Investigating Writing Professionals' Relationships with GenAI: How Combined Perceptions of Rivalry and Collaboration Shape Work Practices and Outcomes

Paper Title

Investigating Writing Professionals' Relationships with GenAI: How Combined Perceptions of Rivalry and Collaboration Shape Work Practices and Outcomes

Publication Info

• Topic area: Human-Computer Interaction (HCI) and the impact of Generative AI (GenAI) on writing professions.
• Keywords: Generative AI, professional writing, collaboration, rivalry, job crafting, skill maintenance, productivity, satisfaction.

Background and Problem

• Problem / challenge: Prior research on GenAI in professional contexts often treats collaboration and rivalry as isolated phenomena, failing to account for their co-occurrence and combined effects on work practices and outcomes.
• Significance: Understanding the dual relationship between rivalry and collaboration with GenAI is critical for shaping sustainable work practices and enhancing long-term career outcomes for writing professionals.
• Motivation and related work: Previous studies have explored GenAI's potential to augment or displace professional roles, emphasizing either collaboration or resistance. However, these perspectives overlook how professionals simultaneously navigate both orientations, creating a gap in understanding the nuanced impacts of GenAI on work practices and outcomes.

Solution

• Proposed approach: A cross-sectional survey study investigating how writing professionals' perceptions of rivalry and collaboration with GenAI independently and jointly associate with job crafting, skill maintenance, productivity, and satisfaction.
• Novelty:
  1. Demonstrates the independent and combined effects of rivalry and collaboration orientations on work practices and outcomes.
  2. Highlights the trade-offs between short-term gains (productivity, satisfaction) and long-term sustainability (skill maintenance).
  3. Proposes design strategies to balance rivalry and collaboration, fostering healthier relationships with GenAI.
• Procedure and key techniques:
  • Conducted a survey with 403 professional writers using validated and adapted scales for rivalry, collaboration, job crafting, skill maintenance, productivity, and satisfaction.
  • Applied linear regression for confirmatory analysis (RQ1) and Response Surface Analysis (RSA) with clustering (PAM) for exploratory analysis (RQ2).
  • Analyzed qualitative responses to understand patterns in skill maintenance.

Results

• Concrete findings:
  • Rivalry was strongly associated with skill maintenance and relational crafting but showed weaker associations with productivity and satisfaction.
  • Collaboration was strongly associated with productivity, satisfaction, and task crafting but correlated less with skill maintenance.
  • Combined high rivalry and high collaboration (HighR/HighC) yielded the strongest associations with job crafting and skill maintenance.
  • High collaboration alone (LowR/HighC) corresponded to the highest levels of productivity and satisfaction.
• Advantage over baselines:
  • Joint modeling of rivalry and collaboration explained more variance in job crafting and productivity compared to independent models.
  • HighR/HighC profiles balanced long-term skill maintenance with short-term productivity gains, unlike profiles dominated by either rivalry or collaboration alone.
• Experiments / evaluation:
  • Survey included demographic stratification and Likert-scale measures validated through pilot studies.
  • Statistical analyses included OLS regression, RSA, PAM clustering, and thematic coding of qualitative responses.
• Limitations and future work:
  • Limited to writing professionals in North America; findings may not generalize to other professions or regions.
  • Relied on self-reported measures, which may introduce biases.
  • Future research should explore longitudinal designs, behavioral data, and broader global samples.

Summary

This study investigates how writing professionals' perceptions of rivalry and collaboration with GenAI shape their work practices and outcomes. Rivalry was associated with skill maintenance and relational crafting, while collaboration correlated with productivity, satisfaction, and task crafting. Combining high levels of rivalry and collaboration yielded the most balanced outcomes, enhancing both long-term skill development and short-term productivity. The findings suggest that intentional design strategies, such as introducing micro-frictions and fostering communities of practice, can help professionals maintain a balanced relationship with GenAI. Future research should validate these results across diverse professions and global contexts.