The Speculative Future of Conversational AI for Neurocognitive Disorder Screening: a Multi-Stakeholder Perspective

2026-04-10

AI Summary

Current screening methods for neurocognitive disorders lack scalability, while conversational AI faces persistent challenges in social acceptance, user engagement, and clinical facilitation. This study addresses these gaps by conducting interviews with 36 clinicians, at-risk individuals, and caregivers to systematically integrate multi-stakeholder perspectives on the perceptions, expectations, and tensions surrounding conversational AI–based screening. Through qualitative analysis and user journey mapping grounded in a human-centered design framework, the research reveals that deploying conversational AI in home and community settings can effectively reduce social stress during cognitive assessments. It further identifies a critical tension between users’ needs for empathetic support and the demand for clinical standardization. These findings offer innovative, practice-oriented guidance for the feasible implementation and system design of conversational AI in early neurocognitive disorder screening.

Technology Category

• Humans and AI: Intelligent User Interfaces
• Cognitive Modeling & Cognitive Systems: Social Cognition And Interaction
• Data Mining & Knowledge Management: Conversational Systems for Recommendation & Retrieval

Application Category

• Search and Retrieval-Augmented AI: Assisted, interactive, and conversational search
• Economics, Online Markets and Human Computation: Trust and reliance of crowd workers and data experts on GenAI
• User Modeling, Personalization and Recommendation: Fairness-aware retrieval and ranking

Abstract

Neurocognitive disorders (NCDs), such as Alzheimer's disease, are globally prevalent and require scalable screening methods for proactive management. Prior research has explored the potential of technologies like conversational AI (CAI) to administer NCD screening tests. However, challenges remain in designing CAI-based solutions that make routine NCD screening socially acceptable, engaging, and capable of encouraging early medical consultation. In this study, we conducted interviews with 36 participants, including clinicians, individuals at risk of NCDs, and their caregivers, to explore the speculative future of adopting CAI for NCD screening. Our findings reveal shared expectations, such as deploying CAI in home or community settings to reduce social stress. Nonetheless, conflicts emerged among stakeholders, for example, users'need for emotional support may conflict with clinicians'preference for CAI's professional and standardized administration. Then, we look into the user journey of NCD screening based on the current practice of manual screening and the expected CAI-supported screening. Finally, leveraging the human-centered approach, we provide actionable implications for future CAI design in NCD screening.

Problem

• conversational AI
• neurocognitive disorder screening
• social acceptability
• early medical consultation
• user engagement

Innovation

• conversational AI
• neurocognitive disorder screening
• multi-stakeholder perspective
• human-centered design
• speculative design