1933: Understanding and Managing AI-Induced Quiet Quitting: A Multifaceted Approach (14964)

Organizer(s)

• MM

  MaQueba Massey

  Iowa State U., United States

Presenter(s)

• LL

  Liza Lybolt

  Texas A&M International U.

Participant(s)

• OC

  Olga Chapa

  U. of Houston, Victoria, United States

Presenter(s)

• RA

  Raghida Abdallah Yassine

  Adelphi U., United States

Participant(s)

• GP

  Gagan Pradhan

  Adelphi U.

Presenter(s)

• PM

  Pearl Malhotra

  Indian Institute of Management, Bangalore, India
• LY

  Lu Yu

  Missouri State U., United States

Participant(s)

• HR

  Hong Ren

  U. of Wisconsin, Milwaukee, United States
• XZ

  Xiaoxia Zhu

  U. of Wisconsin-milwaukee, United States

In the ever-evolving landscape of organizations, the introduction of artificial intelligence (AI) has brought forth a dynamic interplay of opportunities and challenges. A pressing challenge in this context is the phenomenon of "Quiet Quitting" (QQ), where employees silently disengage while technically remaining employed. AI plays a pivotal role in QQ, capable of both exacerbating and alleviating this disengagement trend. Thoughtfully employed, AI-powered solutions can enhance worker satisfaction and engagement by enabling more equitable performance assessments, delivering real-time feedback, and offering tailored learning and development opportunities. Furthermore, addressing algorithmic biases in AI systems can promote fairness and inclusivity in the workplace, thus mitigating the factors contributing to QQ. Ethical and effective integration of AI is paramount for organizations in the current HRM landscape. Building trust and assuaging employee concerns about job security and skill obsolescence through transparent communication and active involvement are essential steps. This proposal seeks to comprehensively explore how AI influences QQ, providing valuable insights and novel management strategies relevant to HRM professionals, addressing the multifaceted impact of AI on QQ and its significance in optimizing HR practices and consulting strategies in the AI-driven workplace.

Presentations:

• 09:45 – 11:15 CT (GMT-5/UTC-5)

  1933: The Perplexities of Artificial Intelligence: A Study of Employee Dynamics and Quiet Quitting (QQ) (14964)
  

  Author: Liza Lybolt – Texas A&M International U.

  Author: Olga Chapa – U. of Houston, Victoria
• 09:45 – 11:15 CT (GMT-5/UTC-5)

  1933: Exploring the Interplay between Trait Emotional Intelligence, Work Motivation, and AI (14964)
  

  Author: Raghida Abdallah Yassine – Adelphi U.

  Author: Gagan Pradhan – Adelphi U.
• 09:45 – 11:15 CT (GMT-5/UTC-5)

  1933: Bias in AI-Generated Performance Feedback and the Rise of "Quiet Quitting" (14964)
  

  Author: MaQueba Massey – Iowa State U.
• 09:45 – 11:15 CT (GMT-5/UTC-5)

  1933: Artificial Intelligence: A tool for Managing Quiet Quitting by Organisations (14964)
  

  Author: Pearl Malhotra – Indian Institute of Management, Bangalore
• 09:45 – 11:15 CT (GMT-5/UTC-5)

  1933: Quiet Quitting in the Era of AI Integration: Unraveling the Dynamics in the Modern Workplace (14964)
  

  Author: Lu Yu – Missouri State U.

  Author: Hong Ren – U. of Wisconsin, Milwaukee

  Author: Xiaoxia Zhu – U. of Wisconsin-milwaukee