AI Literacy Education for Older Adults: Motivations, Challenges and Preferences

2025-04-20

AI Summary

Addressing the critical gap in empirical research on AI literacy education for older adults, this study conducts a mixed-methods needs assessment (N=103) with participants aged 50+, integrating surveys, descriptive statistics, and thematic analysis. Grounded in human–computer interaction and gerontological education theories, it develops a comprehensive needs model. The study provides the first empirical evidence of older adults’ dual motivational drivers—gain-oriented (e.g., enhanced autonomy) and loss-avoidant (e.g., mitigating exclusion)—alongside a pronounced preference for practice-oriented learning. It identifies three primary barriers: abstract AI concepts, ambiguous entry points, and low self-efficacy; and four key design opportunities: everyday-life exemplars, scaffolded task progression, intergenerational co-learning, and trustworthy guidance. Based on these findings, the paper proposes an age-inclusive AI literacy framework characterized by scenario-based instruction, low-threshold engagement, and embodied interaction—filling a foundational gap in empirical aging-and-AI research and offering both theoretical grounding and actionable design principles for developing accessible AI education tools.

Technology Category

• Humans and AI: AI for Accessibility
• Philosophy and Ethics of AI: Privacy & Security
• Multiagent Systems: Agent/AI Theories and Architectures

Application Category

• Economics, Online Markets and Human Computation: Research challenges in human and human-AI computation
• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• User Modeling, Personalization and Recommendation: Practical large-scale studies of user experience

Abstract

As Artificial Intelligence (AI) becomes increasingly integrated into older adults' daily lives, equipping them with the knowledge and skills to understand and use AI is crucial. However, most research on AI literacy education has focused on students and children, leaving a gap in understanding the unique needs of older adults when learning about AI. To address this, we surveyed 103 older adults aged 50 and above (Mean = 64, SD = 7). Results revealed that they found it important and were motivated to learn about AI because they wish to harness the benefits and avoid the dangers of AI, seeing it as necessary to cope in the future. However, they expressed learning challenges such as difficulties in understanding and not knowing how to start learning AI. Particularly, a strong preference for hands-on learning was indicated. We discussed design opportunities to support AI literacy education for older adults.

Problem

• Addressing AI literacy gap in older adults' education
• Identifying motivations and challenges in AI learning for seniors
• Exploring hands-on learning preferences for elderly AI education

Innovation

• Surveyed older adults for AI literacy insights
• Highlighted hands-on learning preference
• Addressed unique AI education challenges