Brain-computer interfaces and personhood: interdisciplinary deliberations on neural technology

Ethical issues raised by incorporating personalized language models into brain-computer interface communication technologies: a qualitative study of individuals with neurological disease

PURPOSE

To examine the views of individuals with neurodegenerative diseases about ethical issues related to incorporating personalized language models into brain-computer interface (BCI) communication technologies.

METHODS

Fifteen semi-structured interviews and 51 online free response surveys were completed with individuals diagnosed with neurodegenerative disease that could lead to loss of speech and motor skills. Each participant responded to questions after six hypothetical ethics vignettes were presented that address the possibility of building language models with personal words and phrases in BCI communication technologies. Data were analyzed with consensus coding, using modified grounded theory.

RESULTS

Four themes were identified. (1) The experience of a neurodegenerative disease shapes preferences for personalized language models. (2) An individual's identity will be affected by the ability to personalize the language model. (3) The motivation for personalization is tied to how relationships can be helped or harmed. (4) Privacy is important to people who may need BCI communication technologies. Responses suggest that the inclusion of personal lexica raises ethical issues. Stakeholders want their values to be considered during development of BCI communication technologies.

CONCLUSIONS

With the rapid development of BCI communication technologies, it is critical to incorporate feedback from individuals regarding their ethical concerns about the storage and use of personalized language models. Stakeholder values and preferences about disability, privacy, identity and relationships should drive design, innovation and implementation.IMPLICATIONS FOR REHABILITATIONIndividuals with neurodegenerative diseases are important stakeholders to consider in development of natural language processing within brain-computer interface (BCI) communication technologies.The incorporation of personalized language models raises issues related to disability, identity, relationships, and privacy.People who may one day rely on BCI communication technologies care not just about usability of communication technology but about technology that supports their values and priorities.Qualitative ethics-focused research is a valuable tool for exploring stakeholder perspectives on new capabilities of BCI communication technologies, such as the storage and use of personalized language models.

The End of Personhood

The concept of personhood has been central to bioethics debates about abortion, the treatment of patients in a vegetative or minimally conscious states, as well as patients with advanced dementia. More recently, the concept has been employed to think about new questions related to human-brain organoids, artificial intelligence, uploaded minds, human-animal chimeras, and human embryos, to name a few. A common move has been to ask what these entities have in common with persons (in the normative sense), and then draw conclusions about what we do (or do not) owe them. This paper argues that at best the concept of "personhood" is unhelpful to much of bioethics today and at worst it is harmful and pernicious. I suggest that we (bioethicists) stop using the concept of personhood and instead ask normative questions more directly (e.g., how ought we to treat this being and why?) and use other philosophical concepts (e.g., interests, sentience, recognition respect) to help us answer them. It is time for bioethics to end talk about personhood.

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

As brain-computer interfaces are promoted as assistive devices, some researchers worry that this promise to "restore" individuals worsens stigma toward disabled people and fosters unrealistic expectations. In three web-based survey experiments with vignettes, we tested how refusing a brain-computer interface in the context of disability affects cognitive (blame), emotional (anger), and behavioral (coercion) stigmatizing attitudes (Experiment 1, N = 222) and whether the effect of a refusal is affected by the level of brain-computer interface functioning (Experiment 2, N = 620) or the risk of malfunctioning (Experiment 3, N = 620). We found that refusing a brain-computer interface increased blame and anger, while brain-computer interface functioning did change the effect of a refusal. Higher risks of device malfunctioning partially reduced stigmatizing attitudes and moderated the effect of refusal. This suggests that information about disabled people who refuse a technology can increase stigma toward them. This finding has serious implications for brain-computer interface regulation, media coverage, and the prevention of ableism.

The Impact of Socially Assistive Robots on Human Flourishing in the Context of Dementia: A Scoping Review

Socially assistive robots are being developed and tested to support social interactions and assist with healthcare needs, including in the context of dementia. These technologies bring their share of situations where moral values and principles can be profoundly questioned. Several aspects of these robots affect human relationships and social behavior, i.e., fundamental aspects of human existence and human flourishing. However, the impact of socially assistive robots on human flourishing is not yet well understood in the current state of the literature. We undertook a scoping review to study the literature on human flourishing as it relates to health uses of socially assistive robots. Searches were conducted between March and July 2021 on the following databases: Ovid MEDLINE, PubMed and PsycINFO. Twenty-eight articles were found and analyzed. Results show that no formal evaluation of the impact of socially assistive robots on human flourishing in the context of dementia in any of the articles retained for the literature review although several articles touched on at least one dimension of human flourishing and other related concepts. We submit that participatory methods to evaluate the impact of socially assistive robots on human flourishing could open research to other values at stake, particularly those prioritized by people with dementia which we have less evidence about. Such participatory approaches to human flourishing are congruent with empowerment theory.

