Responsible Integration of AI-Enabled Service Robots in Healthcare and Eldercare

A Sociotechnical and Ethical Governance Framework

Yuehan Zhang

December 8 2025

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Research Proposal

Research proposal in fulfillment of requirements of the NYU SPS course

Research Process and Methods

Fall 2025

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Research Topic And Question

• Research Topic

Responsible integration of AI-enabled service robots in healthcare and eldercare

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• What I intend to discover

Ethical design, governance, training

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trust, care quality, acceptance

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• Framed Research Question

How can robots augment—not replace—human care responsibly?

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Why is this important?

• Aging populations → Rising long-term care demand → Workforce shortages in healthcare and eldercare
• Robot adoption raises ethical and governance concerns

• Tech + Ethics + Governance + Labor
• Identifies conditions where robots augment not replace
• Cross-national insights for responsible adoption

Why this topic matters

New knowledge this research brings

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Literature review

Ethical & Governance Foundations

Stahl & Coeckelbergh (2016)

Responsible Research & Innovation (RRI)�Multi-level responsibility in healthcare robotics

Social Acceptance & User Perception

Kodate et al. (2022)

Attitudes of older adults & caregivers�Trust, privacy, cultural expectations

Labor Dynamics & Human–Robot Collaboration

Taniguchi et al. (2025)

Reduced physical burden�New skills, reshaped roles

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Theoretical Basis and Model

• Sociotechnical Systems Theory (STS)
• Responsible Research & Innovation (RRI)
• Human-centered care & ethical design principles

Theoretical Basis

Model Used

• Mixed-Methods Design
• Hypothesis Model: �Design → Governance → Workforce Training
• Mechanisms Shaping �Trust & Perceived Care Quality

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Hypothesis

• H1 – Ethical Design & Transparency → Trust & Quality�Higher ethical design boosts trust and perceived care quality.
• H2 – Governance & Policy Support → Adoption & Integration�Stronger governance improves adoption and institutional integration.
• H3 – Care-Robot Literacy (Moderator)�Training strengthens the effect of ethical design on perceived care quality.

Hypotheses

Independent Variables (IVs)

• Ethical design & transparency
• Governance & policy support
• Care-robot literacy programs

Mediator

• Trust in robot-assisted care

Dependent Variables (DVs)

• Quality and acceptance of robot-assisted care

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Research Design

Research Type

• Mixed-methods (Explanatory Sequential Design)

Phase 1: Quantitative

• Online survey measuring ethical design, governance support, literacy, trust, and care outcomes.

Phase 2: Qualitative

• Semi-structured interviews to contextualize quantitative findings across cultural and institutional settings.

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Data Collection

• Online survey using 5-point Likert scales
• Semi-structured interviews
• Institutional and policy document review

• Caregivers & healthcare workers
• Eldercare administrators & managers
• Adult children of older adults

Methods of Data Collection

Data Sources

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Data Analysis

• Descriptive statistics
• Correlation analysis
• Multiple regression (hypothesis testing)
• Mediation & moderation tests
• Institutional / demographic controls

• Thematic coding
• Cross-case comparison
• Contextual explanation of quantitative results

Quantitative Analysis

Qualitative Analysis

• Use qualitative findings to explain quantitative patterns
• Merge results to validate or refine hypotheses

Mixed-Methods Integration

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Results Expected

• Ethical design → Higher trust & perceived quality
• Governance support → Stronger adoption & legitimacy
• Training / Robot literacy → Workforce readiness
• Robots augment (not replace) human caregiving
• Cultural alignment → Safety perception

How Results Will Be Used

• Ethical & governance guidance
• Workforce training support
• Culturally sensitive design & policy

Conclusions �and Recommendations

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• M.S. Graduate Student, Management and Systems, NYU
• Senior Product Manager(AI, Gaming, E-Commerce)
• New York University, School of Professional Studies

https://www.linkedin.com/in/zhangyuehan/

yz11529@nyu.edu

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