Live and recent posts from across the Fediverse tagged #labor-economics, aggregated by home.social.
New analysis: Global Debate on Labor Markets and AI — Entry-Level Pressure, Specialist Demand, and a Mixed Outlook
Key points:
• Entry-level roles facing more pressure from automation and AI tools
• Higher demand for specialized technical and domain expertise
• Short- to medium-term outcomes are mixed; policy and upskilling matter
Read the full article: https://wix.to/8tqUsRl
Older workers aren’t retiring. Should they be required to?
Married mothers do more housework than single mothers. Not a bug — a documented pattern. Why? Because a lot of husbands aren't helping. They're adding work. by @daylightatheism
https://onlys.ky/the-end-of-marriage/?utm_source=mastodon&utm_medium=social&utm_campaign=evergreen
#Feminism #Marriage #GenderEquality #LaborEconomics #Relationships
Panelist Spotlight: Ron Hetrick of Lightcast joins BroadbandLive TODAY: AI and Workforce – Combatting Job Displacement.
A leading labor economist with nearly 30 years of experience, Ron will share insights on AI, labor market trends, and preparing for the future of work.
The Livestream is at 12 ET today. Don't miss it.
#AI #FutureOfWork #LaborEconomics #tech #artificialIntelligence #technology
In 1961, a robot took a job no one wanted. The same robot would have been helpless in a kitchen. Danger isn't a property of an environment. It's a relationship between an environment and the body encountering it. New post on the ecology of work and what robots taught us about human fitness:
https://jameshoward.us/2026/05/29/the-ecology-of-work/
📈📉 Standard Error is delighted to announce that Sarah Winton (LSE ’26) has been awarded the Best Paper Prize at the 7th Workshop on the Economics and Politics of Migration. 🧵 1/9
stderr-editors.com/blog/best-pa...
#Migration #Refugees #LaborEconomics #DevelopmentEconomics
Standard Error awards Best Pap...
Fear and Loathing of AI (Part III): “Learn AI” Is the New “Learn to Code”
By Cliff Potts, CSO, and Editor-in-Chief of WPS News
There is a sentence that shows up in every technological cycle right before the disappointment phase begins.
“Just learn the skill.”
It sounds empowering. It sounds reasonable. It sounds like personal agency.
It is also a lie we have been telling people for decades.
The obedience script
“Learn to code” was never about opportunity.
It was about discipline.
It trained people to accept that:
When the promised jobs didn’t materialize—or paid far less than advertised—the story shifted seamlessly: you didn’t learn the right language, the right framework, the right stack.
Now the phrase has been updated.
“Learn AI.”
Same script. Same pressure. Same outcome.
Skills don’t collapse — markets do
Coding did not fail because people were lazy or incapable. It failed because markets flooded, tools commoditized, and labor lost leverage.
AI will follow the same arc, only faster.
The moment a skill becomes:
it stops being a path to security and becomes a baseline requirement for staying afloat.
The reward for compliance is not prosperity.
It is continued participation.
Training as cost transfer
Here is what “learn AI” really means in practice:
None of that is accidental.
It is a system designed to push costs downward while extracting value upward.
The more often you are told to retrain, the clearer it becomes that training itself is the product.
The illusion of agency
People are encouraged to believe that mastery equals control.
But control does not come from skill alone.
It comes from:
Without those, skill is just labor dressed up as self-improvement.
Learning AI may help you keep your job a little longer.
It will not protect you from the logic of the system deploying it.
What learning actually means now
This does not mean you should refuse to learn.
It means you should learn without illusions.
Learn AI the way you learn any tool:
Do not learn it expecting salvation.
Do not learn it expecting loyalty from platforms.
Do not learn it expecting the market to reward you for effort.
Markets reward leverage, not diligence.
The quiet truth
The most dangerous part of “learn AI” is not that it is false.
It is that it is incomplete.
It tells people how to adapt, but never who benefits.
It demands flexibility, but never offers stability.
It promises relevance, but never guarantees dignity.
We have seen this cycle before.
And it did not end with freedom.
It ended with exhaustion.
