Winners and losers of generative AI: Early Evidence of Shifts in Freelancer Demand
Open accessAbstract
We examine how ChatGPT has changed the demand for freelancers in jobs where generative AI tools can act as substitutes or complements to human labor. Using BERTopic we partition job postings from a leading online freelancing platform into 116 fine-grained skill clusters and with GPT-4o we classify them as substitutable, complementary or unaffected by LLMs . Our analysis reveals that labor demand increased after the launch of ChatGPT, but only in skill clusters that were complementary to or unaffected by the AI tool. In contrast, demand for substitutable skills, such as writing and translation, decreased by 20–50% relative to the counterfactual trend, with the sharpest decline observed for short-term (1-3 week) jobs. Within complementary skill clusters, the results are mixed: demand for machine learning programming grew by 24%, and demand for AI-powered chatbot development nearly tripled, while demand for novice workers declined in general. This result suggests a shift toward more specialized expertise for freelancers rather than uniform growth across all complementary areas.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
BERTopic outperforms LDA, co-word analysis, and STM in interpretability, scalability, and flexibility, and has recently demonstrated superior empirical performance.
“By contrast, BERTopic-leveraging deep semantic understanding, robustness to short texts, and a highly automated pipeline-outperforms LDA, co-word analysis, and STM in interpretability, scalability, and flexibility, and has recently demonstrated superior empirical performance (Tang et al., 2024;Teutloff et al., 2025).”
From Do Research Topics and Abstract Readability Affect Citation Impact in Leading Finance Journals? (2025) · cites this paper as Teutloff et al., 2025
Section 2.3 (p. 5) says BERTopic can capture semantic overlap that skill co-occurrence methods may miss, and that its cluster labels help interpret the results. The authors also found their clusters intuitively meaningful. The paper does not establish that BERTopic outperforms LDA, co-word analysis, and STM across interpretability, scalability, and flexibility, or demonstrate superior empirical performance against those methods. (LLM, conf=0.85)
Experimental — accuracy not yet measuredOver time, the uneven exposure of occupations to LLM and other emerging AI systems may contribute to labor market inequities and health disparities.
“Over time, the uneven exposure of occupations have to LLM and other emerging AI systems may contribute to labor market inequities and health disparities (18, 42).”
From Large language model exposure and precarious occupations: Unpacking relationships in the Canadian labor force (2026) · cites this paper as [42]
The discussion of findings (p. 3) says AI can create labor-market winners and losers depending on workers’ skills, supporting the claim of uneven labor-market effects. The conclusion (p. 17) says long-term effects remain to be studied. The passages do not address health disparities, so that part of the claim is unsupported by this source. (LLM, conf=0.86)
Experimental — accuracy not yet measuredEarly studies on online platforms for freelancers and vacancy postings find substantial negative effects of GenAI on employment and remuneration.
“Early studies on online platforms for freelancers and vacancy postings find substantial negative effects of GenAI on employment and remuneration (Hui, Reshef, & Zhou, 2024;Teeselink, 2025;Teutloff et al., 2025).”
From Labor Market Consequences of Generative AI: Early Evidence from Norway (2026) · cites this paper as Teutloff et al., 2025
Case studies point to notable effects on online labor platforms.
“case studies indicate notable effects on online labor market platforms”
From Still Waters, Rapid Currents: Early Labor Market Transformation under Generative AI (2025) · cites this paper as Teutloff et al., 2025
Teutloff et al. (2025) report that demand for substitutable freelance services such as writing and translation declined by 20-50% after ChatGPT.
“For example, Teutloff et al. (2025) report that demand for substitutable freelance services, such as writing and translation, declined by 20-50% after ChatGPT.”
