Brain–Machine Interfaces as Commodities: Exchanging Mind for Matter

Reilly, Christopher M.

doi:10.1177/0024363920930882

Cited by 7 publications

(4 citation statements)

References 42 publications

(40 reference statements)

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“…Questions about explantation of neural implants at the end of a trial are a topic of debate, as amongst others the proportionality of risks and benefits remain unclear. It is currently uncertain how users may be affected by device removal 8,[20][21][22][23] , and long-term safety of neural implants is poorly understood [24][25][26][27][28] . Moreover, a lack of consensus existed regarding appropriate arrangements for continued access to neural implants post-trial, which is currently an important topic of scholarly debate 24,[29][30][31][32][33] .…”

Section: Aims Uncertainties and Hurdlesmentioning

confidence: 99%

Developer perspectives on the ethics of AI-driven neural implants: a qualitative study

van Stuijvenberg,

Broekman,

Wolff

et al. 2024

Sci Rep

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Convergence of neural implants with artificial intelligence (AI) presents opportunities for the development of novel neural implants and improvement of existing neurotechnologies. While such technological innovation carries great promise for the restoration of neurological functions, they also raise ethical challenges. Developers of AI-driven neural implants possess valuable knowledge on the possibilities, limitations and challenges raised by these innovations; yet their perspectives are underrepresented in academic literature. This study aims to explore perspectives of developers of neurotechnology to outline ethical implications of three AI-driven neural implants: a cochlear implant, a visual neural implant, and a motor intention decoding speech-brain-computer-interface. We conducted semi-structured focus groups with developers (n = 19) of AI-driven neural implants. Respondents shared ethically relevant considerations about AI-driven neural implants that we clustered into three themes: (1) design aspects; (2) challenges in clinical trials; (3) impact on users and society. Developers considered accuracy and reliability of AI-driven neural implants conditional for users’ safety, authenticity, and mental privacy. These needs were magnified by the convergence with AI. Yet, the need for accuracy and reliability may also conflict with potential benefits of AI in terms of efficiency and complex data interpretation. We discuss strategies to mitigate these challenges.

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Section: Aims Uncertainties and Hurdlesmentioning

confidence: 99%

Developer perspectives on the ethics of AI-driven neural implants: a qualitative study

van Stuijvenberg,

Broekman,

Wolff

et al. 2024

Sci Rep

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show abstract

“…BMIs hold immense promise for revolutionizing healthcare, rehabilitation, and even human augmentation. These technologies directly connect the brain to external devices, enabling communication and control in ways previously unimaginable 32 . While preliminary studies show promising results, the long-term safety and efficacy of implanted BMI devices remain unclear.…”

Section: Advancing Our Understanding Of Bmi Technologiesmentioning

confidence: 99%

“…While preliminary studies show promising results, the long-term safety and efficacy of implanted BMI devices remain unclear. Issues like tissue response, biocompatibility, and potential neural disruption require further investigation 32 .…”

Section: Advancing Our Understanding Of Bmi Technologiesmentioning

confidence: 99%

Microengineered neuronal networks: enhancing brain-machine interfaces

Kantawala,

Emir Hamitoglu,

Nohra

et al. 2024

Annals of Medicine &Amp; Surgery

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The Brain-Machine Interface (BMI), a crucial conduit between the human brain and computers, holds transformative potential for various applications in neuroscience. This manuscript explores the role of micro-engineered neuronal networks (MNNs) in advancing BMI technologies and their therapeutic applications. As the interdisciplinary collaboration intensifies, the need for innovative and user-friendly BMI technologies becomes paramount. A comprehensive literature review sourced from reputable databases (PubMed Central, Medline, EBSCOhost, Google Scholar) aided in the foundation of the manuscript, emphasizing the pivotal role of MNNs. This study aims to synthesize and analyse the diverse facets of MNNs in the context of BMI technologies, contributing insights into neural processes, technological advancements, therapeutic potentials, and ethical considerations surrounding BMIs. MNNs, exemplified by dual-mode neural microelectrodes, offer a controlled platform for understanding complex neural processes. Through case studies, we showcase the pivotal role of MNNs in BMI innovation, addressing challenges, and paving the way for therapeutic applications. The integration of MNNs with BMI technologies marks a revolutionary stride in neuroscience, refining brain-computer interactions and offering therapeutic avenues for neurological disorders. Challenges, ethical considerations, and future trends in BMI research necessitate a balanced approach, leveraging interdisciplinary collaboration to ensure responsible and ethical advancements. Embracing the potential of MNNs is paramount for the betterment of individuals with neurological conditions and the broader community.

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“…The operational intricacies of BCIs remain independent and imperceptible, leaving users uncertain about the extent of information transfer and its utilization. Users may harbor suspicions that the device or external manipulation of their prosthetic limb is making incorrect decisions that could harm people [18]. BCI users are frequently willing to voluntarily relinquish privacy for training or research and development, sending sensitive brain data from the edge to the cloud for training [19].…”

Section: The Lost Situation Of Privacy Disclosurementioning

confidence: 99%

Perspective and Boundary Exploration of Privacy Transfer Dilemma in Brain–Computer Interface—Dimension Based on Ethical Matrix

Zhang

2024

Philosophies

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The advent of intelligent technologies, notably Brain–Computer Interfaces (BCIs), has introduced novel privacy dilemmas. Ensuring judicious privacy transfer is imperative for the application of BCI technology and pivotal for fostering economic and technological progress. This study adopts privacy transfer as the research perspective and employs an ethical matrix as the research method. It establishes BCI users as the central core interests, with marketers, developers, and medical personnel as stakeholders. Departing from the binary opposition of public and private in traditional privacy theory, this article proposes ethical principles such as maximizing benefits, minimizing harm, and respecting independent decision-making power. It constructs a judgment matrix for the privacy transfer of BCIs, utilizing this matrix to identify ethical risks like privacy disclosure and hijacking. This study analyzes the reasons for risks, aiming to overcome dilemmas and construct an ethical matrix to explore privacy transfer boundary division methods suitable for BCI technology and tailored to different stakeholders.

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Brain–Machine Interfaces as Commodities: Exchanging Mind for Matter

Cited by 7 publications

References 42 publications

Developer perspectives on the ethics of AI-driven neural implants: a qualitative study

Developer perspectives on the ethics of AI-driven neural implants: a qualitative study

Microengineered neuronal networks: enhancing brain-machine interfaces

Perspective and Boundary Exploration of Privacy Transfer Dilemma in Brain–Computer Interface—Dimension Based on Ethical Matrix

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