Improving Survey Participation in Low-Literacy Populations Through Value-Sensitive Conversational AI
arXiv:2606.30660v1 Announce Type: cross Abstract: Collecting reliable social data from low-literacy populations remains a persistent challenge, particularly when surveys involve sensitive topics and marginalized communities. Traditional paper-based and web-based survey modalities often suffer from high attrition and incomplete responses due to literacy barriers, social pressure, and interactional discomfort. In this paper, we present findings from an initial field evaluation comparing multiple survey modalities paper-based interviews, digital web-based surveys, conversational AI (convAI) surve
The proliferation of advanced conversational AI capabilities makes such applications feasible, combined with increasing demand for inclusive data collection methods from marginalized communities.
This research highlights AI's potential to bridge social data gaps, improve research equity, and provide insights into populations previously difficult to reach, influencing policy and resource allocation.
Survey methodologies can now directly leverage conversational AI to overcome literacy and cultural barriers, transforming how social data is collected and validated in diverse populations.
- · Social researchers
- · Non-governmental organizations (NGOs)
- · Marginalized communities
- · Conversational AI developers
- · Traditional paper survey companies
- · Digital web-based survey platforms (without AI integration)
More accurate and representative social data becomes available for policy-making and humanitarian efforts.
Increased trust and participation from low-literacy populations in data collection leads to better-informed interventions and reduced social inequality.
The success of conversational AI in sensitive data collection could accelerate its adoption in other public service and healthcare interfaces, decentralizing access to information and services.
This signal links to a primary source. Continuum Brief monitors and indexes it as part of the live intelligence stream — we do not republish source content.
Read at arXiv cs.AI