IE Seminar: “Human and Machine: The Impact of Machine Input on Decision-Making Under Cognitive Limitations”, Caner Canyakmaz, 1:30PM April 7 (EN)

Speaker: Caner Canyakmaz, Ozyegin University

Date & Time: April 7, 2023, Friday 13:30

Place: EA-409

Title: Human and Machine: The Impact of Machine Input on Decision-Making Under Cognitive Limitations

Abstract: The rapid adoption of AI technologies by many organizations has recently raised concerns that AI may eventually replace humans in certain tasks. In fact, when used in collaboration, machines can significantly enhance the complementary strengths of humans. Indeed, because of their immense computing power, machines can perform specific tasks with incredible accuracy. In contrast, human decision-makers (DM) are flexible and adaptive but constrained by their limited cognitive capacity. This paper investigates how machine-based predictions may affect the decision process and outcomes of a human DM. We study the impact of these predictions on decision accuracy, the propensity, and the nature of decision errors as well as the DM’s cognitive efforts. To account for both flexibility and limited cognitive capacity, we model the human decision-making process in a rational inattention framework.

In this setup, the machine provides the DM with accurate but sometimes incomplete information at no cognitive cost. We fully characterize the impact of machine input on the human decision process in this framework.

We show that machine input always improves the overall accuracy of human decisions, but may nonetheless increase the propensity of certain types of errors (such as false positives). The machine can also induce the human to exert more cognitive effort, even though its input is highly accurate. Interestingly, this happens when the DM is most cognitively constrained, for instance, because of time pressure or multitasking.
Synthesizing these results, we pinpoint the decision environments in which human-machine collaboration is likely to be most beneficial. Our main insights hold for different information and reward structures, and when the DM mistrust the machine.

Bio: Caner Canyakmaz is an assistant professor of Operations Management at Ozyegin University, Faculty of Business. He earned his Ph.D. in Industrial Engineering & Operations Management at Koç University in 2017, and his B.Sc. degree in Industrial Engineering at Bilkent University in 2011. Prior to joining Ozyegin University, he worked as a postdoctoral researcher at ESMT Berlin where he taught courses in MBA and Master in Management Programs aside from his research activities.

His current research focuses on investigating the impact of customers’
and firms’ information acquisition strategies on operational systems and decision-making. His broad research lies in the areas of stochastic modeling, inventory management, queueing, and the interface of operations and finance.