Deceased Data Rights Explained

• Deceased individuals’ data rights are legal, ethical, and technical frameworks that govern posthumous handling of personal digital assets.
• They encompass principles of deletion, inheritance, and harm prevention, addressing gaps in existing privacy laws and system architectures.
• Key challenges include fragmented regulations, advanced deletion methods like machine unlearning, and developing ethical guidelines for digital legacies.

Deceased individuals’ data rights refer to the legal, ethical, and technical principles that govern the access, preservation, deletion, inheritance, and use of personal data belonging to persons who have died. The management of such data presents unique challenges, especially as digital assets proliferate across cloud services, AI models, and clinical research repositories. Policies and practices in this area intersect with privacy laws, data stewardship frameworks, user preferences, and the operational requirements of large-scale data systems.

1. Regulatory and Industry Landscape

Current privacy regimes such as the GDPR, CCPA, and LGPD afford comprehensive data rights to living individuals, but these protections rarely extend to deceased users (Jarin et al., 9 Sep 2025). Regulations including the EU AI Act impose transparency and anti-abuse requirements on generative AI systems but remain silent on explicit safeguards for post-mortem data. Industry practices across major platforms (e.g., Facebook, Google, Apple, Microsoft) highlight this gap: legacy contact features and memorialization procedures are typically limited to basic account management functions and do not constitute systematic post-mortem data protection or empowerment.

This fragmented regulatory environment introduces privacy and ethical risks. Data belonging to the deceased may be reused or exposed without consent, e.g., in digital clones (“griefbots”) or through inadvertent inclusion in training corpora for foundation models, posing reputational and emotional harm to families and violating expectations of privacy and dignity.

2. Principles and Frameworks for Post-mortem Data Rights

Efforts to conceptualize deceased individuals’ data rights have converged on a handful of principles (Jarin et al., 9 Sep 2025):

1. Post-mortem Data Deletion/Unlearning: Mechanisms should not only support deletion of identifiable personal data but also remove its influence from generative models, using techniques such as machine unlearning. The right to be forgotten, as implemented in GDPR-compliant frameworks, can extend to posthumous erasure if retention exemptions (e.g., legal archiving) are evaluated and logged (Goldsteen et al., 2019).
2. Data Inheritance and Ownership: Individuals should be empowered to decide whether their data is deleted, inherited by heirs, or used for specific purposes posthumously. Modalities of inheritance may cover direct data transfer, anonymized legacy preservation, or monetization without revealing raw data.
3. Purpose Limitation and Harm Prevention: Data designated for post-mortem research or social benefit must be governed by explicit, transparent agreements that enforce strict use limitations and provide safeguards for both the deceased’s legacy and survivors’ emotional wellbeing.

Operationalizing these principles requires integration into privacy policies, standardized workflows (such as a “digital will” mechanism), and technical auditability via watermarking or canary injection methods.

3. Technical Approaches and Systems for Deletion, Stewardship, and Legacy Management

Leading large-scale implementations for complying with deletion rights—potentially applicable to deceased data subjects—feature three core components (Goldsteen et al., 2019):

• System and Data Registry: Catalogs all data types, storage systems, and associated retention policies, specifying deletion commands and APIs. Policy exceptions (e.g., mandatory retention for financial or medical records) are encoded and documented.
• Workflow Engine: Manages erasure requests, capturing the full lifecycle from initiation and review through execution and evidence gathering. Audit trails link deletion activities to specific identifiers, supporting regulatory compliance.
• Execution Engine: Automates job dispatch to target systems, coordinates plugin-based deletion logic updates, and collects acknowledgment or evidence.

Deletion in distributed environments requires these subsystems to manage replicas, backups, derived data, and performance considerations. For instance, plugins can delay execution to avoid system overload and batch deletion tasks to avoid conflict with resource-intensive ETL operations.

Technical measures for generative AI (LLMs and foundation models) additionally require machine unlearning to eliminate residual influence after raw data deletion (Jarin et al., 9 Sep 2025). Cryptographic digital wills and privacy-by-design approaches (e.g., differential privacy with $\Delta f \leq \epsilon$) are advocated for fine-grained, auditable control.

