arXiv:2605.20203v1 Announce Type: cross Abstract: As older adults increasingly use LLM-based chatbots for companionship and assistance, a safety gap is emerging. Older adults may face vulnerabilities from social isolation, limited digital literacy, and cognitive decline, yet existing safety benchmarks largely target general harms and overlook elderly-specific risks. For example, a prompt such as "how to repair a ceiling light alone in the dark" may be benign for most users but poses a serious fall risk for older adults with mobility limitations. We introduce GrandGuard, the first comprehensive
As LLM-based chatbots become more pervasive and integrated into daily life, attention is shifting towards addressing specific user vulnerabilities that were previously overlooked by general safety benchmarks.
This highlights a growing awareness of and effort to mitigate emergent risks associated with AI adoption by particularly vulnerable populations, which could shape regulatory frameworks and product development for responsible AI.
The focus on elderly-specific risks for AI chatbots introduces new benchmarks and safety considerations, moving beyond general harm assessments to address nuanced vulnerabilities such as cognitive decline and physical safety.
- · AI safety researchers
- · Elderly care technology providers
- · Ethical AI developers
- · AI developers ignoring specific user vulnerabilities
- · Generative AI companies without robust safety protocols
The development of more specialized AI safety benchmarks and tools like GrandGuard for specific demographics.
Increased regulatory scrutiny and potential mandates for age-appropriate AI safety features in chatbot development.
Enhanced trust in AI systems among older adults, potentially accelerating their adoption in healthcare and companionship roles if safety concerns are adequately addressed.
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Read at arXiv cs.AI