Evidence map›Paper›PMID 38570593›Full record

ArticleScientific reports2024

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

Odile C van Stuijvenberg, Marike L D Broekman, Samantha E C Wolff, Annelien L Bredenoord, Karin R Jongsma

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
3.0field-weighted citation impact, top 9% of its field
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

5 citing papers in PubMed, 11 citations in OpenAlex.

  1. Article
  2. Review
  3. AI-Powered Microscopic Diagnostic Techniques forJournal of dentistry (Shiraz, Iran) · 2026
    Article
  4. Explainability in AI-enabled medical neurotechnology: a scoping review.Journal of neuroengineering and rehabilitation · 2026
    Article
  5. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 4 institutions in 2 countries.

Odile C van StuijvenbergDepartment of Bioethics and Health Humanities, Julius Center, University Medical Center Utrecht, Utrecht University, 3508 GA, Utrecht, The Netherlands. o.c.vanstuijvenberg-2@umcutrecht.nl.ORCID 0000-0001-7766-6853
Marike L D BroekmanDepartment of Neurosurgery, Haaglanden Medical Center, 2512 VA, The Hague, The Netherlands.
Samantha E C WolffNetherlands Institute for Neuroscience, 1105 BA, Amsterdam, The Netherlands.
Annelien L BredenoordErasmus School of Philosophy, Erasmus University Rotterdam, 3062 PA, Rotterdam, The Netherlands.
Karin R JongsmaDepartment of Bioethics and Health Humanities, Julius Center, University Medical Center Utrecht, Utrecht University, 3508 GA, Utrecht, The Netherlands.
Utrecht University · NLErasmus University Rotterdam · NLLeiden University Medical Center · NLNetherlands Institute for Neuroscience · NL

Funding

Nederlandse Organisatie voor Wetenschappelijk Onderzoek 17619
6 · The paper itself

Abstract

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.

Indexed as

Artificial IntelligenceCochlear ImplantsFocus GroupsQualitative ResearchReproducibility of ResultsAmyotrophic lateral sclerosisBlindnessDeafnessEthicsLocked-in-syndromeNeuromodulation

Identifiers

PMID38570593
PMCPMC10991497
OpenAlexW4393899665

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.