625: AI-Enabled Respect: How Framing of AI Affects Occupational Stigma Toward Dirty Work (18430)

Sunday, August 11, 2024

09:45 – 11:15 CT (GMT-5/UTC-5)

Location: Hyatt: Michigan 1A

Session Number: 625
Paper Session
Orientation: Theme,Research
Shareable link: https://cdmcd.co/raqbG3

Author(s)

YG

Yuqing Gan

School of Business, Sun Yat-sen U.
XZ

Xiang Zhou

Sun Yat-Sen U., China
RZ

Rongrong Zhang

The Chinese U. of Hong Kong, Shenzhen, China
LJ

Luyuan Jiang

China U. of Mining and Technology, China
SM

Shuying Mao

School of Business, Sun Yat-sen U.

Although past research has explored various strategies for coping with occupational stigma, there has been a relative neglect in examining the role of technology development, particularly the transformative impact of artificial intelligence (AI). Integrating signaling theory and meaningful work literature, we develop a model that specifies when and why framing of AI used by the organization involved in dirty work changes people’s perception of dirty work. Using a multi-wave survey and two experiments, we find that framing AI as an augmentation (as opposed to automation) is positively associated with people’s perceived meaningfulness of dirty work, which is further negatively associated with occupational stigma toward dirty work. In addition, we find that people’s fixed mindset weakens the indirect effect of framing of AI on occupational stigma through perceived meaningfulness of dirty work. We discuss our theoretical and practical contributions and propose future directions.

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