Women Worry, Men Adopt: How Gendered Perceptions Shape the Use of Generative AI

2026-01-07

AI Summary

This study addresses the pronounced gender gap in generative artificial intelligence (GenAI) adoption, wherein women exhibit significantly lower usage rates than men. Leveraging nationally representative survey data from the UK collected between 2023 and 2024, the research constructs a novel composite index of perceived societal risks—encompassing mental health, privacy, climate, and employment impacts—and employs a synthetic twin panel design, interaction regression models, and intersectional analysis to identify the causal effect of risk perception on GenAI uptake. Findings reveal that risk perception is a key inhibiting factor for women’s GenAI use, accounting for 9%–18% of the observed gender disparity. Moreover, enhancing young women’s optimistic expectations regarding AI’s societal implications could increase their adoption rate from 13% to 33%, substantially narrowing the gender gap.

Technology Category

• Humans and AI: AI for Accessibility
• Application Domains: Humanities & Computational Social Science
• Philosophy and Ethics of AI: Bias, Fairness & Equity

Application Category

• Social Networks and Social Media: Generative AI / large language models and their impact on social systems
• Economics, Online Markets and Human Computation: Trust and reliance of crowd workers and data experts on GenAI
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web

Abstract

Generative artificial intelligence (GenAI) is diffusing rapidly, yet its adoption is strikingly unequal. Using nationally representative UK survey data from 2023 to 2024, we show that women adopt GenAI substantially less often than men because they perceive its societal risks differently. We construct a composite index capturing concerns about mental health, privacy, climate impact, and labor market disruption. This index explains between 9 and 18 percent of the variation in GenAI adoption and ranks among the strongest predictors for women across all age groups, surpassing digital literacy and education for young women. Intersectional analyses show that the largest disparities arise among younger, digitally fluent individuals with high societal risk concerns, where gender gaps in personal use exceed 45 percentage points. Using a synthetic twin panel design, we show that increased optimism about AI's societal impact raises GenAI use among young women from 13 percent to 33 percent, substantially narrowing the gender divide. These findings indicate that gendered perceptions of AI's social and ethical consequences, rather than access or capability, are the primary drivers of unequal GenAI adoption, with implications for productivity, skill formation, and economic inequality in an AI enabled economy.

Problem

• gender gap
• generative AI
• technology adoption
• societal risk perception
• digital inequality

Innovation

• gendered perceptions
• generative AI adoption
• societal risk index
• synthetic twin panel
• AI ethics