Ethical Implications of Using Digital Twins to Treat Autism

Abstract

Digital twins create digital simulations that allow testing and optimization of systems.  Recent enhancements in artificial intelligence (AI) now allow digital twin applications across many fields, including healthcare. Currently, the ethics of their use, while not completely unexplored, are rather underdeveloped. On the topic of developing a digital twin for autism spectrum disorder (ASD), specific ethical guidelines currently do not exist. Here, basic ethical considerations and guidelines are identified through a targeted literature review. These topics include those covered by laws and those that are not. The basic needs of the patient must be met by enabling informed consent, by giving proper information and reasoning, and promoting autonomy by taking patient desires into account. ASD makes this more difficult because of unique communication styles, different ways of processing information, and common biases that individuals with ASD are not capable of deciding what is best for them. This is exacerbated because many patients are underage, leaving parents responsible for treatment and needing adequate information. As well, patient data must be very well protected, as if it is compromised it can lead to adverse patient outcomes. Data is also much harder to use since much of it is children’s data. To prevent discrimination against those with ASD, proper goals must be set, while not assuming innate limitations of any given patient. This is especially important in the context of ASD because many treatments that aim to make patients appear normal lead to long-term mental health harm. Ethical testing is important to mitigate unneeded risk. These ethical standards are critical to prevent harm when developing ASD digital twin technologies.