--- title: "Workers’ perceptions of the economic impact of generative AI on sustainable economic development: evidence from ensemble tree models and explainable machine learning · AI Fault Line" url: https://aifaultline.com/research/p/doi-10-1007-s11135-026-02916-6/ description: "AI Fault Line is a neutral, evidence-cited field guide to why experts looking at the same developments disagree about AI's effect on productivity, jobs, inequality, regulation and the pace of change." --- [Research](https://aifaultline.com/research/) # Workers’ perceptions of the economic impact of generative AI on sustainable economic development: evidence from ensemble tree models and explainable machine learning Jorge Andrés-Sánchez, Teresa Torres-Coronas · Quality & Quantity · 18 Jun 2026 [Read original source](https://doi.org/10.1007/s11135-026-02916-6) Open access Where this sits in the debate - [Will AI actually boost productivity and growth?](https://aifaultline.com/debate/productivity/) Direction of the finding as read from the abstract by an AI model ([AI-written](https://aifaultline.com/about/)). ## Key takeaway [AI-written](https://aifaultline.com/about/) A survey study of workers in Spain that uses ensemble machine-learning models with SHAP explanations to identify what shapes perceptions of generative AI's contribution to sustainable economic development. Technological optimism, insecurity and habitual use matter most; women hold systematically less favorable views than men, and entrepreneurs slightly more favorable ones. ## Abstract Abstract Generative artificial intelligence (GenAI) is transforming society, including its economic foundations. This study examines the drivers and barriers shaping perceptions of GenAI’s influence on sustainable economic development (SED) among the working population. We adopt a conceptual framework in which these perceptions are shaped by four cognitive factors: three derived from the Technology Readiness and Acceptance Model, namely technological optimism, technological insecurity, and habitual use of GenAI, and a fourth related to the perceived need for regulation. The framework also incorporates three professional and sociodemographic characteristics: entrepreneurial status, gender, and membership in digital versus non-digital generations. Using a survey from Spain, we employ an analytical approach that combines ensemble tree–based machine learning models with Shapley Additive Explanations (SHAP) to enhance interpretability and explanatory insight. Among the evaluated models, XGBoost and Bayesian Additive Regression Trees achieve the strongest predictive performance. Random Forest exhibits comparatively weaker generalization performance. SHAP analyses consistently reveal that cognitive factors related to technology perceptions and habit in GenAI use play a central role in shaping evaluations of its contribution to sustainable economic development, whereas entrepreneurial status and generational cohort exert a secondary influence. Gender, however, shows greater explanatory relevance than perceptions regarding the need for regulation and reveals a pronounced gender gap in GenAI acceptance, with women exhibiting systematically less favorable perceptions than men. Although entrepreneurship exerts a relatively small effect, entrepreneurs tend to hold more favorable views regarding GenAI’s role in fostering sustainable economic development. Overall, the findings demonstrate that ensemble-based machine learning models, combined with SHAP, provide a powerful and trans ## About this publication **Academic journal.** Published in an academic journal — typically peer-reviewed before publication, though indexing alone doesn't guarantee review depth. Published 2026 (4 months ago) Citations 0 (OpenAlex) 0 citations recorded by OpenAlex — too few 2026 papers in this collection for a fair comparison. [Chart: published 2026] ## More on this topic Related by theme, not necessarily by method or conclusion. - [The Effects of Generative AI on High Skilled Work: Evidence from Three Field Experiments with Software Developers](https://aifaultline.com/research/p/doi-10-2139-ssrn-4945566/) SSRN · 2024 - [GPTs are GPTs: An Early Look at the Labor Market Impact Potential of Large Language Models](https://aifaultline.com/research/p/doi-10-48550-arxiv-2303-10130/) arXiv · 2023 - [Experimental evidence on the productivity effects of generative artificial intelligence](https://aifaultline.com/research/p/doi-10-1126-science-adh2586/) Science · 2023 - [The simple macroeconomics of AI](https://aifaultline.com/research/p/doi-10-1093-epolic-eiae042/) Economic Policy · 2024 Overview assembled automatically from collected metadata. [How this site is built](https://aifaultline.com/about/).