Frontier Systems Technical Paper
Company-Led Technical Preprint / Technical Disclosure Version
Version 1.0 | 2026
RR-Ethics™: A Human-Centred Ethical Readiness Index for Responsible Deployment of Embodied AI Humanoid Eldercare Robotics
A Systems-Oriented HERI Framework for Legal Accountability, Safety Boundaries, Public Health Protection and Institutional Deployment Governance
Xin Zhao¹†, Weijie Tan¹†, Tian Shen¹†, Wentao Zhao¹, Qiang Huang¹, Hon Hsiang Ong¹, Wenqun Guo¹, Tingting Shen², Chunqiu Yan², and Jian Zhang¹,*
¹ AJJ Healthcare Management Pte. Ltd., Singapore.
² Hangzhou Huaxi Intelligent Technology Co. Ltd., Hangzhou, China.
† These authors contributed equally to this work and share first authorship.
* Correspondence: zhangjian@ajjmedtech.com.sg
Important Notice
This public version presents the Humanoid Eldercare Robotics Ethical Readiness Index (HERI™) Version 1.0 for transparency, academic discussion and future development purposes. HERI Version 1.0 represents an initial framework contribution in an emerging field and should be interpreted together with its stated research boundaries and limitations. Future development may include broader expert review, multi-site evaluation, inter-rater reliability assessment and additional validation activities.
Publication and Evidence Boundary
HERI Version 1.0 is presented as a framework-definition contribution developed within a bounded pioneer-developer context involving AJJ Healthcare Management and Hangzhou Huaxi Intelligent Technology. The framework is informed by literature review, system-level analysis and preliminary deployment-related observations. It should not be interpreted as an independently validated clinical instrument, regulatory standard or universal deployment certification system. Evidence discussed in this version should be interpreted as framework-support evidence intended to inform future refinement and evaluation activities.
Prior Public Version and Future Journal Submission Boundary
This document is released as a public framework-definition version intended to support transparency, discussion and institutional awareness. It is not presented as a peer-reviewed journal publication and should not be interpreted as the final scholarly version of HERI. Future journal submissions may contain expanded methodology, additional evidence, independent validation results, refined scoring approaches and updated framework components.
Abstract
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The rapid emergence of embodied AI humanoid robots in eldercare settings is creating new opportunities for supporting ageing populations, workforce shortages and long-term care delivery. However, the deployment of such systems also raises significant ethical, legal, governance and institutional readiness challenges involving vulnerable older adults, caregivers, healthcare organisations and public-interest obligations. Although existing literature provides important contributions in AI ethics, care robotics, dignity protection, accountability and human–robot interaction, most frameworks remain principle-oriented and do not provide a practical mechanism for evaluating whether a robot is ethically ready for deployment in a real-world care environment. To address this gap, RR-Ethics™ introduces the Humanoid Eldercare Robotics Ethical Readiness Index (HERI™), a structured and evidence-oriented readiness framework designed to support institutional deployment assessment of embodied AI humanoid eldercare robotics. HERI Version 1.0 consists of ten assessment dimensions covering dignity and personhood protection, consent and autonomy safeguards, privacy and data proportionality, safety and medical boundary control, human oversight and override, legal accountability, auditability, public health protection, emotional dependency management and caregiver fairness. The framework combines evidence-based scoring, weighted readiness assessment, critical-dimension floors and readiness-level interpretation to support transparent and systematic deployment review. HERI is intended as a decision-support framework rather than a regulatory, certification, legal or clinical approval mechanism. As an initial framework contribution developed within a bounded pioneer-developer context, HERI Version 1.0 should be regarded as a foundation for future expert review, independent evaluation and continued framework refinement.
Keywords: Humanoid eldercare robotics; ethical readiness; embodied AI; healthcare governance; responsible AI; long-term care; robotics ethics; institutional deployment
1. Introduction
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Population ageing is rapidly reshaping healthcare and long-term care systems worldwide[1]. Many countries are experiencing increasing demand for eldercare services while simultaneously facing persistent workforce shortages, rising care costs and growing pressure on institutional care environments . These challenges have stimulated significant interest in the development and deployment of advanced robotics, artificial intelligence (AI) and embodied AI systems capable of supporting care delivery[2].