Use of Invasive Brain-Computer Interfaces in Pediatric Neurosurgery: Technical and Ethical Considerations

Invasive brain-computer interfaces hold promise to alleviate disabilities in individuals with neurologic injury, with fully implantable brain-computer interface systems expected to reach the clinic in the upcoming decade. Children with severe neurologic disabilities, like quadriplegic cerebral palsy or cervical spine trauma, could benefit from this technology. However, they have been excluded from clinical trials of intracortical brain-computer interface to date. In this manuscript, we discuss the ethical considerations related to the use of invasive brain-computer interface in children with severe neurologic disabilities. We first review the technical hardware and software considerations for the application of intracortical brain-computer interface in children. We then discuss ethical issues related to motor brain-computer interface use in pediatric neurosurgery. Finally, based on the input of a multidisciplinary panel of experts in fields related to brain-computer interface (functional and restorative neurosurgery, pediatric neurosurgery, mathematics and artificial intelligence research, neuroengineering, pediatric ethics, and pragmatic ethics), we then formulate initial recommendations regarding the clinical use of invasive brain-computer interfaces in children.

Public attitudes towards neurotechnology: Findings from two experiments concerning Brain Stimulation Devices (BSDs) and Brain-Computer Interfaces (BCIs)

This study contributes to the emerging literature on public perceptions of neurotechnological devices (NTDs) in their medical and non-medical applications, depending on their invasiveness, framing effects, and interindividual differences related to personal needs and values. We conducted two web-based between-subject experiments (2×2×2) using a representative, nation-wide sample of the adult population in Germany. Using vignettes describing how two NTDs, brain stimulation devices (BSDs; NExperiment 1 = 1,090) and brain-computer interfaces (BCIs; NExperiment 2 = 1,089), function, we randomly varied the purpose (treatment vs. enhancement) and invasiveness (noninvasive vs. invasive) of the NTD, and assessed framing effects (variable order of assessing moral acceptability first vs. willingness to use first). We found a moderate moral acceptance and willingness to use BSDs and BCIs. Respondents preferred treatment over enhancement purposes and noninvasive over invasive devices. We also found a framing effect and explored the role of personal characteristics as indicators of personal needs and values (e.g., stress, religiosity, and gender). Our results suggest that the future demand for BSDs or BCIs may depend on the purpose, invasiveness, and personal needs and values. These insights can inform technology developers about the public’s needs and concerns, and enrich legal and ethical debates.

Supervised and Semisupervised Manifold Embedded Knowledge Transfer in Motor Imagery-Based BCI

A long calibration procedure limits the use in practice for a motor imagery (MI)-based brain-computer interface (BCI) system. To tackle this problem, we consider supervised and semisupervised transfer learning. However, it is a challenge for them to cope with high intersession/subject variability in the MI electroencephalographic (EEG) signals. Based on the framework of unsupervised manifold embedded knowledge transfer (MEKT), we propose a supervised MEKT algorithm (sMEKT) and a semisupervised MEKT algorithm (ssMEKT), respectively. sMEKT only has limited labelled samples from a target subject and abundant labelled samples from multiple source subjects. Compared to sMEKT, ssMEKT adds comparably more unlabelled samples from the target subject. After performing Riemannian alignment (RA) and tangent space mapping (TSM), both sMEKT and ssMEKT execute domain adaptation to shorten the differences among subjects. During domain adaptation, to make use of the available samples, two algorithms preserve the source domain discriminability, and ssMEKT preserves the geometric structure embedded in the labelled and unlabelled target domains. Moreover, to obtain a subject-specific classifier, sMEKT minimizes the joint probability distribution shift between the labelled target and source domains, whereas ssMEKT performs the joint probability distribution shift minimization between the unlabelled target domain and all labelled domains. Experimental results on two publicly available MI datasets demonstrate that our algorithms outperform the six competing algorithms, where the sizes of labelled and unlabelled target domains are variable. Especially for the target subjects with 10 labelled samples and 270/190 unlabelled samples, ssMEKT shows 5.27% and 2.69% increase in average accuracy on the two abovementioned datasets compared to the previous best semisupervised transfer learning algorithm (RA-regularized common spatial patterns-weighted adaptation regularization, RA-RCSP-wAR), respectively. Therefore, our algorithms can effectively reduce the need of labelled samples for the target subject, which is of importance for the MI-based BCI application.

