mlsanityData to 14 Oct 2026

AI Safety Should Prioritize the Future of Work

arXiv 2504.13959 ↗First posted 16 Apr 2025cs.CY cs.AI cs.CLcited by 11

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

  1. 2023Jailbroken: How Does LLM Safety Training Fail?cited by 1,651
  2. 2023Fine-tuning Aligned Language Models Compromises Safety, Even When Users Do Not Intend To!cited by 1,154
  3. 2024The AI Scientist: Towards Fully Automated Open-Ended Scientific Discoverycited by 1,071
  4. 2023ChatGPT Outperforms Crowd-Workers for Text-Annotation Taskscited by 870
  5. 2022Out of One, Many: Using Language Models to Simulate Human Samplescited by 752
  6. 2023Extracting Training Data from Diffusion Modelscited by 732
  7. 2021Documenting Large Webtext Corpora: A Case Study on the Colossal Clean Crawled Corpuscited by 492
  8. 2024Can LLMs Generate Novel Research Ideas? A Large-Scale Human Study with 100+ NLP Researcherscited by 363
  9. 2024Alignment faking in large language modelscited by 360
  10. 2023The Impact of AI on Developer Productivity: Evidence from GitHub Copilotcited by 274
  11. 2024Spotting LLMs With Binoculars: Zero-Shot Detection of Machine-Generated Textcited by 263
  12. 2023Can Large Language Models Transform Computational Social Science?cited by 250
23 more
  1. 2023An Overview of Catastrophic AI Riskscited by 222
  2. 2023Does Writing with Language Models Reduce Content Diversity?cited by 192
  3. 2023GPTs are GPTs: An Early Look at the Labor Market Impact Potential of Large Language Modelscited by 176
  4. 2023Emergent autonomous scientific research capabilities of large language modelscited by 132
  5. 2024Language Models Learn to Mislead Humans via RLHFcited by 124
  6. 2023Foundation Models and Fair Usecited by 116
  7. 2021Algorithmic Monoculture and Social Welfarecited by 100
  8. 2024Watermark Stealing in Large Language Modelscited by 92
  9. 2023Robustness of AI-Image Detectors: Fundamental Limits and Practical Attackscited by 81
  10. 2024The AI Review Lottery: Widespread AI-Assisted Peer Reviews Boost Paper Scores and Acceptance Ratescited by 69
  11. 2025Gradual Disempowerment: Systemic Existential Risks from Incremental AI Developmentcited by 46
  12. 2025People who frequently use ChatGPT for writing tasks are accurate and robust detectors of AI-generated textcited by 40
  13. 2024Two Types of AI Existential Risk: Decisive and Accumulativecited by 22
  14. 2024An Economic Solution to Copyright Challenges of Generative AIcited by 18
  15. 2024AI Art is Theft: Labour, Extraction, and Exploitation, Or, On the Dangers of Stochastic Pollockscited by 13
  16. 2024ED-Copilot: Reduce Emergency Department Wait Time with Language Model Diagnostic Assistancecited by 9
  17. 2024Copying style, Extracting value: Illustrators' Perception of AI Style Transfer and its Impact on Creative Laborcited by 8
  18. 2024The Reality of AI and Bioriskcited by 8
  19. 2024Economic Policy Challenges for the Age of AIcited by 6
  20. 2023Artificial Intelligence Impact On The Labour Force -- Searching For The Analytical Skills Of The Future Software Engineerscited by 4
  21. 2025Examining Popular Arguments Against AI Existential Risk: A Philosophical Analysiscited by 4
  22. 2023Artificial Intelligence and Aesthetic Judgmentcited by 3
  23. 2024The Dual-Edged Sword of Technical Debt: Benefits and Issues Analyzed Through Developer Discussionscited by 1

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 3; 2026: 8.

11 papers.

Similar, not cited

Close in wording, no citation either way

  1. 2025Beyond Automation: Rethinking Work, Creativity, and Governance in the Age of Generative AI
  2. 2026Agentic AI and Occupational Displacement: A Multi-Regional Task Exposure Analysis of Emerging Labor Market Disruption
  3. 2025The AI Risk Spectrum: From Dangerous Capabilities to Existential Threats
  4. 2026Bounded by Risk, Not Capability: Quantifying AI Occupational Substitution Rates via a Tech-Risk Dual-Factor Model ↗
  5. 2026Human-Provenance Verification should be Treated as Labor Infrastructure in AI-Saturated Markets
  6. 2026The Human Utility Factor: A Computable Welfare Metric That Reframes AI Governance as a Constrained Optimisation Problem
  7. 2025Three Lenses on the AI Revolution: Risk, Transformation, Continuity
  8. 2026The Shadow Boss: Identifying Atomized Manipulations in Agentic Employment of XR Users using Scenario Constructions