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

Neural implants are being developed to treat various conditions, including sensory impairments such as blindness and deafness. In these technologies there is a growing role for artificial intelligence (AI) to enable interpretation of complex data input. Current users of cochlear implants (CIs) face challenges in noisy environments, prompting the development of AI-driven software for personalized and context-aware noise suppression and speech enhancement. For blindness, an AI-driven cortical visual neural implant (cVNI) for artificial visual perception is under development. Here, AI-driven software may be used to process camera imaging for interfacing with the brain. If successful, these devices can offer important advantages for their users yet may also have ethical implications. Perspectives of (potential) users of these technologies is an important source for ethical analysis, yet so far these have not been explored in-depth. We performed a focus-group and interview study including potential users of a) the AI-driven cVNI (<i>n</i> = 5) and of b) the AI-driven CI (<i>n</i> = 3), and c) current or (former) users or a retinal implant (<i>n</i> = 3). Focus groups and interviews were transcribed and analyzed thematically. Perspectives were clustered under 1) expectations and experiences, including improvements from the status quo, enhancement of autonomy and design requirements, and 2) perceived risks and anticipated disadvantages, including uncertainty on effectiveness, operational risks, surgical risks, and media attention. AI-driven neural implants for vision and hearing were positively received by potential users due to their potential to improve autonomy. Yet, possible conditions for uptake were identified, including device aesthetics and sufficient levels of user-control.