Recent advances in embodied AI humanoid robotics have expanded the potential role of robots beyond industrial automation and logistics. Humanoid eldercare robots are increasingly being developed for functions such as companionship, information assistance, monitoring, mobility support, activity facilitation and selected care-related tasks. As these systems become more capable and socially interactive, they are also becoming more deeply integrated into environments involving vulnerable older adults, caregivers, healthcare organisations and public-interest responsibilities.
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The deployment of such systems creates opportunities to improve care capacity, operational efficiency and service accessibility. However, it also introduces a complex set of ethical, legal, governance and institutional challenges. Questions concerning dignity, autonomy, privacy, accountability, transparency, safety, emotional dependency and human oversight become increasingly important as robots move from experimental settings into real-world care environments[2-8].
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Over the past decade, substantial research has been conducted in fields including AI ethics, healthcare AI governance, social robotics, human–robot interaction and responsible innovation[2-8]. Existing literature has contributed valuable insights regarding ethical principles, risk identification and normative guidance for care-related technologies. Nevertheless, most existing approaches remain principle-oriented and do not provide institutions with a practical mechanism for evaluating whether a specific robotic system is ethically prepared for deployment.
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In practice, healthcare providers, long-term care operators and technology developers often face a more operational question:
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Is a humanoid eldercare robot ethically ready for deployment within a real-world care environment?
Answering this question requires more than the identification of ethical concerns. Institutions must be able to assess evidence, evaluate safeguards, review governance structures and determine whether appropriate protections have been established before deployment occurs.
To address this implementation gap, RR-Ethics™ introduces the Humanoid Eldercare Robotics Ethical Readiness Index (HERI™). HERI is designed as a structured and evidence-oriented framework for assessing ethical readiness in institutional eldercare settings. Rather than focusing solely on ethical principles, HERI seeks to translate ethical expectations into observable deployment requirements that can be reviewed, documented and assessed.
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HERI Version 1.0 consists of ten assessment dimensions covering dignity and personhood protection, consent and autonomy safeguards, privacy and data proportionality, safety and medical boundary control, human oversight, accountability, auditability, public health protection, emotional dependency management and caregiver fairness. Together, these dimensions form a readiness architecture intended to support transparent, systematic and human-centred deployment evaluation.
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As an initial framework contribution developed within an emerging field, HERI Version 1.0 should be understood as a foundation for future refinement, independent evaluation and broader validation efforts.
2. Existing Ethical Assessment Gap
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The growing body of literature on AI ethics, healthcare governance and social robotics has significantly advanced understanding of the ethical challenges associated with robotic care technologies. Existing studies have explored important issues including dignity protection, autonomy, accountability, privacy, emotional dependency, trust, human–robot interaction and responsible deployment within care environments[2-8].
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These contributions provide valuable ethical foundations and have helped identify many of the risks that may emerge when robots are introduced into eldercare settings. However, most existing approaches focus primarily on ethical principles, conceptual analysis or risk discussion. Relatively few provide a structured mechanism for determining whether a specific robotic system is ethically prepared for deployment within a real-world institutional environment.
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From an operational perspective, care providers, healthcare organisations and deployment partners require more than ethical awareness. They must also be able to evaluate evidence, assess safeguards, review governance mechanisms and determine whether minimum readiness conditions have been achieved before deployment occurs.
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As a result, a practical gap remains between ethical principles and deployment decision-making. Existing frameworks often help answer:
What ethical issues should be considered?
What risks may arise?
What principles should guide responsible innovation?
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However, institutions frequently require an additional question to be addressed:
Has sufficient ethical readiness been demonstrated to support deployment?
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HERI was developed to address this implementation-oriented gap. Rather than replacing existing ethical frameworks, HERI seeks to translate key ethical expectations into a structured readiness architecture supported by evidence requirements, weighted assessment, critical-dimension safeguards and deployment readiness interpretation.
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Within the reviewed comparator literature and public-source search scope, HERI is positioned as a first-definition-type, deployment-oriented ethical readiness framework that operationalises established care-robot ethics, healthcare AI governance and AI robot accountability principles into a structured, evidence-linked assessment architecture for embodied AI humanoid eldercare robotics.
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Table 1 summarises several influential contributions that informed HERI development and highlights the distinction between principle-oriented ethics frameworks and deployment-oriented readiness assessment.