From Still Waters, Rapid Currents: Early Labor Market Transformation under Generative AI (2025) · cites this paper as Teutloff et al. (2025)
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Glove: Global Vectors for Word Representation
Pennington, J., Socher, R., & Manning, C. (2014) · Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.3115/v1/d14-1162 · Cited by 34,071 · see citing works
Efficient Estimation of Word Representations in Vector Space
Mikolov, T., Chen, K., Corrado, G., & Dean, J. (2013) · arXiv · doi:10.48550/arxiv.1301.3781 · Cited by 26,568 · see citing works
Language Models are Few-Shot Learners
Brown, T. B., Mann, B., Ryder, N., Subbiah, M., Kaplan, J., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., et al. (2020) · arXiv · doi:10.48550/arxiv.2005.14165 · Cited by 23,372 · see citing works
The future of employment: How susceptible are jobs to computerisation?
Frey, C. B., & Osborne, M. A. (2017) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2016.08.019 · Cited by 8,727 · see citing works
UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction
McInnes, L., Healy, J., & Melville, J. (2018) · arXiv · doi:10.48550/arxiv.1802.03426 · Cited by 7,101 · see citing works
The second machine age: work, progress, and prosperity in a time of brilliant technologies
(2015) · Choice Reviews Online · doi:10.5860/choice.184834 · Cited by 4,401 · see citing works
Chain-of-Thought Prompting Elicits Reasoning in Large Language Models
Wei, J., Wang, X., Schuurmans, D., Bosma, M., Ichter, B., Xia, F., Chi, E., Le, Q., & Zhou, D. (2022) · arXiv · doi:10.48550/arxiv.2201.11903 · Cited by 4,263 · see citing works
Skills, Tasks and Technologies: Implications for Employment and Earnings
Acemoglu, D., & Autor, D. (2011) · Handbook of Labor Economics · doi:10.1016/s0169-7218(11)02410-5 · Cited by 3,799 · see citing works
Acemoglu, D., & Restrepo, P. (2018) · American Economic Review · doi:10.1257/aer.20160696 · Cited by 3,121 · see citing works
On the Surprising Behavior of Distance Metrics in High Dimensional Space
Aggarwal, C. C., Hinneburg, A., & Keim, D. A. (2001) · Lecture notes in computer science · doi:10.1007/3-540-44503-x_27 · Cited by 2,179 · see citing works
Experimental evidence on the productivity effects of generative artificial intelligence
Noy, S., & Zhang, W. (2023) · Science · doi:10.1126/science.adh2586 · Cited by 2,150 · see citing works
Text-Based Network Industries and Endogenous Product Differentiation
Hoberg, G., & Phillips, G. M. (2011) · Journal of Political Economy · doi:10.1086/688176 · Cited by 2,139 · see citing works
Dimensionality Reduction: A Comparative Review
van der Maaten, L., Postma, E. O., & van den Herik, H. J. (2009) · Cited by 2,066 · see citing works
The Nature of Technology: What it Is and How it Evolves
Arthur, W. B. (2009) · Cited by 2,043 · see citing works
BERTopic: Neural topic modeling with a class-based TF-IDF procedure
Grootendorst, M. (2022) · arXiv · doi:10.48550/arxiv.2203.05794 · Cited by 1,423 · see citing works
What can machine learning do? Workforce implications
Brynjolfsson, E., & Mitchell, T. (2017) · Science · doi:10.1126/science.aap8062 · Cited by 1,131 · see citing works
Brynjolfsson, E., Li, D., & Raymond, L. (2023) · National Bureau of Economic Research · doi:10.3386/w31161 · Cited by 995 · see citing works
Skill relatedness and firm diversification
Neffke, F. M. H., & Henning, M. (2012) · Strategic Management Journal · doi:10.1002/smj.2014 · Cited by 629 · see citing works
Online labour index: Measuring the online gig economy for policy and research
kässi, O., & Lehdonvirta, V. (2018) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2018.07.056 · Cited by 591 · see citing works
Self-citationAccelerated Hierarchical Density Based Clustering