For more social commentary, please see Occupy 2.5 at https://Occupy25.com
#AISkills #ArtificialIntelligence #economicPrecarity #futureOfWork #laborEconomics #learnToCode #Occupy25 #platformCapitalism #technologyHype #workforceRetraining #WPSNews
https://www.europesays.com/2965570/ Gallup Analysis Finds AI Not Reducing Artists’ Earnings #CreativeIndustries #Data #Gallup #GenerativeAI #LaborEconomics #OccupationalExposureIndex
TVs get cheaper every year. So does fast fashion. But rent, healthcare, and college tuition keep climbing. Baumol explained this in 1966. We're still living it. by @daylightatheism.bsky.social
https://onlys.ky/cost-disease/
#Economics #CostOfLiving #Inequality #LaborEconomics #PublicPolicy
https://www.europesays.com/ie/361400/ Phenomenal Cosmic Power, Itty Bitty Labor Force? #AIAgents #ArtificialIntelligence #CareerDevelopment #CosmicPowers #DataScience #DisneyAladdin #Éire #IE #Ireland #Jafar #LaborEconomics #Technology #WageCompression #WallStreet
https://www.europesays.com/2776907/ The AI Jobs Non-Apocalypse: An Update | American Enterprise Institute #AI #ArtificialIntelligence #LaborEconomics #USEconomy
Turns Out They Didn’t Really Want You To Bring Your Whole Self To Work
Interesting angle, but letting your best people walk just to avoid paying them more seems like self-sabotage. Sure, you keep “solid” workers at standard wages, but isn’t that how you end up with mediocrity baked in?
#WorkCulture #HR #BusinessStrategy #LaborEconomics
Why top firms paradoxically fi...
Pluralistic: The enshittification of labor (07 Nov 2025)
https://web.brid.gy/r/https://pluralistic.net/2025/11/07/postwar-social-contract/
Things versus People: Gender Differences in Vocational Interests and in Occupational Preferences https://www.sciencedirect.com/science/article/pii/S0167268122003201
HT @SteveStuWill
"On average, men are more interested in working with things, whereas women are more interested in working with people.
…
Every push to get more women into things-related fields is simultaneously a push to get them out of equally important people-related fields such as healthcare and education - fields that, on average, they tend to prefer. We’re therefore faced with a decision: Should #GenderEquality mean identical outcomes, or identical freedom to follow one’s interests?"
#STEM #LaborEconomics #Psychology
AI-assisted Programming May Decrease the Productivity of Experienced Developers by Increasing Maintenance Burden https://arxiv.org/pdf/2510.10165
"… find that productivity indeed increases.
… the increase in productivity is driven by less-experienced (peripheral) developers.
… find that code written after the adoption of #AI requires more rework.
… the added rework burden falls on the more experienced (core) developers, who review 6.5% more code after Copilot's introduction, but show a 19% drop in their original code #productivity.
… this finding raises caution that productivity gains of AI may mask the growing burden of maintenance on a shrinking pool of experts."
#economics #LaborEconomics #skills
Thrilled to share my latest publication with coauthors Marianne Tønnessen and Astri Syse (open access) in Demography, October 2025. I thank the editor Sara Curran, and three anonymous reviewers, and #ReadDemography, and #PennPSC. https://read.dukeupress.edu/demography/article/doi/10.1215/00703370-12271149/403699/Goodbye-Norway-Top-Earners-Selection-Into-Return?fbclid=IwY2xjawNfgvtleHRuA2FlbQIxMQABHgkapuzYnl7R8qkJqdJofVHsHkPvm8I2VVzefb53l-ezAkYI_o64mtK7vNMf_aem_bc5nosvA7cc3zdoRsO4vuQ #Migration, #LaborEconomics, #PopulationEconomics, #norway
Mind the Gap: Gender-based Differences in Occupational Embeddings
https://aclanthology.org/2025.gebnlp-1.7.pdf
"Across five state-of-the-art multilingual models and seven reference-set configurations, up to 82% of gendered pairs received divergent Top-5 suggestions. These differences involved distinct occupational codes that sometimes crossed major #KldB group
.…gendered job titles—such as Autor vs. Autorin —often lead to different occupation codes, despite having identical meanings. Our findings underscore the importance of grounding #NLP innovations in language-specific sociolinguistic knowledge. Without rigorous attention to linguistic structure and social context, these tools risk perpetuating systemic biases—particularly in settings where semantic equivalence is masked by morphological variation. Addressing such challenges is crucial not only for the technical refinement of NLP systems, but for ensuring that their real-world applications advance rather than hinder equity"
#jobtech #gender #discrimination #LaborEconomics #llm
Measuring Gender Bias in Job Title Matching for Grammatical Gender Languages
https://www.arxiv.org/pdf/2509.13803
"… propose a methodology to measure gender bias in a high-impact #NLP application in the human resources domain: job title matching. Using an existing test set in English for this task, we have generated gender-annotated analogous corpora in four languages with grammatical gender, and addressed the evaluation of #genderBias as ranking comparison controlling for gender. Additionally, we establish baselines and confirm that this type of bias already exists in out-of-the-box pre-trained models, which are often used as the core for developing job title matching applications.