3. HERI V1.0 Methodology and Scoring Architecture
3.1. Framework Purpose
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The Humanoid Eldercare Robotics Ethical Readiness Index (HERI™) was developed to provide a structured, evidence-oriented mechanism for assessing ethical readiness prior to the deployment of embodied AI humanoid robots in institutional eldercare environments. Unlike principle-oriented ethics frameworks that primarily identify ethical concerns or normative obligations, HERI focuses on deployment readiness. The framework is designed to support institutional review by translating ethical expectations into observable evidence requirements, structured assessment criteria and readiness-level interpretation. HERI does not assess technological capability, engineering performance or commercial competitiveness. Instead, the framework focuses on whether sufficient ethical, governance, accountability and safety safeguards have been established before deployment occurs.
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The framework is intended to support:
• institutional deployment review;
• governance and oversight assessment;
• deployment-risk identification;
• documentation and evidence evaluation;
• readiness benchmarking across care environments.
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HERI should be interpreted as a decision-support framework rather than a regulatory approval mechanism, legal opinion, certification programme or clinical authorisation system. To operationalise these objectives, HERI integrates ethical principles, governance safeguards, evidence requirements and deployment-readiness criteria into a unified assessment architecture.
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A HERI assessment should be tied to a specific robot configuration, deployment function, institution, software version and assessment date, and should not be generalised across different deployment contexts without further review.
The architecture links the pioneer-developer evidence boundary, structured literature comparison, ten HERI dimensions, critical floors, deployment gates and future validation roadmap.
3.2. Composite Formula, Scoring Scale and Weighting Principle
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Each HERI dimension is assessed using a 0–5 evidence-maturity scoring scale. This scale is designed to distinguish between absence of evidence, initial awareness, partial documentation, defined controls, evidence-supported implementation and mature auditable readiness.
The weighted raw HERI score is calculated as follows:
where si represents the 0–5 score of HERI dimension i, and wi represents the assigned weight of that dimension.
For readiness interpretation, the raw score is normalised to a 0–1 scale:
Using the proposed HERI V1.0 dimension set, the weighted formula may be expanded as follows:
where the abbreviations are defined as follows:
• HD = Dignity and personhood protection;
• IC = Consent, autonomy and proxy safeguards;
• PDP = Privacy and data proportionality;
• SMB = Safety and medical boundary control;
• HO = Human oversight and override;
• LA = Legal accountability and responsibility chain;
• AT = Auditability and traceability;
• PHW = Public health and workplace safety;
• EDR = Emotional dependency and substitution control;
• CJT = Caregiver justice, training and workflow fairness.
The proposed weighting structure is initial and evidence-informed. It reflects the higher deployment significance of safety and medical boundary control while preserving balanced attention to dignity, consent, privacy, oversight, accountability, auditability, public health, emotional dependency and caregiver justice. Future expert review, inter-rater reliability testing, Delphi-style refinement, sensitivity analysis and multi-site validation may further refine these weights. HERI should not be interpreted as an automatic mathematical decision tool. A deployment may achieve a relatively high aggregate score but still remain ethically unready if critical safeguards are insufficient.
3.3. Ten HERI Dimensions, Literature Anchors and Evidence Requirements
HERI Version 1.0 evaluates ethical readiness through ten dimensions representing key ethical, legal, governance, public-health and operational considerations associated with the deployment of embodied AI humanoid robots in eldercare environments. The dimensions were derived from the comparator literature reviewed in Section 2 and translated into deployment-oriented assessment criteria through the HERI framework architecture. Rather than functioning as isolated ethical categories, the dimensions are intended to operate as an integrated readiness system in which dignity, autonomy, privacy, safety, oversight, accountability and organisational safeguards collectively contribute to deployment readiness. Each dimension is associated with a defined literature anchor, evidence requirements, core scoring question and deployment risk rationale. Together, these dimensions provide the substantive assessment foundation of HERI Version 1.0. Table 2 presents the ten HERI dimensions, associated literature anchors and evidence requirements.
3.4. Evidence-Maturity Scoring Levels
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To support consistent assessment across institutions and deployment contexts, HERI adopts a structured evidence-maturity scoring approach. The scoring framework is intended to evaluate not only whether a safeguard exists, but also the extent to which it is documented, implemented, evidenced and auditable. The evidence-maturity model recognises that ethical readiness develops progressively. Organisations may demonstrate awareness of a requirement without having fully implemented controls, while more mature deployments are expected to provide documented procedures, supporting records and evidence of operationalisation. Accordingly, HERI uses a five-level evidence-maturity framework ranging from absence of evidence to mature and auditable implementation. Table 3 summarises the evidence-maturity scoring levels used throughout HERI Version 1.0.