McInnes, L., & Healy, J. (2017) · IEEE ... International Conference on Data Mining workshops · doi:10.1109/icdmw.2017.12 · Cited by 573 · see citing works
GPTs are GPTs: An Early Look at the Labor Market Impact Potential of Large Language Models
Eloundou, T., Manning, S., Mishkin, P., & Rock, D. (2023) · arXiv · doi:10.48550/arxiv.2303.10130 · Cited by 545 · see citing works
Self-citationThe Impact of Artificial Intelligence on the Labor Market
Webb, M. (2019) · SSRN Electronic Journal · doi:10.2139/ssrn.3482150 · Cited by 531 · see citing works
Is Automation Labor-Displacing? Productivity Growth, Employment, and the Labor Share
Autor, D., & Salomons, A. (2018) · National Bureau of Economic Research · doi:10.3386/w24871 · Cited by 429 · see citing works
Building a composite Help-Wanted Index
Barnichon, R. (2010) · Economics Letters · doi:10.1016/j.econlet.2010.08.029 · Cited by 403 · see citing works
The Establishment-Level Behavior of Vacancies and Hiring *
Davis, S. J., Faberman, R. J., & Haltiwanger, J. (2013) · The Quarterly Journal of Economics · doi:10.1093/qje/qjt002 · Cited by 370 · see citing works
The new paradigm of economic complexity
Balland, P., Broekel, T., Diodato, D., Giuliani, E., Hausmann, R., O’Clery, N., & Rigby, D. L. (2021) · Research Policy · doi:10.1016/j.respol.2021.104450 · Cited by 292 · see citing works
The Impact of AI on Developer Productivity: Evidence from GitHub Copilot
Peng, S., Kalliamvakou, E., Cihon, P., & Demirer, M. (2023) · arXiv · doi:10.48550/arxiv.2302.06590 · Cited by 287 · see citing works
New Frontiers: The Origins and Content of New Work, 1940–2018
Autor, D., Chin, C., Salomons, A., & Seegmiller, B. (2022) · The Quarterly Journal of Economics · doi:10.1093/qje/qjae008 · Cited by 277 · see citing works
A survey of density based clustering algorithms
Bhattacharjee, P., & Mitra, P. (2020) · Frontiers of Computer Science · doi:10.1007/s11704-019-9059-3 · Cited by 273 · see citing works
Hui, X., Reshef, O., & Zhou, L. (2024) · Social Science Research Network · doi:10.2139/ssrn.4527336 · Cited by 229 · see citing works
Monopsony in Online Labor Markets
Dubé, A., Jacobs, J., Naidu, S., & Suri, S. (2020) · American Economic Review Insights · doi:10.1257/aeri.20180150 · Cited by 226 · see citing works
2010 IEEE International Conference on Data Mining Workshops
(2010) · doi:10.1109/icdmw18178.2010 · Cited by 225 · see citing works
Opening the Black Box of the Matching Function: The Power of Words
Marinescu, I., & Wolthoff, R. (2016) · Journal of Labor Economics · doi:10.1086/705903 · Cited by 220 · see citing works
What is the price of a skill? The value of complementarity
Stephany, F., & Teutloff, O. (2024) · Research Policy · doi:10.1016/j.respol.2023.104898 · Cited by 199 · see citing works
Self-citationAsh, E., & Hansen, S. (2023) · Annual Review of Economics · doi:10.1146/annurev-economics-082222-074352 · Cited by 197 · see citing works
The Oxford Handbook of Skills and Training
Dalziel, P. (2017) · Oxford University Press eBooks · doi:10.1093/oxfordhb/9780199655366.001.0001 · Cited by 195 · see citing works
Online Labour Index 2020: New ways to measure the world’s remote freelancing market
Stephany, F., kässi, O., Rani, U., & Lehdonvirta, V. (2022) · UTUPub (University of Turku) · doi:10.1177/20539517211043240 · Cited by 189 · see citing works
Self-citationRandomization inference for difference-in-differences with few treated clusters
MacKinnon, J. G., & Webb, M. D. (2020) · Journal of Econometrics · doi:10.1016/j.jeconom.2020.04.024 · Cited by 182 · see citing works
Applying AI to Rebuild Middle Class Jobs
Autor, D. (2024) · doi:10.3386/w32140 · Cited by 157 · see citing works
Transforming boundaries: how does ChatGPT change knowledge work?
