Social sciences as tools for predicting societal impacts of AI on education and work

Abstract

This study investigated the intersection of Artificial Intelligence, education, workforce preparation, and the social sciences in mitigating societal risks in AI adoption. A mixed-method descriptive survey design was employed across three Colleges of Education in Ilorin, Lafiagi, and Oro. A total of 288 usable responses were analyzed through descriptive and inferential statistics alongside qualitative evidence. Findings revealed that AI adoption significantly improves learning outcomes, access, and educational equity; the majority of respondents attested to notable effects. Results further showed that AI-driven automation is reshaping employment structures and altering skills demand, with respondents indicating significant changes in workforce competencies. Additionally, respondents emphasized the importance of social sciences particularly sociology, psychology, and economics in anticipating and mitigating the social risks of AI adoption. The study concludes that AI adoption is a socio-technical process shaped by infrastructure, access, policy contexts, and human behaviour. It recommends enhancing equitable access to AI learning tools, strengthening teacher training, promoting digital literacy, and developing localized content, alongside continuous reskilling and stronger collaboration between academia, industry, and policymakers. Integrating social science expertise in AI governance and investing in digital infrastructure will ensure sustainable and equitable AI adoption in education and society.