNet?

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Detmar W. Straub

Professor and IBIT Research Fellow

Temple University Fox School of Business

Regents Professor Emeritus

University System of Georgia and Georgia State University

Friday, April 3

10:30 – 12:00 pm | Zoom

Abstact:

Capabilities of AI and thinking/learning machines are clearly overtaking human abilities (a.k.a. “technological singularity” or, more plainly speaking, “singularity”), with several forecasters like Winograd (2006) predicting that machine will outthink us within the first half of the 21st century. Is it possible that humans will not be able to control the burgeoning intelligence of machines and that we will, frighteningly, be subordinated to them, especially as they become self-aware? This talk starts by sketching out some past and present forecasts of when technological singularity will be real and present, what social, economic, and political issues will emerge, what security issues will loom, and finally how futurists (including science fiction writers and the movies) have envisioned the role of human beings in the coming era of the thinking machine. While the future of humanity might be hanging in the balance, one key academic question arises. What should researchers, in particular information systems researchers, study w/r/t AI? This overall issue has been framed as IA versus AI, or intelligence (human) augmentation (IA) versus artificial (computer) intelligence (AI). Enduring research questions might include: (1) technical issues with achieving singularity and requirements such as designing a tamper-proof “kill” switch for intelligent machines; (2) behavioral questions such as the pace of change and problems with duplicating human creativity; (3) social-economic conundrums such what will people do in an era of omnipresent thinking/working machines and worldwide societal disruption; and (4) organizational matters such as will there be an IS/IT Dept. and, if so, what will it do?

April 24 – Xueming Luo to present “Quantifying the Impact of Human-AI Supervisor Assemblages on Employee Performance: A Field Experiment”

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Quantifying the Impact of Human-AI Supervisor Assemblages on Employee Performance: A Field Experiment

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Xueming Luo

Founder/Director of Global Center on Big Data in Mobile Analytics
Charles Gilliland Distinguish
Chair Professor of Marketing, Strategy, and MIS
Fox School of Business
Temple University

Friday, April 24

10:30 – 12:00 pm | Zoom

Abstact:

Despite the promises of artificial intelligence (AI), there are concerns from both employees and managers about adopting AI at workplaces. Examining how firms can integrate AI into performance management systems (PMS), this research focuses on the impact of various human-AI supervisor assemblages on employees’ task performances and relations with human bosses. We utilize data from a field experiment on customer service employees in a fintech company who are randomly assigned to receive job performance feedback from human managers only, an AI bot only, or human-AI supervisory assemblages. A unique feature in our experiment is that the assemblages encompass a dual human-and-AI configuration (where employees receive feedback from both human managers and an AI bot in parallel) and a shadow-AI-human-face configuration (where employees receive feedback that is generated by an AI bot but delivered by human managers). The results suggest that relative to conventional human supervision, a dual human-and-AI design negatively impacts employee task performance, whereas a shadow-AI-human-face design positively impacts employee task performance. Explorations of the mechanisms support that a dual condition with both AI and human supervision in parallel leads employees to perceive more confused leadership and feedback, less learning from the feedback, and lower employee-manager relationship quality in a vicious cycle. In contrast, the shadow-AI design significantly improves employees’ perceptions of feedback accuracy and consistency, willingness to proactively seek feedback, and organizational commitment in a virtuous cycle. These findings suggest that firms should prudently design the human-AI supervisory assemblages. As a double-edged sword, AI-based PMS should be deployed in the shadows to empower human managers, rather than to displace or compete with them, to achieve higher worker productivity and healthier employee-manager relationships.