Ritala, P., Ruokonen, M., & Ramaul, L. (2023) · Journal of Business Strategy · doi:10.1108/jbs-05-2023-0094 · Cited by 101 · see citing works
Threatened by AI: Analyzing Users’ Responses to the Introduction of AI in a Crowd-Sourcing Platform
Lysyakov, M., & Viswanathan, S. (2022) · Information Systems Research · doi:10.1287/isre.2022.1184 · Cited by 97 · see citing works
Labor Economists Get Their Microscope: Big Data and Labor Market Analysis
Horton, J. J., & Tambe, P. B. (2015) · Big Data · doi:10.1089/big.2015.0017 · Cited by 92 · see citing works
The global polarisation of remote work
Braesemann, F., Stephany, F., Teutloff, O., kässi, O., Graham, M., & Lehdonvirta, V. (2022) · PLoS ONE · doi:10.1371/journal.pone.0274630 · Cited by 90 · see citing works
Self-citationManaging a ChatGPT-empowered workforce: Understanding its affordances and side effects
Retkowsky, J., Hafermalz, E., & Huysman, M. (2024) · Business Horizons · doi:10.1016/j.bushor.2024.04.009 · Cited by 90 · see citing works
Large language models reduce public knowledge sharing on online Q&A platforms
del Rio-Chanona, R. M., Laurentsyeva, N., & Wachs, J. (2024) · PNAS Nexus · doi:10.1093/pnasnexus/pgae400 · Cited by 87 · see citing works
Language Ranker: A Metric for Quantifying LLM Performance Across High and Low-Resource Languages
Li, Z., Shi, Y., Liu, Z., Yang, F., Payani, A., Liu, N., & Du, M. (2025) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v39i27.35038 · Cited by 86 · see citing works
Skill networks and measures of complex human capital
Anderson, K. A. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1706597114 · Cited by 74 · see citing works
Karjus, A. (2025) · Humanities and Social Sciences Communications · doi:10.1057/s41599-025-04503-w · Cited by 68 · see citing works
Empirical Confirmation of Creative Destruction from World Trade Data
Klimek, P., Hausmann, R., & Stefan Thurner, A. (2012) · PLoS ONE · doi:10.1371/journal.pone.0038924 · Cited by 66 · see citing works
Occupational mobility and automation: a data-driven network model
del Rio-Chanona, R. M., Mealy, P., Beguerisse-Díaz, M., Lafond, F., & Farmer, J. D. (2021) · Journal of The Royal Society Interface · doi:10.1098/rsif.2020.0898 · Cited by 64 · see citing works
Are Large Language Models a Threat to Digital Public Goods? Evidence from Activity on Stack Overflow
del Rio-Chanona, M., Laurentsyeva, N., & Wachs, J. (2023) · arXiv · doi:10.48550/arxiv.2307.07367 · Cited by 62 · see citing works
Skill Mismatch and the Costs of Job Displacement
Neffke, F. M. H., Nedelkoska, L., & Wiederhold, S. (2022) · Research Policy · doi:10.1016/j.respol.2023.104933 · Cited by 61 · see citing works
Market power and artificial intelligence work on online labour markets
Duch-Brown, N., Gomez-Herrera, E., Mueller-Langer, F., & Tolan, S. (2022) · Research Policy · doi:10.1016/j.respol.2021.104446 · Cited by 53 · see citing works
New technologies and jobs in Europe
Stefania Albanesi, Y., da Silva, A. D., Jimeno, J. F., Lamo, A., & Wabitsch, A. (2024) · Economic Policy · doi:10.1093/epolic/eiae058 · Cited by 51 · see citing works
AI Agents and Education: Simulated Practice at ScalePreprint
Mollick, E., Mollick, L., Bach, N., Ciccarelli, L., Przystanski, B., & Ravipinto, D. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.4871171 · Cited by 49 · see citing works
