Knowledge Resource
Work, Wellbeing, and Choice: Empirical Lessons for AI Futures
- Author
- Aziz Shuaib Ausi
- Published
- 11 September 2026
- Reading time
- 1 min
- Publication type
- Knowledge Resource
- Availability
- Open access
Recent research in Computers and Society explores the evolving relationship between paid work and human wellbeing, particularly in the context of increasing AI-driven automation. The study aims to provide empirical grounding by surveying existing psychological, sociological, and economic literature on this topic. It investigates how wellbeing is influenced by work and how it is maintained among those who do not work, seeking to inform future economic transformations induced by AI.
Why it matters
This research is strategically important because it addresses fundamental questions about the future of work and human flourishing in an AI-augmented economy. Understanding the drivers of wellbeing beyond traditional employment is crucial for organizational and societal resilience, enabling proactive planning for workforce transitions and new models of value creation.
Key insights
- AI-driven automation raises questions about the necessity and availability of paid employment.
- Paid work is characterized as both a contributor to and an impediment to human wellbeing.
- The research seeks to understand the relationship between paid work and wellbeing from existing literature.
- It aims to identify factors influencing wellbeing among individuals who are not engaged in or do not require paid work.
- The findings are intended to inform potential AI-induced economic transformations.
Source
arXiv — Computers and Society — https://arxiv.org/abs/2609.11019
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Citation
Cite this publication (APA 7)
Aziz Shuaib Ausi (2026). Work, Wellbeing, and Choice: Empirical Lessons for AI Futures. Knowledge Resource. Aziz Shuaib Ausi. https://www.azizshuaib.com/verify/ASA-EXE-2026-00426
Verification
This is an authenticated institutional record.
- Verification ID
- ASA-EXE-2026-00426
- Version
- v1.0 · r0
- Issued
- 11 September 2026
- Publisher
- Aziz Shuaib Ausi
- Licence
- All rights reserved. Reproduction requires written permission.