Finding a trade-off between model performance and #gender #bias is an important issue to address when developing and selecting job matching models for deployment. On the one hand, choosing a model with apparent good performance but that in turn shows a considerable gender gap may not only be ethically questionable, but it may also result in reputation and even legal consequences on the company responsible for it."
#llm #jobtech #discrimination #LaborEconomics
https://www.europesays.com/2401140/ AI’s Uncertain Cost Effects in Health Care | American Enterprise Institute #AI #ArtificialIntelligence #HealthCareCosts #HealthCarePolicy #LaborEconomics #MedicareAdvantage
Large Language Models, Small Labor Market Effects
https://bfi.uchicago.edu/wp-content/uploads/2025/04/BFI_WP_2025-56-2.pdf
"#AI chatbots have had no significant impact on earnings or recorded hours in any occupation, with confidence intervals ruling out effects larger than 1%. Modest productivity gains (average time savings of 3%), combined with weak wage pass-through, help explain these limited labor market effects.
… no evidence of differential trends over time, suggesting that the limited effects are not merely a very short-run phenomenon.
… findings challenge narratives of imminent labor market transformation due to Generative AI."
#llm #laborEconomics #wages
A recent study analyzing the Danish labor market (2023-2024) offers some insights into the early impact of generative AI. While AI chatbots have seen rapid adoption across various occupations, the study suggests their effects on overall wages and employment have been remarkably limited so far. 🌐
Key takeaways from the research:
📈 Despite widespread use, AI chatbots showed no significant impact on earnings or recorded hours.
🤔 While AI saves time for many users, the study found that new tasks created by AI (like reviewing AI output or crafting prompts) often offset these time savings for 8.4% of workers.
💸 Only a small fraction (3-7%) of productivity gains translated into higher earnings for workers, raising questions about who benefits most from efficiency.
This early look provides perspective, challenging some narratives around immediate, widespread labor market transformation. It highlights that the integration of AI is still evolving and its long-term economic impact remains a dynamic area for further research. What are your observations on AI's impact in your workplace?
https://arstechnica.com/ai/2025/05/time-saved-by-ai-offset-by-new-work-created-study-suggests/
#GenerativeAI #LaborEconomics #AIImpact #WorkplaceInnovation #FutureOfWork
New research shows that #inflation affects workers' #wellbeing beyond its impact on real #wages . As prices rise, #workers must fight for raises, creating #ConflictCosts that more than double inflation's effect on their well-being. #LaborEconomics #FutureOfWork
https://www.nber.org/papers/w32956
#CfP
How is #EUIntegration reshaping work in #SoutheasternEurope? We're looking for papers on #labor market reforms, skills & education, labor mobility and technology transfer for a special issue of our open access journal #COMPSEES.
🗓️ Deadline: July 1, 2024
➡️ https://leibniz-ios.de/en/knowledge-transfer/news/newsdetail/cfp-compsees-sonderausgabe
#Economics #LaborEconomics #Histodons #SocialScience #SocialSciences
Reputational Algorithm Aversion https://arxiv.org/pdf/2402.15418
"…rational humans may engage in “algorithm aversion” & override algorithms even if it is inefficient to do so. The intuition: they have to sometimes override algorithms in order to prove they are not replaceable
…problems: firms become slower to adopt algorithms, or forego using humans for a wider variety of tasks than would be necessary in the absence of reputational concerns"
#AI #LaborEconomics
Does gender of firm ownership matter? http://d.repec.org/n?u=RePEc:zbw:glodps:1422&r=lma
Gender pay gaps are 2 percentage points lower in female-owned firms
In male-dominated industries the #gpg is larger
In the service sector, female firm owners realize relative wages that reduce the #gpg partly fully to 0
While in small firms, female owners can reduce relatively low gender pay gaps by half, their influence on gender pay gaps in larger firms is limited
#wages #LaborEconomics