Influencing discussions and use of Neuroadvancements: Perspectives of Canadian occupational therapists

BACKGROUND: The early involvement of many actors including health professionals is identified in neuroethics and neurogovernance discussions as crucial in constructing conversations around awareness, reaction, and knowledge development pertaining to the ethical, legal, and societal consequences of neuroscientific or neurotechnological advancements (NA). Occupational Therapists (OTs) have a stake in NA; however, OTs are rarely mentioned within this context. Lifelong learning (LL) could be used to increase OTs knowledge on NA and its consequences. However, LL is rarely mentioned within neuroethics and neurogovernance discussions. OBJECTIVE: The study’s purpose is to understand the role of OTs as professionals and citizens in neuroethics and neurogovernance discussions and to examine the utility of LL processes put in place for OTs to empower OTs to contribute in a meaningful way to NA discussions. METHODS: 8 semi-structured interviews with OTs were conducted and analyzed using a directed content analysis. RESULTS: Although participants believed OTs can provide a holistic perspective to neurogovernance discussions, their knowledge on NA and its consequences is limited, and LL is not used as a tool to remain informed about such consequences. CONCLUSION: More education on NA and its consequences throughout their OT degree and through LL opportunities is warranted to facilitate their involvement.

Neurosurgical Team Acceptability of Brain-Computer Interfaces: A Two-Stage International Cross-Sectional Survey

OBJECTIVE

Invasive brain-computer interfaces (BCIs) require neurosurgical implantation, which confers a range of risks. Despite this situation, no studies have assessed the acceptability of invasive BCIs among the neurosurgical team. This study aims to establish baseline knowledge of BCIs within the neurosurgical team and identify attitudes toward different applications of invasive BCI.

METHODS

A 2-stage cross-sectional international survey of the neurosurgical team (neurosurgeons, anesthetists, and operating room nurses) was conducted. Results from the first, qualitative, survey were used to guide the second-stage quantitative survey, which assessed acceptability of invasive BCI applications. Five-part Likert scales were used to collect quantitative data. Surveys were distributed internationally via social media and collaborators.

RESULTS

A total of 108 qualitative responses were collected. Themes included the promise of BCIs positively affecting disease targets, concerns regarding stability, and an overall positive emotional reaction to BCI technology. The quantitative survey generated 538 responses from 32 countries. Baseline knowledge of BCI technology was poor, with 9% claiming to have a good or expert knowledge of BCIs. Acceptability of invasive BCI for rehabilitative purposes was >80%. Invasive BCI for augmentation in healthy populations divided opinion.

CONCLUSIONS

The neurosurgical team's view of the acceptability of invasive BCI was divided across a range of indications. Some applications (e.g., stroke rehabilitation) were viewed as more appropriate than other applications (e.g., augmentation for military use). This range in views highlights the need for stakeholder consultation on acceptable use cases along with regulation and guidance to govern initial BCI implantations if patients are to realize the potential benefits.

Ethical implications of visual neuroprostheses-a systematic review

Objective. The aim of this review was to systematically identify the ethical implications of visual neuroprostheses.Approach. A systematic search was performed in both PubMed and Embase using a search string that combined synonyms for visual neuroprostheses, brain-computer interfaces (BCIs), cochlear implants (CIs), and ethics. We chose to include literature on BCIs and CIs, because of their ethically relavant similarities and functional parallels with visual neuroprostheses.Main results. We included 84 articles in total. Six focused specifically on visual prostheses. The other articles focused more broadly on neurotechnologies, on BCIs or CIs. We identified 169 ethical implications that have been categorized under seven main themes: (a) benefits for health and well-being; (b) harm and risk; (c) autonomy; (d) societal effects; (e) clinical research; (f) regulation and governance; and (g) involvement of experts, patients and the public.Significance. The development and clinical use of visual neuroprostheses is accompanied by ethical issues that should be considered early in the technological development process. Though there is ample literature on the ethical implications of other types of neuroprostheses, such as motor neuroprostheses and CIs, there is a significant gap in the literature regarding the ethical implications of visual neuroprostheses. Our findings can serve as a starting point for further research and normative analysis.

