Brain-computer interfaces, disability, and the stigma of refusal: A factorial vignette study

Sample, Matthew; Sattler, Sebastian; Boehlen, Wren; Racine, Éric

doi:10.1177/09636625221141663

Cited by 4 publications

(4 citation statements)

References 68 publications

(86 reference statements)

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“…Neuroethics and neurotechnology governance discourses emerged to decrease or prevent the negative impact of neuro-advancements [3,4,11,13,14]. Disabled people are one of the main user targets for neuro-interventions [18][19][20][21][22][64][65][66][67], and what counts as a neuro-impairment constantly shifts [68][69][70][71].…”

Section: Discussionmentioning

confidence: 99%

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Neuro-Abilities and a Good Life

Wolbring

2024

J Neurol Res

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Background: Neuro-based scientific and technological advancements constantly shape and are shaped by body/mind ability expectations, which in turn influence the perception and meaning of below species-typical (impaired), species-typical (normal) and beyond species-typical abilities (enhanced), which neuro-abilities are desired, and what neuro-ability-related actions are taken. Neuro-abilities from below to beyond species-typical abilities impact many indicators of well-being, or in other words the ability to have a good life. Disabled people experience barriers to a good life, many of which are outlined in the United Nations Convention on the Rights of Persons with Disabilities. Therefore, it is of importance to disabled people how neuroadvancements and neuro-ability expectations are governed. Abilitybased theoretical concepts could be used to discuss and analyze in a systematic fashion neuro-ability expectation dynamics, the impact of neuro-advancements and human enhancements including neuro/cognitive enhancements on the ability to have a good life and contribute a unique lens to neuroethics, neurotechnology governance and ability expectation governance efforts. Methods:In this study an online survey approach was used to ascertain the views of first-year undergraduate disability studies students on the impact of neurotechnologies, neuro/cognitive enhancements and human enhancements on the good life and the impact of being a disabled person in general and belonging to another marginalized group on experiencing a good life. Neuro-focused academic abstracts obtained from Scopus, Web of Science, and the 70 databases of EB-SCO-HOST were searched for the presence of ability-based concepts.Results: Students indicated that: 1) Disabled people will be increasingly impacted in a positive way by human enhancements and neurotechnologies; 2) Disabled people in general and even more if they belong also to another disadvantaged group experience a lower level of or are more impacted by most of the indicators of the four composite well-being measures (Social Determinants of Health; Canadian Index of Well-being, OECD Better Life Index and World Health Organization Community-Based Rehabilitation Matrix) than non-disabled people; and 3) More indicators of well-being of the four composite well-being measures are impacted by neurotechnologies and neuro/ cognitive enhancements than not impacted. The review of the academic abstracts indicated that ability-based concepts were not used to discuss neuro-advancements or neuro-enhancements. Conclusions:The findings of this study suggests that an in-depth engagement with the impact of neuro-advancements on the ability for a good life, especially in relation to disabled people, is warranted as is the use of ability-based concepts as an analytical lens.

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Section: Discussionmentioning

confidence: 99%

“…Disabled people are one of the main user targets for neuro-interventions [18][19][20][21][22], especially brain-computer interfaces [64][65][66], often under the header of assistive technologies [67]. Furthermore, what counts as a neuro-impairment constantly shifts.…”

Section: Neurotechnologies and Neuro/cognitive Enhancements: Disabled...mentioning

confidence: 99%

Neuro-Abilities and a Good Life

Wolbring

2024

J Neurol Res

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“…However, using non-invasive BCIs can sometimes stigmatize users [ 24 ]. Furthermore, the general adoption of these systems also for people without disabilities can reduce stigmatization, but it can widen the stigmatization of people with disabilities who will not use these systems, especially from the perspective of a transhumanist future [ 25 , 26 ]. The conspicuous use of these devices could make the user's medical problem more apparent or even the user can be treated by society as a 'cyborg' [ 27 ].…”

Section: Reviewmentioning

confidence: 99%

Understanding the Ethical Issues of Brain-Computer Interfaces (BCIs): A Blessing or the Beginning of a Dystopian Future?

Livanis,

Voultsos,

Vadikolias

et al. 2024

Cureus

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In recent years, scientific discoveries in the field of neuroscience combined with developments in the field of artificial intelligence have led to the development of a range of neurotechnologies. Advances in neuroimaging systems, neurostimulators, and brain-computer interfaces (BCIs) are leading to new ways of enhancing, controlling, and "reading" the brain. In addition, although BCIs were developed and used primarily in the medical field, they are now increasingly applied in other fields (entertainment, marketing, education, defense industry). We conducted a literature review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines to provide background information about ethical issues related to the use of BCIs. Among the ethical issues that emerged from the thematic data analysis of the reviewed studies included questions revolving around human dignity, personhood and autonomy, user safety, stigma and discrimination, privacy and security, responsibility, research ethics, and social justice (including access to this technology). This paper attempts to address the various aspects of these concerns. A variety of distinct ethical issues were identified, which, for the most part, were in line with the findings of prior research. However, we identified two nuances, which are related to the empirical research on ethical issues related to BCIs and the impact of BCIs on international relationships. The paper also highlights the need for the cooperation of all stakeholders to ensure the ethical development and use of this technology and concludes with several recommendations. The principles of bioethics provide an initial guiding framework, which, however, should be revised in the current artificial intelligence landscape so as to be responsive to challenges posed by the development and use of BCIs.

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“…Through the feature extraction of electroencephalogram (EEG) signals and using machine learning classifier to obtain accurate classification results of motor imagery (MI), the successful application of BCI technology can be achieved [2]. At present, MI-based BCI signals have played a role in intelligent assisted driving [3], brain-controlled robots [4], and life support for the disabled [5].…”

Section: Introductionmentioning

confidence: 99%

Feature Extraction of Motor Imagery EEG via Discrete Wavelet Transform and Generalized Maximum Fuzzy Membership Difference Entropy: A Comparative Study

et al. 2023

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Identifying motor imagery (MI) electroencephalogram (EEG) is an important way to achieve brain–computer interface (BCI), but its applicability is heavily dependent on the performance of feature extraction procedure. In this paper, a feature extraction method based on generalized maximum fuzzy membership difference entropy (GMFMDE) and discrete wavelet transform (DWT) was proposed for the feature extraction of EEG signals. The influence of different distance calculation methods, embedding dimensions and tolerances were studied to find the best configuration of GMFMDE for the feature extraction of MI–EEG. The gradient boosting decision tree (GBDT) classifier was used to classify the features extracted from GMFMDE and DWT. The average classification accuracy of 93.71% and the maximum classification accuracy of 96.96% were obtained, which proved the effectiveness of the proposed feature extraction method for EEG signal feature extraction.

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Brain-computer interfaces, disability, and the stigma of refusal: A factorial vignette study

Cited by 4 publications

References 68 publications

Neuro-Abilities and a Good Life

Neuro-Abilities and a Good Life

Understanding the Ethical Issues of Brain-Computer Interfaces (BCIs): A Blessing or the Beginning of a Dystopian Future?

Feature Extraction of Motor Imagery EEG via Discrete Wavelet Transform and Generalized Maximum Fuzzy Membership Difference Entropy: A Comparative Study

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