"Generate" the Future of Work through AI: Empirical Evidence from Online Labor MarketsPreprint
Liu, J., Xu, X.-C., Li, Y.-J., & Tan, Y. (2023) · Social Science Research Network · doi:10.2139/ssrn.4529739 · Cited by 33 · see citing works
Skill dependencies uncover nested human capital
Hosseinioun, M., Neffke, F. M. H., Zhang, L., & Youn, H. (2025) · Nature Human Behaviour · doi:10.1038/s41562-024-02093-2 · Cited by 30 · see citing works
den Bussche, J. V., & Vianu, V. (2001) · Springer eBooks · Cited by 21 · see citing works
Remote Work Across Jobs, Companies, and SpacePreprint
Hansen, S. E., Lambert, P., Bloom, N., Davis, S. J., Sadun, R., & Taska, B. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4377782 · Cited by 21 · see citing works
New Technologies and Jobs in Europe
Stefania Albanesi, Y., da Silva, A. D., Jimeno, J. F., Lamo, A., & Wabitsch, A. (2023) · National Bureau of Economic Research · doi:10.3386/w31357 · Cited by 21 · see citing works
What You Do at Work Matters: New Lenses on LabourPreprint
Mealy, P., del Rio-Chanona, R. M., & Farmer, J. D. (2018) · SSRN Electronic Journal · doi:10.2139/ssrn.3143064 · Cited by 17 · see citing works
Who Is AI Replacing? The Impact of Generative AI on Online Freelancing PlatformsPreprint
Demirci, O., Hannane, J., & Zhu, X. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4602944 · Cited by 17 · see citing works
Flexible Work Arrangements in Low Wage Jobs: Evidence from Job Vacancy DataPreprint
Adams‐Prassl, A., Balgová, M., & Qian, M. (2020) · SSRN Electronic Journal · doi:10.2139/ssrn.3695392 · Cited by 16 · see citing works
AI and Jobs: Has the Inflection Point Arrived? Evidence from an Online Labor PlatformPreprint
Qiao, D., Rui, H., & Xiong, Q. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4656716 · Cited by 13 · see citing works
What Is Expected of Higher Education Graduates in the Twenty-first Century?
Humburg, M., & van der Velden, R. (2017) · Oxford University Press eBooks · doi:10.1093/oxfordhb/9780199655366.013.10 · Cited by 10 · see citing works
del Rio-Chanona, R. M., Carrillo, A. H., Sepahpour‐Fard, M., Sun, L., Topinková, R., & Nedelkoska, L. (2023) · EPJ Data Science · doi:10.1140/epjds/s13688-023-00417-2 · Cited by 6 · see citing works
The Ruble Collapse in an Online Marketplace: Some Lessons for Market Designers
Horton, J. J. (2021) · National Bureau of Economic Research · doi:10.3386/w28702 · Cited by 6 · see citing works
Lukáč, M. (2021) · doi:10.31235/osf.io/m7ah4 · Cited by 5 · see citing works
GPT-4 vs. GPT-3.5 AS CODING ASSISTANTSPreprint
Moussiades, L., Zografos, G., & Papakostas, G. A. (2024) · Research Square · doi:10.21203/rs.3.rs-3920214/v1 · Cited by 4 · see citing works
The Ruble Collapse in an Online Marketplace: Some Lessons for Market DesignersPreprint
Horton, J. J. (2021) · SSRN Electronic Journal · doi:10.2139/ssrn.3834142 · Cited by 2 · see citing works
Skills, Job Application Behavior and the Gender Wage Gap: Evidence from Online FreelancingPreprint
Teutloff, O., Stenzhorn, E., & kässi, O. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4631160 · Cited by 1 · see citing works
Self-citationRemote Work across Jobs, Companies, and Space
