AI Safety Should Prioritize the Future of Work
Not on the map. Why?
Abstract (arXiv)
Current efforts in AI safety prioritize filtering harmful content, preventing manipulation of human behavior, and eliminating existential risks in cybersecurity or biosecurity. While pressing, this narrow focus overlooks critical human-centric considerations that shape the long-term trajectory of a society. In this position paper, we identify the risks of overlooking the impact of AI on the future of work and recommend comprehensive transition support towards the evolution of meaningful labor with human agency. Through the lens of economic theories, we highlight the intertemporal impacts of AI on human livelihood and the structural changes in labor markets that exacerbate income inequality. Additionally, the closed-source approach of major stakeholders in AI development resembles rent-seeking behavior through exploiting resources, breeding mediocrity in creative labor, and monopolizing innovation. To address this, we argue in favor of a robust international copyright anatomy supported by implementing collective licensing that ensures fair compensation mechanisms for using data to train AI models. We strongly recommend a pro-worker framework of global AI governance to enhance shared prosperity and economic justice while reducing technical debt.
Key facts. Cited by 11 papers in the map (data through 14 Oct 2026). Builds on 35 of its 116 references that are in the map. First posted on arXiv 16 Apr 2025.
Builds on
35 of 116 references.
References · 35
- 2023Jailbroken: How Does LLM Safety Training Fail?cited by 1,651
- 2023Fine-tuning Aligned Language Models Compromises Safety, Even When Users Do Not Intend To!cited by 1,154
- 2024The AI Scientist: Towards Fully Automated Open-Ended Scientific Discoverycited by 1,071
- 2023ChatGPT Outperforms Crowd-Workers for Text-Annotation Taskscited by 870
- 2022Out of One, Many: Using Language Models to Simulate Human Samplescited by 752
- 2023Extracting Training Data from Diffusion Modelscited by 732
- 2021Documenting Large Webtext Corpora: A Case Study on the Colossal Clean Crawled Corpuscited by 492
- 2024Can LLMs Generate Novel Research Ideas? A Large-Scale Human Study with 100+ NLP Researcherscited by 363
- 2024Alignment faking in large language modelscited by 360
- 2023The Impact of AI on Developer Productivity: Evidence from GitHub Copilotcited by 274
- 2024Spotting LLMs With Binoculars: Zero-Shot Detection of Machine-Generated Textcited by 263
- 2023Can Large Language Models Transform Computational Social Science?cited by 250
23 more
- 2023An Overview of Catastrophic AI Riskscited by 222
- 2023Does Writing with Language Models Reduce Content Diversity?cited by 192
- 2023GPTs are GPTs: An Early Look at the Labor Market Impact Potential of Large Language Modelscited by 176
- 2023Emergent autonomous scientific research capabilities of large language modelscited by 132
- 2024Language Models Learn to Mislead Humans via RLHFcited by 124
- 2023Foundation Models and Fair Usecited by 116
- 2021Algorithmic Monoculture and Social Welfarecited by 100
- 2024Watermark Stealing in Large Language Modelscited by 92
- 2023Robustness of AI-Image Detectors: Fundamental Limits and Practical Attackscited by 81
- 2024The AI Review Lottery: Widespread AI-Assisted Peer Reviews Boost Paper Scores and Acceptance Ratescited by 69
- 2025Gradual Disempowerment: Systemic Existential Risks from Incremental AI Developmentcited by 46
- 2025People who frequently use ChatGPT for writing tasks are accurate and robust detectors of AI-generated textcited by 40
- 2024Two Types of AI Existential Risk: Decisive and Accumulativecited by 22
- 2024An Economic Solution to Copyright Challenges of Generative AIcited by 18
- 2024AI Art is Theft: Labour, Extraction, and Exploitation, Or, On the Dangers of Stochastic Pollockscited by 13
- 2024ED-Copilot: Reduce Emergency Department Wait Time with Language Model Diagnostic Assistancecited by 9
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- 2024The Reality of AI and Bioriskcited by 8
- 2024Economic Policy Challenges for the Age of AIcited by 6
- 2023Artificial Intelligence Impact On The Labour Force -- Searching For The Analytical Skills Of The Future Software Engineerscited by 4
- 2025Examining Popular Arguments Against AI Existential Risk: A Philosophical Analysiscited by 4
- 2023Artificial Intelligence and Aesthetic Judgmentcited by 3
- 2024The Dual-Edged Sword of Technical Debt: Benefits and Issues Analyzed Through Developer Discussionscited by 1
Built on by
Citing papers per year: 2025: 3; 2026: 8.
11 papers.
- 2025Future of Work with AI Agents: Auditing Automation and Augmentation Potential across the U.S. Workforcecited by 38
- 2026MLReplicate: Benchmarking Autonomous Research Systems for Machine Learning Reproducibilitycited by 8
- 2025Accepted with Minor Revisions: Value of AI-Assisted Scientific Writingcited by 1
- 2026CollabSkill: Evaluating Human-Agent Collaboration On Real-World Taskscited by 1
- 2025Idempotent Equilibrium Analysis of Hybrid Workflow Allocation: A Mathematical Schema for Future Workcited by 0
- 2026A paradox of AI fluencycited by 0
- 2026Generative Models Erode Human Temporal Learning Through Market Selectioncited by 0
- 2026Position: Preventing AI-Generated CSAM Necessitates New Approaches to AI Safetycited by 0
- 2026Position: AI/ML Deepfake Research is Misaligned with AI-Generated Non-Consensual Intimate Imagery (AIG-NCII)cited by 0
- 2026Position: AI Lock-In Is in Progress, and We Must Be Preparedcited by 0
- 2026An Investigation of the NeurIPS and ICML 2025 Position Trackscited by 0
- 2026An Investigation of the NeurIPS and ICML 2025 Position Tracks6 Jul 2026
- 2026Position: Preventing AI-Generated CSAM Necessitates New Approaches to AI Safety9 Jun 2026
- 2026Generative Models Erode Human Temporal Learning Through Market Selection4 Jun 2026
- 2026Position: AI Lock-In Is in Progress, and We Must Be Prepared28 May 2026
- 2026Position: AI/ML Deepfake Research is Misaligned with AI-Generated Non-Consensual Intimate Imagery (AIG-NCII)16 May 2026
- 2026MLReplicate: Benchmarking Autonomous Research Systems for Machine Learning Reproducibility15 May 2026
- 2026A paradox of AI fluency28 Apr 2026
- 2026CollabSkill: Evaluating Human-Agent Collaboration On Real-World Tasks20 Apr 2026
- 2025Accepted with Minor Revisions: Value of AI-Assisted Scientific Writing16 Nov 2025
- 2025Idempotent Equilibrium Analysis of Hybrid Workflow Allocation: A Mathematical Schema for Future Work2 Aug 2025
- 2025Future of Work with AI Agents: Auditing Automation and Augmentation Potential across the U.S. Workforce6 Jun 2025
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