Ethics of Generating Synthetic MRI Vocal Tract Views from the Face

TL;DR

This paper investigates the ethical implications of using AI to generate MRI images of the oral cavity from facial data, highlighting privacy concerns and demonstrating a preliminary generative approach with Pix2PixGAN.

Contribution

It introduces the concept of external-to-internal correlation modeling (E2ICM) for cost-effective MRI generation and discusses associated ethical issues.

Findings

Feasibility of generating pseudo-MRI views from facial data using Pix2PixGAN

Discussion of privacy and consent concerns in AI-generated medical imaging

Preliminary validation of E2ICM approach

Abstract

Forming oral models capable of understanding the complete dynamics of the oral cavity is vital across research areas such as speech correction, designing foods for the aging population, and dentistry. Magnetic resonance imaging (MRI) technologies, capable of capturing oral data essential for creating such detailed representations, offer a powerful tool for illustrating articulatory dynamics. However, its real-time application is hindered by expense and expertise requirements. Ever advancing generative AI approaches present themselves as a way to address this barrier by leveraging multi-modal approaches for generating pseudo-MRI views. Nonetheless, this immediately sparks ethical concerns regarding the utilisation of a technology with the capability to produce MRIs from facial observations. This paper explores the ethical implications of external-to-internal correlation modeling (E2ICM). E2ICM utilises facial movements to infer internal configurations and provides a cost-effective supporting technology for MRI. In this preliminary work, we employ Pix2PixGAN to generate pseudo-MRI views from external articulatory data, demonstrating the feasibility of this approach. Ethical considerations concerning privacy, consent, and potential misuse, which are fundamental to our examination of this innovative methodology, are discussed as a result of this experimentation.