Evidence map›Paper›PMID 31674917›Full record

ArticleJournal of medical Internet research2019

The Ethical and Responsible Development and Application of Advanced Brain Machine Interfaces.

Andrew David Maynard, Marissa Scragg

Abstract readComment
In one paragraph

Article in Journal of medical Internet research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

  1. Ethical Precision in Nanoscale Brain Interfacing.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Article
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  4. Review
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

Andrew David Maynard *School for the Future of Innovation in Society, Arizona State University, Tempe, AZ, United States.ORCID 0000-0003-2117-5128
Marissa Scragg *School for the Future of Innovation in Society, Arizona State University, Tempe, AZ, United States.ORCID 0000-0002-9090-8949

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Advanced brain machine interfaces provide potentially transformative approaches to treating neurological conditions and enhancing the performance of users. Yet, as technological capabilities continue to progress in leaps and bounds, there is a possibility that these capabilities outstrip our collective understanding of how to ensure brain machine interfaces are developed and used ethically and responsibly. In this case, there is an overt danger of rapid technological developments leading to unanticipated harm through a lack of foresight including threats to privacy, autonomy, self-identity, and other areas of personal and social value which, while hard to quantify, represent substantial risks. There is also a very real likelihood of such risks undermining value creation around the technologies and the associated enterprises, as key stakeholders push back against perceived and actual threats to what they, in turn, hold to be of value. In order to successfully traverse the resulting risk landscape, researchers and developers will need to become increasingly adept at integrating a sophisticated understanding of ethical and socially responsible innovation into their enterprises. Here, we illustrate how a "risk innovation" approach may provide novel insights into mapping out this landscape and revealing potentially blindsiding risks. We show how this approach can be used to illuminate challenges and opportunities to the successful, ethical, and responsible development of advanced brain machine interfaces. In addition, we emphasize how success will ultimately depend on the willingness of innovators and others to take ethical and responsible innovation seriously and to draw on the interdisciplinary and transdisciplinary expertise that is necessary to translate good intentions into positive outcomes.

Indexed as

Brain-Computer InterfacesHumansPrivacyResearch PersonnelTechnologybioethicsbrain machine interfaceethical innovationethicsneuroethicsresponsible innovationriskrisk innovation

Identifiers

PMID31674917
PMCPMC7351257

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.