Hansen, S., Lambert, P. J., Bloom, N., Davis, S., Sadun, R., & Taska, B. (2023) · doi:10.3386/w31007
Skill dependencies uncover nested human capital
Hosseinioun, M., Neffke, F., Zhang, L., & Youn, H. (2023) · arXiv · doi:10.48550/arxiv.2303.15629
Flagged first, then by citations
Research works printed but not linked: 3
- Arntz, M., Gregory, T., Zierahn, U., 2016. The Risk of Automation for Jobs in OECD Countries: A Comparative Analysis. oecd. http://refhub.elsevier.com/S0167-2681(2400459-1/sb7)
- Corporaal, G.F., Lehdonvirta, V., 2017. Platform Sourcing: How Fortune 500 Firms are Adopting Online Freelancing Platforms. University of Oxford. http://refhub.elsevier.com/S0167-2681(2400459-1/sb21)
- Farinha, T., et al., 2020. Impacts From Automation Diffuse Locally  e ''A Novel Approach To Estimate Jobs Risk In Us Cities. Technical Report, Utrecht University, Department of Human Geography and Spatial Planning .... http://refhub.elsevier.com/S0167-2681(2400459-1/sb30)
Cited by
Sorted by citations
Still Waters, Rapid Currents: Early Labor Market Transformation under Generative AI
Humlum, A., & Vestergaard, E. (2025) · doi:10.3386/w33777 · Cited by 34 · see citing works
Large Language Models, Small Labor Market Effects
Humlum, A., & Vestergaard, E. (2025) · doi:10.2139/ssrn.5219933 · Cited by 27 · see citing works
Costa, C., & Murphy, M. G. (2025) · Technology Pedagogy and Education · doi:10.1080/1475939x.2025.2547728 · Cited by 16 · see citing works
Assessing early labour market effects of generative AI: evidence from population data
Kauhanen, A., & Rouvinen, P. (2026) · Applied Economics Letters · doi:10.1080/13504851.2025.2513973 · Cited by 6 · see citing works
Reiter, L., BOHM, R. M., & Fuchs, C. (2025) · Computers in Human Behavior Reports · doi:10.1016/j.chbr.2025.100905 · Cited by 4 · see citing works
Mergenbayeva, A. T. (2026) · Bangladesh Journal of Multidisciplinary Scientific Research · doi:10.46281/bjmsr.v11i6.2958 · Cited by 3 · see citing works
Resilienz statt Reskilling: Wie KI den Arbeitsmarkt verändert und wie wir darauf reagieren müssen
Teutloff, O., & Braesemann, F. (2025) · Wirtschaftsdienst · doi:10.2478/wd-2025-0184 · Cited by 2 · see citing works
Self-citationGrant, Z., Green, J., & Evans, G. (2026) · Journal of European Public Policy · doi:10.1080/13501763.2026.2710714 · Cited by 2 · see citing works
Complex systems approaches to 21st century challenges: Introduction to the Special Issue
Bednar, J., del Rio-Chanona, R. M., Farmer, J. D., Kaszowska, J. A., Lafond, F., Mealy, P., Pangallo, M., & Pichler, A. (2025) · Journal of Economic Behavior & Organization · doi:10.1016/j.jebo.2025.107049 · Cited by 2 · see citing works
Beerepoot, N. (2026) · Globalizations · doi:10.1080/14747731.2025.2599681 · Cited by 1 · see citing works
Andraschko, L., & Weritz, P. (2026) · Electronic Markets · doi:10.1007/s12525-026-00894-z · Cited by 1 · see citing works
Digital gig workers vs. artificial intelligence – a battle of the wits
Kelly, S. N., Wisenthige, K., & Perera, L. (2026) · International Journal of Sociology and Social Policy · doi:10.1108/ijssp-02-2026-0192 · Cited by 1 · see citing works
Agnellini, F. (2025) · doi:10.64628/aai.hq7x5xseg · Cited by 1 · see citing works
Do Research Topics and Abstract Readability Affect Citation Impact in Leading Finance Journals?