Brain Computer Interfaces and Communication Disabilities: Ethical, Legal, and Social Aspects of Decoding Speech From the Brain

A brain-computer interface technology that can decode the neural signals associated with attempted but unarticulated speech could offer a future efficient means of communication for people with severe motor impairments. Recent demonstrations have validated this approach. Here we assume that it will be possible in future to decode imagined (i.e., attempted but unarticulated) speech in people with severe motor impairments, and we consider the characteristics that could maximize the social utility of a BCI for communication. As a social interaction, communication involves the needs and goals of both speaker and listener, particularly in contexts that have significant potential consequences. We explore three high-consequence legal situations in which neurally-decoded speech could have implications: Testimony, where decoded speech is used as evidence; Consent and Capacity, where it may be used as a means of agency and participation such as consent to medical treatment; and Harm, where such communications may be networked or may cause harm to others. We then illustrate how design choices might impact the social and legal acceptability of these technologies.

Influencing discussions and use of neuroadvancements as professionals and citizens: Perspectives of Canadian speech-language pathologists and audiologists

BACKGROUND: Early involvement of stakeholders in neuroethics and neurogovernance discourses of neuroscientific and neurotechnological advancements is seen as essential to curtail negative consequences. Speech-language pathologists (SLPs) and audiologists (AUs) make use of neuroadvancements including cochlear implants, brain-computer interfaces, and deep-brain stimulation. Although they have a stake in neuroethics and neurogovernance discussions, they are rarely mentioned in having a role, whether as professionals or as citizens. OBJECTIVE: The objective of the study was to explore the role of SLPs and AUs as professionals and citizens in neuroethics and neurogovernance discussions and examine the utility of lifelong learning mechanisms to learn about the implications of neuroadvancements to contribute in a meaningful way to these discussions. METHODS: Semi-structured interviews conducted with 7 SLPs and 3 AUs were analyzed using thematic analysis. RESULTS: Participants stated that their roles expected from them as professionals and as citizens indicate the importance to be knowledgeable on ethical, legal, and social implications of neuroadvancements and that lifelong learning is not used to learn about these implications. CONCLUSION: More must be done to facilitate the participation of SLPs and AUs in neuroethics and neurogovernance discussions, which would enrich the neuroethics and neurogovernance discourses benefitting patients, professionals, and the public.

Selective Cross-Subject Transfer Learning Based on Riemannian Tangent Space for Motor Imagery Brain-Computer Interface

A motor imagery (MI) brain-computer interface (BCI) plays an important role in the neurological rehabilitation training for stroke patients. Electroencephalogram (EEG)-based MI BCI has high temporal resolution, which is convenient for real-time BCI control. Therefore, we focus on EEG-based MI BCI in this paper. The identification of MI EEG signals is always quite challenging. Due to high inter-session/subject variability, each subject should spend long and tedious calibration time in collecting amounts of labeled samples for a subject-specific model. To cope with this problem, we present a supervised selective cross-subject transfer learning (sSCSTL) approach which simultaneously makes use of the labeled samples from target and source subjects based on Riemannian tangent space. Since the covariance matrices representing the multi-channel EEG signals belong to the smooth Riemannian manifold, we perform the Riemannian alignment to make the covariance matrices from different subjects close to each other. Then, all aligned covariance matrices are converted into the Riemannian tangent space features to train a classifier in the Euclidean space. To investigate the role of unlabeled samples, we further propose semi-supervised and unsupervised versions which utilize the total samples and unlabeled samples from target subject, respectively. Sequential forward floating search (SFFS) method is executed for source selection. All our proposed algorithms transfer the labeled samples from most suitable source subjects into the feature space of target subject. Experimental results on two publicly available MI datasets demonstrated that our algorithms outperformed several state-of-the-art algorithms using small number of the labeled samples from target subject, especially for good target subjects.