4. User Preferences, Behavioral Barriers, and Design Recommendations

Empirical research has illuminated substantial public interest in controlling digital legacies post-mortem. Australians overwhelmingly prefer that data be managed by trusted individuals or user-configurable third-party software, while expressing low trust in social media companies for this role (Reeves et al., 1 Jul 2024). Survey analysis via linear regression demonstrates that Internet usage, education, and parenthood are significant predictors of stronger desires for posthumous data control, whereas age and gender show non-significant effects.

However, observed behavioral obstacles include the post-mortem privacy paradox (Holt et al., 2021): individuals value legacy planning but rarely act, deterred by emotional discomfort, perceived burden, and the mistaken belief that privacy practices in life naturally persist after death.

Design recommendations to address this gap include:

• Integrating granular legacy controls (e.g., selective credential sharing via password managers)
• Enabling periodic review of legacy preferences
• Automating or assisting legacy handover processes
• Establishing legal defaults with opt-out provisions for those unwilling to engage in detailed planning

Such solutions would enhance both security in life and accessibility after death, balancing privacy and legacy needs.

5. Data Rights in Clinical Research and Medical Domains

Clinical data warehouses (r-CDWs) and associated research projects increasingly require robust post-mortem data management. Linking EHRs to external death registries (e.g., SSA LADMF) involves deterministic token-based matching, with tokens constructed from standardized identifiers (SSN, names, birth date), evaluated for completeness and distinctiveness (Peralta et al., 2022). Federal regulations restrict access to certain death data for three years post-mortem, even for de-identified records.

Privacy-preserving linkage methods (hashing, tokenization) support ethical stewardship. However, linkage uncertainty (coverage vs. accuracy trade-off) and transparency in match error rates become critical—affecting not just the representation of deceased data but also downstream research outcomes and privacy obligations.

6. Emerging Issues in AI-Based Digital Reconstruction

The feasibility of generating “electronic copies” of deceased individuals via AI fine-tuning is now established, with inherited data volumes (on the order of one million words) sufficing for high-fidelity stylistic and domain-specific emulation (Zilberman, 3 Jul 2025). Applications include intellectual legacy preservation, research augmentation, and collaboration among digital personas. Nonetheless, unresolved ethical and legal issues persist:

• Ownership of inherited data and resulting AI models is ambiguous when multiple devices or contributors are involved
• Consent for posthumous digital reconstruction is often absent or unclearly expressed
• Risks of unauthorized access or misuse necessitate robust legal and security protocols

Societal implications include redefinitions of memory, identity, and legacy—necessitating new guidelines balancing technical innovation with ethical and legal responsibilities.

7. Future Directions and Policy Recommendations

Advancement in post-mortem data rights will require regulatory evolution to explicitly encompass deceased individuals, deploying technological measures that guarantee secure, auditable, and transparent processes (Jarin et al., 9 Sep 2025). Recommendations include:

• Extension of data protection laws to support posthumous rights, inheritance, and erasure
• Mandatory disclosure of post-mortem processing practices by AI agents
• Formalization of digital wills, modeled on testamentary freedom in estate law
• Deployment of evaluation and audit frameworks for confirming unlearning and privacy compliance in generative AI

Research should further empirically test these principles, evaluate the effectiveness of machine unlearning and related safeguards, and consider the diverse legal and cultural attitudes toward posthumous data.

Summary Table: Deceased Individuals Data Rights Dimensions

Dimension	Key Findings	Paper(s)
Regulatory Landscape	Data rights protections for deceased are limited and fragmented	(Jarin et al., 9 Sep 2025)
Technical Implementation	System/data registries, workflow engines, machine unlearning, cryptographic wills	(Goldsteen et al., 2019, Jarin et al., 9 Sep 2025)
User Preferences/Barriers	Desire for control; privacy paradox; low trust in platforms	(Holt et al., 2021, Reeves et al., 1 Jul 2024)
Clinical Data Stewardship	Federally regulated linkage, hashing, stewardship demands	(Peralta et al., 2022)
Digital Legacy AI Copy	Feasible fine-tuning; ethical, legal questions about ownership and consent	(Zilberman, 3 Jul 2025)

The evolving domain of deceased individuals’ data rights thus encompasses regulatory gaps, technical systems, public preferences, research stewardship practices, ethical dilemmas, and the unique implications posed by generative AI. Continued research, policy development, and system innovation are necessary to operationalize responsible and effective digital legacy protections.