BackgroundBrain-Computer Interface (BCI) is a set of technologies that are of increasing interest to researchers. BCI has been proposed as assistive technology for individuals who are non-communicative or paralyzed, such as those with amyotrophic lateral sclerosis or spinal cord injury. The technology has also been suggested for enhancement and entertainment uses, and there are companies currently marketing BCI devices for those purposes (e.g., gaming) as well as health-related purposes (e.g., communication). The unprecedented direct connection created by BCI between human brains and computer hardware raises various ethical, social, and legal challenges that merit further examination and discussion.MethodsTo identify and characterize the key issues associated with BCI use, we performed a scoping review of biomedical ethics literature, analyzing the ethics concerns cited across multiple disciplines, including philosophy and medicine.ResultsBased on this investigation, we report that BCI research and its potential translation to therapeutic intervention generate significant ethical, legal, and social concerns, notably with regards to personhood, stigma, autonomy, privacy, research ethics, safety, responsibility, and justice. Our review of the literature determined, furthermore, that while these issues have been enumerated extensively, few concrete recommendations have been expressed.ConclusionsWe conclude that future research should focus on remedying a lack of practical solutions to the ethical challenges of BCI, alongside the collection of empirical data on the perspectives of the public, BCI users, and BCI researchers.Electronic supplementary materialThe online version of this article (10.1186/s12910-017-0220-y) contains supplementary material, which is available to authorized users.

Since the 1960s, scientists, engineers, and healthcare professionals have developed brain–computer interface (BCI) technologies, connecting the user’s brain activity to communication or motor devices. This new technology has also captured the imagination of publics, industry, and ethicists. Academic ethics has highlighted the ethical challenges of BCIs, although these conclusions often rely on speculative or conceptual methods rather than empirical evidence or public engagement. From a social science or empirical ethics perspective, this tendency could be considered problematic and even technocratic because of its disconnect from publics. In response, our trinational survey (Germany, Canada, and Spain) reports public attitudes toward BCIs ( N = 1,403) on ethical issues that were carefully derived from academic ethics literature. The results show moderately high levels of concern toward agent-related issues (e.g., changing the user’s self) and consequence-related issues (e.g., new forms of hacking). Both facets of concern were higher among respondents who reported as female or as religious, while education, age, own and peer disability, and country of residence were associated with either agent-related or consequence-related concerns. These findings provide a first look at BCI attitudes across three national contexts, suggesting that the language and content of academic BCI ethics may resonate with some publics and their values.

Forms of Artificial Intelligence (AI), like deep learning algorithms and neural networks, are being intensely explored for novel healthcare applications in areas such as imaging and diagnoses, risk analysis, lifestyle management and monitoring, health information management, and virtual health assistance. Expected benefits in these areas are wide-ranging and include increased speed in imaging, greater insight into predictive screening, and decreased healthcare costs and inefficiency. However, AI-based clinical tools also create a host of situations wherein commonly-held values and ethical principles may be challenged. In this short column, we highlight three potentially problematic aspects of AI use in healthcare: (1) dynamic information and consent, (2) transparency and ownership, and (3) privacy and discrimination. We discuss their impact on patient/client, clinician, and health institution values and suggest ways to tackle this impact. We propose that AI-related ethical challenges may represent an opportunity for growth in organizations.

Neural devices now under development stand to interact with and alter the human brain in ways that may challenge standard notions of identity, normality, authority, responsibility, privacy and justice.

Ranging from miniaturized biological robots to organoids, multi-cellular engineered living systems (M-CELS) pose complex ethical and societal challenges. Some of these challenges, such as how to best distribute risks and benefits, are likely to arise in the development of any new technology. Other challenges arise specifically because of the particular characteristics of M-CELS. For example, as an engineered living system becomes increasingly complex, it may provoke societal debate about its moral considerability, perhaps necessitating protection from harm or recognition of positive moral and legal rights, particularly if derived from cells of human origin. The use of emergence-based principles in M-CELS development may also create unique challenges, making the technology difficult to fully control or predict in the laboratory as well as in applied medical or environmental settings. In response to these challenges, we argue that the M-CELS community has an obligation to systematically address the ethical and societal aspects of research and to seek input from and accountability to a broad range of stakeholders and publics. As a newly developing field, M-CELS has a significant opportunity to integrate ethically responsible norms and standards into its research and development practices from the start. With the aim of seizing this opportunity, we identify two general kinds of salient ethical issues arising from M-CELS research, and then present a set of commitments to and strategies for addressing these issues. If adopted, these commitments and strategies would help define M-CELS as not only an innovative field, but also as a model for responsible research and engineering.

Remarkable progress in bioengineering over the past two decades has enabled the formulation of fundamental design principles for a variety of medical and non-medical applications. These advancements have laid the foundation for building multicellular engineered living systems (M-CELS) from biological parts, forming functional modules integrated into living machines. These cognizant design principles for living systems encompass novel genetic circuit manipulation, self-assembly, cell–cell/matrix communication, and artificial tissues/organs enabled through systems biology, bioinformatics, computational biology, genetic engineering, and microfluidics. Here, we introduce design principles and a blueprint for forward production of robust and standardized M-CELS, which may undergo variable reiterations through the classic design-build-test-debug cycle. This Review provides practical and theoretical frameworks to forward-design, control, and optimize novel M-CELS. Potential applications include biopharmaceuticals, bioreactor factories, biofuels, environmental bioremediation, cellular computing, biohybrid digital technology, and experimental investigations into mechanisms of multicellular organisms normally hidden inside the “black box” of living cells.

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Brain-Computer Interface (BCI) research is an interdisciplinary area of study within Neural Engineering. Recent interest in end-user perspectives has led to an intersection with user-centered design (UCD). The goal of user-centered design is to reduce the translational gap between researchers and potential end users. However, while qualitative studies have been conducted with end users of BCI technology, little is known about individual BCI researchers' experience with and attitudes towards UCD. Given the scientific, financial, and ethical imperatives of UCD, we sought to gain a better understanding of practical and principled considerations for researchers who engage with end users. We conducted a qualitative interview case study with neural engineering researchers at a center dedicated to the creation of BCIs. Our analysis generated five themes common across interviews. The thematic analysis shows that participants identify multiple beneficiaries of their work, including other researchers, clinicians working with devices, device end users, and families and caregivers of device users. Participants value experience with device end users, and personal experience is the most meaningful type of interaction. They welcome (or even encourage) end-user input, but are skeptical of limited focus groups and case studies. They also recognize a tension between creating sophisticated devices and developing technology that will meet user needs. Finally, interviewees espouse functional, assistive goals for their technology, but describe uncertainty in what degree of function is "good enough" for individual end users. Based on these results, we offer preliminary recommendations for conducting future UCD studies in BCI and neural engineering.