# The New Social Image: How AI Competency and AI Proactivity Influence Self- and Peer-Perceptions in the Workplace

arXiv: https://arxiv.org/abs/2606.00182 · HTML: https://mlsanity.com/paper/2606.00182/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 13 of its 140 references that are in the map.
- First posted on arXiv 29 May 2026.

## Builds on (most cited first, 13 of 13)

- [Hybrid Intelligence](https://mlsanity.com/paper/2105.00691/) (2021)
- [Cooperating with Machines](https://mlsanity.com/paper/1703.06207/) (2017)
- [The future of human-AI collaboration: a taxonomy of design knowledge for hybrid intelligence systems](https://mlsanity.com/paper/2105.03354/) (2021)
- [GazePointAR: A Context-Aware Multimodal Voice Assistant for Pronoun Disambiguation in Wearable Augmented Reality](https://mlsanity.com/paper/2404.08213/) (2024)
- [Human-AI Collaboration: The Effect of AI Delegation on Human Task Performance and Task Satisfaction](https://mlsanity.com/paper/2303.09224/) (2023)
- [How Do Data Analysts Respond to AI Assistance? A Wizard-of-Oz Study](https://mlsanity.com/paper/2309.10108/) (2023)
- [Designing for human-AI complementarity in K-12 education](https://mlsanity.com/paper/2104.01266/) (2021)
- ["If the Machine Is As Good As Me, Then What Use Am I?" -- How the Use of ChatGPT Changes Young Professionals' Perception of Productivity and Accomplishment](https://mlsanity.com/paper/2404.12549/) (2024)
- [Exploring the Impact of AI Value Alignment in Collaborative Ideation: Effects on Perception, Ownership, and Output](https://mlsanity.com/paper/2402.12814/) (2024)
- [Comparing Zealous and Restrained AI Recommendations in a Real-World Human-AI Collaboration Task](https://mlsanity.com/paper/2410.11860/) (2024)
- [When Teams Embrace AI: Human Collaboration Strategies in Generative Prompting in a Creative Design Task](https://mlsanity.com/paper/2509.21731/) (2025)
- [Intelligent Notification Systems: A Survey of the State of the Art and Research Challenges](https://mlsanity.com/paper/1711.10171/) (2017)
- [Positive Work Practices. Opportunities and Challenges in Designing Meaningful Work-related Technology](https://mlsanity.com/paper/2003.05533/) (2020)

## Abstract (arXiv)

Human-AI collaboration is considered the most promising way to incorporate AI in the workplace. What remains unexplored are the experiential consequences of this teaming. More specifically, in a team with AI, how humans perceive themselves (self-perception) and how they are perceived by their coworkers (peer perception) in terms of work ownership and job meaningfulness. In a 2x2x2 vignette study (n=50), participants rated perceptions of ownership, affect, job meaningfulness and satisfaction, and role dynamics across two levels (low/high) of AI proactivity and AI competency as within-subject factors, with point-of-view (self perception/peer perception) as between-subjects. Our results showed that AI with low competency or low proactivity generally improved feelings related to ownership, meaningfulness, satisfaction, and role dynamics, and also increased positive affect while reducing negative affect. However, these effects were often influenced by point-of-view. For instance, low AI proactivity resulted in higher job satisfaction from self-perception rather than peer perception. Based on our findings, we argue that designing AI for the future of work solely around performance metrics may not be adequate. Highly competent and proactive AI-driven systems can have undesirable impacts on perceptions of ownership, job identity, social image and team dynamics, and consequently, job meaningfulness.