Brain-Computer Interfaces Systems for Upper and Lower Limb Rehabilitation: A Systematic Review

In recent years, various studies have demonstrated the potential of electroencephalographic (EEG) signals for the development of brain-computer interfaces (BCIs) in the rehabilitation of human limbs. This article is a systematic review of the state of the art and opportunities in the development of BCIs for the rehabilitation of upper and lower limbs of the human body. The systematic review was conducted in databases considering using EEG signals, interface proposals to rehabilitate upper/lower limbs using motor intention or movement assistance and utilizing virtual environments in feedback. Studies that did not specify which processing system was used were excluded. Analyses of the design processing or reviews were excluded as well. It was identified that 11 corresponded to applications to rehabilitate upper limbs, six to lower limbs, and one to both. Likewise, six combined visual/auditory feedback, two haptic/visual, and two visual/auditory/haptic. In addition, four had fully immersive virtual reality (VR), three semi-immersive VR, and 11 non-immersive VR. In summary, the studies have demonstrated that using EEG signals, and user feedback offer benefits including cost, effectiveness, better training, user motivation and there is a need to continue developing interfaces that are accessible to users, and that integrate feedback techniques.

Cognitive Enhancement: Unanswered Questions About Human Psychology and Social Behavior

Stimulant drugs, transcranial magnetic stimulation, brain-computer interfaces, and even genetic modifications are all discussed as forms of potential cognitive enhancement. Cognitive enhancement can be conceived as a benefit-seeking strategy used by healthy individuals to enhance cognitive abilities such as learning, memory, attention, or vigilance. This phenomenon is hotly debated in the public, professional, and scientific literature. Many of the statements favoring cognitive enhancement (e.g., related to greater productivity and autonomy) or opposing it (e.g., related to health-risks and social expectations) rely on claims about human welfare and human flourishing. But with real-world evidence from the social and psychological sciences often missing to support (or invalidate) these claims, the debate about cognitive enhancement is stalled. In this paper, we describe a set of crucial debated questions about psychological and social aspects of cognitive enhancement (e.g., intrinsic motivation, well-being) and explain why they are of fundamental importance to address in the cognitive enhancement debate and in future research. We propose studies targeting social and psychological outcomes associated with cognitive enhancers (e.g., stigmatization, burnout, mental well-being, work motivation). We also voice a call for scientific evidence, inclusive of but not limited to biological health outcomes, to thoroughly assess the impact of enhancement. This evidence is needed to engage in empirically informed policymaking, as well as to promote the mental and physical health of users and non-users of enhancement.

Ethical Aspects of BCI Technology: What Is the State of the Art?

Brain–Computer Interface (BCI) technology is a promising research area in many domains. Brain activity can be interpreted through both invasive and non-invasive monitoring devices, allowing for novel, therapeutic solutions for individuals with disabilities and for other non-medical applications. However, a number of ethical issues have been identified from the use of BCI technology. In this paper, we review the academic discussion of the ethical implications of BCI technology in the last five years. We conclude that some emerging applications of BCI technology—including commercial ventures that seek to meld human intelligence with AI—present new and unique ethical concerns. Further, we seek to understand how academic literature on the topic of BCIs addresses these novel concerns. Similar to prior work, we use a limited sample to identify trends and areas of concern or debate among researchers and ethicists. From our analysis, we identify two key areas of BCI ethics that warrant further research: the physical and psychological effects of BCI technology. Additionally, questions of BCI policy have not yet become a frequent point of discussion in the relevant literature on BCI ethics, and we argue this should be addressed in future work. We provide guiding questions that will help ethicists and policy makers grapple with the most important issues associated with BCI technology.

Injecting Information into the Mammalian Cortex: Progress, Challenges, and Promise

For 150 years artificial stimulation has been used to study the function of the nervous system. Such stimulation-whether electrical or optogenetic-eventually may be used in neuroprosthetic devices to replace lost sensory inputs and to otherwise introduce information into the nervous system. Efforts toward this goal can be classified broadly as either biomimetic or arbitrary. Biomimetic stimulation aims to mimic patterns of natural neural activity, so that the subject immediately experiences the artificial stimulation as if it were natural sensation. Arbitrary stimulation, in contrast, makes no attempt to mimic natural patterns of neural activity. Instead, different stimuli-at different locations and/or in different patterns-are assigned different meanings randomly. The subject's time and effort then are required to learn to interpret different stimuli, a process that engages the brain's inherent plasticity. Here we will examine progress in using artificial stimulation to inject information into the cerebral cortex and discuss the challenges for and the promise of future development.