Economic AI-Human Interactions
Preferences in human feedback, timing for AI-human interactions.
Job Market Paper
Dynamic Binary Elicitation Method
with Jing Zhou.
Beliefs or perceptions play a central role in studying economic behavior, yet eliciting them accurately presents challenges. We introduce a novel elicitation method, called
the \textit{Dynamic Binary Method} (DBM), designed to address the common challenge individuals face in pinpointing the best point estimate of their beliefs, particularly when their beliefs are imprecise.
Unlike Classical Methods (CM), which require respondents to form a point estimate of their true beliefs, DBM prompts respondents to make a series of binary relative judgments and enables them to express
interval beliefs by exiting the process at any step. After the exit, we will randomly pick a number in the interval as their final beliefs.
We conduct both within-subject and between-subject experiments using a diverse range of perception tasks drawn from previous literature and CM as a benchmark of performances in each task. We find that,
at the aggregate level, DBM does not perform significantly differently from CM, regardless of whether the perception tasks involve artificial/laboratory settings or real-life scenarios, and irrespective
of the performance metric used. However, DBM has an asymmetric effect relative to CM: individuals who performed poorly under CM tend to improve under DBM, while those who performed well under CM tend to
do worse under DBM. This asymmetry can be explained by the rational inattention framework: when the DBM methodology aligns with an individual's optimal information structure in the CM methodology, they perform
better under DBM; otherwise, performance may not improve and could even decline.
While group identity can generate in-group bias, the topic of how activities generate group affiliation is largely
unexplored. We experimentally study the effect of shared experience on group affiliation, varying shared
experiences by paying subjects differently for the same task. The results show that shared fortune leads to
in-group bias, while shared misfortune does not.
Working Paper
Pinocchio's Clock: Using Response Time to Detect Deception in Sender-Receiver Games
with Bohan Ye, Submitted.
The inclusion of Response Time (RT) stamps has become a common feature of contemporary social media sites and applications. What private information does the response time carry when there is a
conflict of interest between users? Can people use it to improve their welfare in communication? We develop a framework and design a sender-receiver experiment to examine the relationship between
RT and honesty in communication. We find that long RT is associated with a higher likelihood of deceit, consistent with predictions from the drift-diffusion model when assuming that lying requires
more cognitive struggle. Receivers tend to overtrust slow messages, and the composition of RT affects receivers' interpretation of RT.
Teaching Experience
Instructor
Principles of Microeconomics (Fall 2025, USC)
Corporation Finance (Winter 2020, Spring 2020, UCSB)
Co-Instructor
Principles of Microeconomics(Spring 2025, USC)
Teaching Assistant at UCSB
Corporate Finance, 3 quarters
Intermediate Microeconomics, 3 quarters
Introduction to Game Theory, 3 quarters
Principles for Microeconomics, 3 quarters
Principles for Macroeconomics, 1 quarter