3.5 Readiness Levels and Critical Floors
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The overall HERI score is intended to support readiness interpretation rather than provide a simple pass-or-fail outcome. Ethical readiness exists along a continuum, and institutions may demonstrate varying levels of preparedness depending on governance maturity, evidence quality and deployment safeguards. To facilitate deployment review, HERI groups overall scores into readiness categories that reflect increasing levels of ethical preparedness[8]. These categories are designed to support institutional decision-making, remediation planning and future deployment benchmarking. However, ethical readiness cannot be determined solely by aggregate scores. Certain dimensions represent foundational safeguards whose absence may create unacceptable deployment risks regardless of overall performance in other areas. For this reason, HERI incorporates critical-dimension floors to prevent high aggregate scores from masking significant deficiencies in core areas such as safety, oversight, accountability or privacy protection. Table 4 presents the HERI readiness-level interpretation framework.
4. Illustrative Evidence Requirements and Example Application
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HERI is intended to support evidence-based ethical readiness assessment rather than principle-based review alone. Accordingly, each dimension is associated with observable evidence requirements that may be examined during institutional assessment. Examples of supporting evidence may include governance documents, deployment protocols, safety procedures, consent processes, audit records, staff training materials, accountability structures, privacy safeguards and operational review mechanisms. The purpose of evidence collection is not to demonstrate perfection, but to establish whether sufficient safeguards have been implemented and documented to support responsible deployment. To illustrate how evidence may be mapped to HERI dimensions, Version 1.0 includes an example evidence-reference structure. The example is intended for explanatory purposes and should not be interpreted as a mandatory documentation standard. Table 6 provides an illustrative mapping between HERI dimensions and representative evidence categories that may be considered during readiness assessment.
5. Limitations and Future Development
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HERI Version 1.0 should be interpreted as an initial framework contribution developed within an emerging field of embodied AI humanoid eldercare robotics. While the framework seeks to translate established ethical principles into a structured readiness architecture, several limitations should be acknowledged. First, HERI Version 1.0 was developed within a bounded pioneer-developer context and therefore does not constitute an independently validated assessment instrument. The framework is intended to provide an initial operational model rather than a finalised standard. Second, the proposed weighting structure reflects evidence-informed judgement and literature-supported prioritisation. Although the weighting approach was designed to align with deployment-risk considerations, future refinement may further improve consistency and generalisability. Third, HERI Version 1.0 has not yet undergone large-scale inter-rater reliability testing across multiple independent institutions. Additional evaluation is required to assess scoring consistency under different deployment conditions and assessment teams.
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Future development of HERI may include:
• broader expert review and feedback;
• Delphi-based refinement of dimensions and weighting structures;
• inter-rater reliability assessment;
• multi-site evaluation across diverse eldercare environments;
• sensitivity analysis of scoring and weighting assumptions;
• comparison with emerging international governance frameworks;
• future HERI version updates informed by empirical deployment experience.
HERI is intended to evolve through ongoing review, practical application and independent evaluation. Future versions may incorporate additional evidence, refined scoring approaches and expanded deployment guidance as the field of embodied AI eldercare robotics continues to mature.
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6.Conclusions
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The emergence of embodied AI humanoid robotics in eldercare environments presents significant opportunities for addressing workforce shortages, supporting care delivery and improving service accessibility. At the same time, these technologies introduce complex ethical, legal, governance and deployment challenges that extend beyond technical performance alone. Existing literature has established important ethical principles and identified many of the risks associated with care-related robotics. However, institutions often require a more operational mechanism for determining whether sufficient ethical safeguards have been established prior to deployment. To address this gap, RR-Ethics™ introduces the Humanoid Eldercare Robotics Ethical Readiness Index (HERI™), a structured and evidence-oriented framework designed to support ethical readiness assessment for embodied AI humanoid eldercare robotics. HERI Version 1.0 integrates ten assessment dimensions, evidence-maturity scoring, weighted evaluation, critical-dimension safeguards and readiness-level interpretation into a unified deployment-review architecture. The framework is intended to support transparent, systematic and human-centred assessment while remaining distinct from regulatory approval, clinical certification or legal authorisation processes. As an initial framework contribution, HERI should be understood as a foundation for continued refinement, independent evaluation and future validation. The framework is expected to evolve alongside advances in robotics, artificial intelligence, eldercare practice and international governance expectations. By translating ethical principles into an operational readiness structure, HERI seeks to contribute to the responsible, accountable and human-centred deployment of embodied AI humanoid robotics within eldercare environments.