Luo, Z., & Tse, Y. (2025) · Applied Finance Letters · doi:10.24135/afl.v14i.1059
“…deep semantic understanding, robustness to short texts, and a highly automated pipeline—outperforms LDA, co-word analysis, and STM in interpretability, scalability, and flexibility, and has recently demonstrated superior empirical performance (Tang et al., 2024; Teutloff et al., 2025).”
Jetha, A., Liao, Q., Smith, P., Vu, V., Biswas, A., Smith, B., & Vahid Shahidi, F. (2026) · Scandinavian Journal of Work, Environment & Health · doi:10.5271/sjweh.4312
“Over time, the uneven exposure of occupations have to LLM and other emerging AI systems may contribute to labor market inequities and health disparities ( 18, 42 ).”
Labor Market Consequences of Generative AI: Early Evidence from Norway
Facius, D., & Iacono, R. (2026) · CESifo Working Papers · doi:10.65864/8a4auliirt
Tekić, Ž., Omelchenko, Y., & Dunaeva, A. (2026) · Technology in Society · doi:10.1016/j.techsoc.2026.103464
GenAI, Growth, and the Multi-Sector MultipliersPreprint
Kuusi, T. (2025) · Research Square · doi:10.21203/rs.3.rs-7573536/v1
The innovation dynamics of programming technologies
Borchers, C., & Braesemann, F. (2025) · Journal of The Royal Society Interface · doi:10.1098/rsif.2025.0166
Self-citationBeyond automation and augmentation: reframing innovation policy for the work in the age of AI
Lee, J., & Lee, S. H. (2025) · Science and Public Policy · doi:10.1093/scipol/scaf078
Intelligent Acquisition and Retention: “The Future of Mentorship with AI”
Singh, M., Malviya, J. A., Patidar, P., Anjana, A., Nigam, N., & Bansal, C. (2026) · International Journal of Advancement and Innovation in Technology and Research · doi:10.63844/ijaitr.v3.i1.2026.302-307
Automation in the Wake of GenAI: Implications for Firm TrainingPreprint
Schilter, C., & Gschwendt, C. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.6617411
Overrated Judgment, Underrated Power: Gen AI at WorkPreprint
Moscato, D. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.6662078
Generative AI : Catalyst for Growth or Harbinger of Premature De‐Professionalization?
Liu, Y. (2026) · World Economy · doi:10.1111/twec.70109
The silent expansion: How does AI change labor market power?
