Control and Ownership of Neuroprosthetic Speech.

Brain-computer interfaces Control Neuroprosthetics Ownership Responsibility Speech

Journal

Philosophy & technology
ISSN: 2210-5433
Titre abrégé: Philos Technol
Pays: Netherlands
ID NLM: 101583724

Informations de publication

Date de publication:
2021
Historique:
received: 21 01 2019
accepted: 14 11 2019
entrez: 1 11 2021
pubmed: 2 11 2021
medline: 2 11 2021
Statut: ppublish

Résumé

Implantable brain-computer interfaces (BCIs) are being developed to restore speech capacity for those who are unable to speak. Patients with locked-in syndrome or amyotrophic lateral sclerosis could be able to use covert speech - vividly imagining saying something without actual vocalisation - to trigger neural controlled systems capable of synthesising speech. User control has been identified as particularly pressing for this type of BCI. The incorporation of machine learning and statistical language models into the decoding process introduces a contribution to (or 'shaping of') the output that is beyond the user's control. Whilst this type of 'shared control' of BCI action is not unique to speech BCIs, the automated shaping of what a user 'says' has a particularly acute ethical dimension, which may differ from parallel concerns surrounding automation in movement BCIs. This paper provides an analysis of the control afforded to the user of a speech BCI of the sort under development, as well as the relationships between

Identifiants

pubmed: 34722130
doi: 10.1007/s13347-019-00389-0
pii: 389
pmc: PMC8550345
doi:

Types de publication

Journal Article

Langues

eng

Pagination

425-445

Subventions

Organisme : Wellcome Trust
Pays : United Kingdom
Organisme : Wellcome Trust
ID : 104848/Z/14/Z
Pays : United Kingdom

Informations de copyright

© The Author(s) 2020.

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Auteurs

Hannah Maslen (H)

Oxford Uehiro Centre for Practical Ethics, University of Oxford, Suite 8, Littlegate House 16/17 St Ebbe's Street, Oxford, OX1 1PT UK.

Stephen Rainey (S)

Oxford Uehiro Centre for Practical Ethics, University of Oxford, Suite 8, Littlegate House 16/17 St Ebbe's Street, Oxford, OX1 1PT UK.

Classifications MeSH