Declarations
Prior Public Version Disclosure
This company-led technical preprint / technical disclosure version is made available for transparency, version control and public reference. It has not undergone independent peer review. If a substantially revised manuscript is later submitted to a peer-reviewed journal, this public version and DOI/URL should be disclosed to the target journal in accordance with its editorial policy.
Author Contributions
Conceptualization, Jian Zhang and Chunqiu Yan; methodology, Jian Zhang, Xin Zhao, Weijie Tan, Tian Shen and Hon Hsiang Ong; framework development, Jian Zhang, Xin Zhao, Tian Shen, Weijie Tan, Wentao Zhao, Qiang Huang, Wenqun Guo and Hon Hsiang Ong; institutional workflow interpretation and documentation review, Wentao Zhao, Qiang Huang, Wenqun Guo and Weijie Tan; robotics deployment context and technical interpretation, Tingting Shen, Tian Shen and Chunqiu Yan; evidence coordination and supplementary documentation, Xin Zhao, Tian Shen, Tingting Shen, Chunqiu Yan and Hon Hsiang Ong; writing—original draft preparation, Xin Zhao, Tian Shen, Weijie Tan, Hon Hsiang Ong and Jian Zhang; writing—review and editing, all authors; supervision, Jian Zhang. All authors have read and approved this technical report / technical disclosure version.
Funding
This research received no external funding.
Institutional Review Board Statement
Not applicable. This technical report presents an ethical-readiness assessment framework and framework-development study. It does not report a clinical trial, clinical intervention, medical treatment evaluation or human-subject biomedical research. The evidence categories discussed in this report are anonymised, aggregated or governance-level records used for framework demonstration and evidence-boundary analysis. Any future empirical validation involving human participants, identifiable personal data, resident-level records, clinical evaluation or interventional deployment should obtain appropriate ethics, consent, institutional, data-protection and regulatory review.
Informed Consent Statement
Not applicable. No personally identifiable resident data, identifiable medical records, biometric identification data or individual clinical decision data are disclosed in this manuscript.
Data Availability Statement
The supporting evidence categories are anonymised, aggregated or retained internally under access-controlled conditions. Identifiable source records, signatures, photographs, resident-related data, staff-identifiable materials and institution-specific operational records are not publicly disclosed. Anonymised summaries and evidence-control materials may be made available by the corresponding author upon reasonable request, subject to institutional approval, confidentiality requirements and applicable data-protection obligations.
Conflicts of Interest
Several authors are affiliated with AJJ Healthcare Management Pte. Ltd. and Hangzhou Huaxi Intelligent Technology Co., Ltd., which are involved in healthcare technology, robotics-related deployment activities or related governance documentation. The RR-Ethics™ / HERI framework is proposed as an academic ethical-readiness assessment framework and should not be interpreted as regulatory approval, clinical validation, medical-device certification, commercial product certification, investment recommendation or universal deployment clearance. The authors declare that this technical report has been prepared for academic analysis, framework development and technical disclosure purposes, and that the interpretation and application of HERI remain subject to independent review, local regulation, institutional governance requirements and future validation.
Declaration of AI-Assisted Language and Editorial Support
AI-assisted tools were used during manuscript preparation to support English language editing, grammar refinement, formatting consistency, table organisation and structural clarity. The underlying research framework, field observations, operational evidence logic, validation design, model calculations, references, interpretation and conclusions were reviewed, verified and approved by the authors. No AI-assisted tool was used to generate original field data, fabricate source records, create unsupported references, replace institutional confirmation, perform independent research judgment or assume authorship responsibility.
Supplementary Materials
No supplementary files are publicly released with this company-led technical preprint / technical disclosure version. The HERI framework is supported by anonymised and institutionally controlled evidence materials retained by the research team for framework-development and evidence-control purposes. These materials are not published as supplementary files on this website and do not disclose identifiable resident data, individual medical records, biometric identifiers, facial images, voice recordings or individual clinical decision data. The evidence materials are used only to support the development of the HERI framework, pioneer-developer evidence mapping and future research refinement. They should not be interpreted as independent third-party validation, regulatory certification, clinical validation, medical-device approval, market assurance or final deployment approval.
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