Guo, G., Hu, Y., Wang, W., & Yan, Z. (2026) · International Review of Economics & Finance · doi:10.1016/j.iref.2026.105471
Kumar, M., Patouillard, L., Donaldson, A., Cornago, S., Bartocci, P., Tu, Q., Wachter, H. D., Hübner, N., Dumont, M., Coroamă, V. C., et al. (2026) · The International Journal of Life Cycle Assessment · doi:10.21203/rs.3.rs-9984806/v1
Upskilling with Generative AI: Practices and Challenges for Freelance Knowledge Workers
Imteyaz, K., Hurtado, I. L., Rajpal, N., Shin, H., & Savage, S. (2026) · Annual Symposium on Human-Computer Interaction for Work (CHIWORK) · doi:10.1145/3808045.3808068
The geography of artificial intelligence in European regions: innovation, exposure and use
Buarque, B. S., Casas, P., Fernández‐Macías, E., González-Vázquez, I., Hynes, R. M., Kogler, D. F., & Salotti, S. (2026) · Regional Studies · doi:10.1080/00343404.2026.2681659
Suarez-Rodríguez, C. H., Largo-Ávila, E., & Llano-Gallón, N. S. (2026) · Social Sciences & Humanities Open · doi:10.1016/j.ssaho.2026.103202 · Cited by 1 · see citing works
Creativity and AI skill demand in the post-ChatGPT labour market: evidence from UK job vacancies
Wang, Z., Baksy, A., Bakhshi, H., & Siepel, J. (2026) · Regional Studies · doi:10.1080/00343404.2026.2688960 · Cited by 1 · see citing works
Welfare State Deservingness in the Era of Mass Higher Education
Diessner, S., Durazzi, N., Filetti, F., Hope, D., Kleider, H., Limberg, J., & Tonelli, S. (2026) · Public Opinion Quarterly · doi:10.1093/poq/nfag056
Chapter 14: The Impact of Artificial Intelligence on Tax Law: Finland
Nissinen, M. (2026) · WU Institute for Austrian and International Tax Law, tax law and policy series. · doi:10.59403/1gs8pg9014
Can the fourth industrial revolution solve the productivity problem?
Tholen, G., & Westwood, A. F. (2026) · The Economic and Labour Relations Review · doi:10.1017/elr.2026.10077
Worker Repositioning and Technological Change: Evidence from an Online Labor Market
Yiu, S., Seamans, R., Raj, M., & Liu, T. (2026) · Organization Science · doi:10.1287/orsc.2025.20566
Bridging the gap between vocational AI curricula and industry skill demand: Evidence from China
Xiao, H., Lee, H. L., Zheng, K., Kuang, Z., Oung, Q. W., & Zhang, Q. (2026) · Industry and Higher Education · doi:10.1177/09504222261478197
Aponte-López, A. C. (2026) · Región Científica · doi:10.58763/rc2026589
Zhao, L., Zhang, B., Du, X., Xu, W., Zhang, Y., & Li, X. (2026) · International Conference on Machine Learning and Neural Networks · doi:10.1145/3821725.3821766
何郁達, Maideen, M. B. H., Sun, C., & Guo, Z. (2026) · Labor History · doi:10.1080/0023656x.2026.2733500
Liu, J., Zhong, C., Meng, F., Shank, D. B., & Wunsch, D. C. (2026) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2026.103140
Occupational exposure to generative AI and worker wages in Korea
Lee, S., & Kim, S. (2026) · Applied Economics Letters · doi:10.1080/13504851.2026.2744548
Huang, H., Mbanyele, W., & Muchenje, L. T. (2026) · Journal of Multinational Financial Management · doi:10.1016/j.mulfin.2026.100981
- Authors
- Teutloff, O., Einsiedler, J., Kässi, O., Braesemann, F., Mishkin, P., & del Rio-Chanona, R. M.
- Affiliations
- University of Copenhagen (DK)
- University of Oxford (GB)
- Venue
- Journal of Economic Behavior & Organization
- Publisher
- Elsevier BV
- Published
- 2025-07
- Volume
- 235
- Pages
- 106845
- ISSN
- 0167-2681 (ISSN-L)
- OpenAlex
- W4406893601
- Cited by
- 39
- References
- 69
- Citations by year
- 2026: 28 · 2025: 11
- FWCI
- 67.46
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Journal of Economic Behavior & Organization (publishedVersion, cc-by)
- Research at the University of Copenhagen (University of Copenhagen) (publishedVersion, cc-by)
- UCL Discovery (University College London) (submittedVersion, cc-by)
- Funders
- James S McDonnell Foundation
- Topics
- Social Sciences › Sociology and Political Science › Digital Economy and Work Transformation
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Labor market dynamics and wage inequality
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Keywords
- generative AI, ChatGPT, freelancers, labor demand, skill complementarity, skill substitution, job advertisements, freelancing platforms, chatbot development, novice workers
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
