Supporting the Digital Autonomy of Elders Through LLM Assistance

TL;DR

The paper addresses the grey digital divide impacting elderly users and the need for safe, autonomous online navigation. It proposes SAGE, a multi-modal, in-browser LLM-based assistant designed to provide just-in-time, in-context support, risk identification, and fraud protection. Through a prompt-engineered prototype (SAGE 0.1) evaluated with GPT-4-Turbo and Claude-3-Opus, the study demonstrates both potential benefits and safety/interaction challenges across real-world tasks. The findings highlight a trade-off: GPT offers broader guidance but can be overwhelming, while Claude provides safer, more concise interactions; overall, the work motivates further development of an in-browser, multimodal SAGE to empower elderly digital autonomy while mitigating risk.

Abstract

The internet offers tremendous access to services, social connections, and needed products. However, to those without sufficient experience, engaging with businesses and friends across the internet can be daunting due to the ever present danger of scammers and thieves, to say nothing of the myriad of potential computer viruses. Like a forest rich with both edible and poisonous plants, those familiar with the norms inhabit it safely with ease while newcomers need a guide. However, reliance on a human digital guide can be taxing and often impractical. We propose and pilot a simple but unexplored idea: could an LLM provide the necessary support to help the elderly who are separated by the digital divide safely achieve digital autonomy?