The functional differentiation of brain-computer interfaces (BCIs) and its ethical implications

The paper addresses the growing ethical debate surrounding BCIs, noting concerns over safety, privacy, informed consent, identity, responsibility, and social justice. Prior works have demonstrated risks such as physical safety issues due to immature standards, exposure of brain information, and the collection of private and sensitive data via consumer BCIs. Scholars also highlight effects on identity and agency, public views on responsibility for BCI users, and fairness concerns. A key gap identified is that most analyses treat BCIs monolithically and overlook functional and technical differences between write-in and read-out systems. The authors propose that because distinct technical approaches lead to distinct ethical consequences, governance must differentiate between write-in and read-out BCIs and adopt a precise governance approach tailored to each.

The paper surveys extensive prior scholarship: safety and privacy concerns in BCIs (Bonaci et al., Klein et al., Ienca et al.), effects on identity and self-conception (Versalovic et al., Postan), public attitudes toward responsibility (Schmid et al.), and fairness (Burwell et al.). It discusses debates on agency and autonomy in clinical populations (Abbott and Peck; Gilbert et al.), and the potential for BCIs to alter agency. The review also references technical capabilities of read-out BCIs in motor and language restoration and speculative applications such as lie detection, along with vulnerabilities (e.g., malware, brain “spyware”). It emphasizes that prior ethical analyses often lack differentiation between write-in (stimulation-based) and read-out (signal decoding) BCIs, despite evidence that these functions yield different ethical profiles (e.g., Mazurek and Schieber 2021).

The study is a conceptual and normative analysis rather than an empirical investigation. It: (1) functionally distinguishes BCIs into write-in (stimulation-based, e.g., DBS, cochlear implants) and read-out (signal acquisition and decoding, e.g., EEG/fMRI-based systems); (2) comparatively examines their technical approaches, maturity, risks, and feasibility; (3) analyzes ethical implications specific to each type across seven domains (safety, privacy, identity, autonomy/agency, responsibility, fairness, informed consent), summarized in a comparative table; and (4) proposes a precision governance (PG) framework that tailors ethical and technical governance measures to the distinct challenges of write-in and read-out BCIs. The methodology synthesizes existing technical and ethical literature to derive differentiated governance recommendations.

- Functional differentiation: Write-in BCIs inject or stimulate neural activity (e.g., DBS), whereas read-out BCIs record neural activity and decode intentions to control external effectors. This functional split leads to distinct risk profiles and ethical implications. - Technical contrasts: Write-in BCIs involve invasive procedures with surgical and stimulation risks, uncertain mechanisms, feasibility concerns (e.g., inflammation, gliosis), and long-term safety unknowns. Read-out BCIs are generally non-invasive and feasible for extended use but face signal accuracy and transmission limitations (e.g., skull/scalp interference) and potential security vulnerabilities. - Ethical profiles (from Table 1 synthesis): • Write-in BCIs: Major issues include safety (large impact), identity (large), autonomy and agency (large). Privacy is present but slight. Responsibility and fairness are significant; informed consent is a shared concern. • Read-out BCIs: Privacy is the predominant concern (large impact). Safety, autonomy/agency issues are generally slight; fairness and responsibility still arise though with different magnitudes; informed consent similarly applies. - Privacy risk amplification in read-out BCIs: These systems can collect brain and auxiliary data enabling inferences about intentions, beliefs, health, and traits; are vulnerable to malware/“brain spyware”; and could enable manipulation or coercion. Notably, non-invasive fMRI language decoders have achieved up to ~82% accuracy in speech perception tasks, heightening privacy concerns as capabilities advance. - Governance mismatch: Treating BCIs monolithically can over-regulate low-risk areas while missing high-risk ones, potentially stifling innovation and failing to protect users. - Precision governance recommendations: For write-in BCIs, prioritize safety, mechanism clarity, feasibility, and protection of identity and autonomy; restrict deployment until high safety standards are met and implement audits and review mechanisms. For read-out BCIs, improve technical performance/accuracy and institute robust privacy/security protections, standards, and monitoring. For shared issues, clarify responsibility attribution, strengthen legal/policy protections (including consent), and address distributive justice via pricing, subsidies, and context-sensitive allocation.

By differentiating write-in from read-out BCIs, the analysis shows how technical mechanisms drive distinct ethical landscapes. This directly addresses the initial problem of governance mismatch by arguing that ethical governance should be tailored to function-specific risks and needs. The proposed precision governance framework operationalizes this by separating ethical and technical governance tracks and recommending targeted measures: safety-first restrictions and autonomy/identity protections for write-in; performance improvements and privacy/security safeguards for read-out; and cross-cutting responsibility, fairness, and consent measures. This differentiation can prevent overgeneralized rules that either misallocate resources or inadvertently hinder beneficial applications, and it can more effectively mitigate real harms while facilitating responsible development and deployment of BCI technologies.

The paper concludes that BCIs should be functionally differentiated into write-in and read-out categories for ethical analysis and governance. Write-in BCIs face pronounced challenges in safety, mechanism uncertainty, and feasibility, and pose significant ethical issues regarding user security, identity, autonomy, and agency. Read-out BCIs primarily raise privacy and security concerns, alongside technical performance limitations. Effective governance requires a precision governance approach with tailored ethical and technical measures for each BCI type, complemented by common policies on responsibility, fairness, and informed consent. The authors note a limitation in their reliance on a general, contested notion of identity and anticipate future convergence of write-in and read-out techniques, calling for continued research, clinical attention, and investment.

The authors acknowledge that identity is a complex, contested concept; their analysis relies on a general definition, which limits precision in assessing identity-related impacts. They also note that future BCIs will likely combine write-in and read-out techniques, implying that governance approaches must evolve as hybrid systems emerge.