AI-driven neural implants for vision and hearing: a qualitative study of user perspectives

Area of Science:

• Neuroscience and Biomedical Engineering
• Artificial Intelligence in Healthcare
• Human-Computer Interaction

Background:

• Neural implants, increasingly incorporating AI, aim to restore sensory functions like vision and hearing.
• Current cochlear implants (CIs) struggle with noise, driving AI software development for enhanced sound processing.
• AI-driven cortical visual neural implants (cVNI) are emerging for artificial vision restoration.

Purpose of the Study:

• To explore the perspectives of potential users of AI-driven neural implants for sensory restoration.
• To understand expectations, experiences, perceived risks, and ethical implications of these advanced technologies.
• To inform the ethical analysis and design of future AI-driven neural implants.

Main Methods:

• A qualitative study involving focus groups and interviews with potential users of AI-driven cVNIs and CIs, and users of retinal implants.
• Thematic analysis of transcribed discussions to identify key themes and user perspectives.
• Clustering of perspectives into categories of expectations, experiences, risks, and disadvantages.

Main Results:

• Potential users expressed positive reception towards AI-driven neural implants, particularly for enhanced autonomy.
• Key expectations included improvements over current technologies and greater user control.
• Identified concerns encompassed uncertainty about effectiveness, operational and surgical risks, and media attention.

Conclusions:

• AI-driven neural implants for vision and hearing hold significant promise for improving user autonomy.
• User acceptance is contingent on factors such as device aesthetics and robust user control mechanisms.
• Further research should prioritize user-centered design and address ethical considerations.