# Will AI Agents Free Us From Meaningless Work? A Human-Centered Analysis

arXiv: https://arxiv.org/abs/2606.12430 · HTML: https://mlsanity.com/paper/2606.12430/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 3 of its 17 references that are in the map.
- First posted on arXiv 15 May 2026.

## Builds on (most cited first, 3 of 3)

- [Future of Work with AI Agents: Auditing Automation and Augmentation Potential across the U.S. Workforce](https://mlsanity.com/paper/2506.06576/) (2025)
- [The Potential Impact of AI Innovations on U.S. Occupations](https://mlsanity.com/paper/2312.04714/) (2023)
- [Are We Automating the Joy Out of Work? Designing AI to Augment Work, Not Meaning](https://mlsanity.com/paper/2603.14963/) (2026)

## Abstract (arXiv)

Some claim that AI agents will free workers from the boring parts of their jobs, yet little is known about how workers themselves identify which tasks should be automated. Prior research focuses on occupations, overlooking that workers experience varying levels of meaning across tasks within the same role. We address this gap with a task-level analysis grounded in Graeber's theory of bullshit jobs. Using ratings from 202 workers on 171 workplace tasks, we (1) validate a five-item scale of perceived bullshitness, (2) show that perceived bullshitness strongly predicts desire for AI delegation, and (3) find that such tasks are also seen as requiring less human oversight. Together, these findings suggest that tasks perceived as bullshit are natural candidates for AI delegation, aligning worker preferences with perceived feasibility.