Australasian Dentist Issue 92

CATEGORY 64 AUSTRALASIAN DENTIST LINICAL Prediction: Legislated responsible AI-ML policy ensure patients, Personalised Health Providers & Dentists are assigned liability Clinical decision support systems (CDSS) were described in a previous article. CDSS are the core technology of many commercial services that offer clinical and technical assistance with diagnosis in pathology, aesthetics and occlusion, interventions in orthodontics, surgery and prosthodontics, and active maintenance. These emerged during the Digital Revolution of the late 20th century 1,2,3,4,5, and more recently 6,7,8,9,10,11 in our current era known as the Fourth Industrial Revolution. Some institutions utilise integrated services which combine generative artificial intelligence, augmented and virtual reality systems to take dental education 12 , technology 10 and surgery 13 to the next level. As Australian Dentists, we can obtain, “expert assistance”, in our own clinics from AI services to improve our patient care and efficiencies in business practices. Regulation of clinical decision support software by the Australian Government Therapeutic Goods Administration 14 (TGA) commenced in 2021: CDSS is software that can perform a broad range of functions that facilitate, support and enable clinical practice. Clinical decision support software that meets the definition of a medical device must be included in the Australian Register of Therapeutic Goods unless otherwise exempt. Currently however, there are no statutory boundaries or policies which guide, limit or restrict when or how we can use these technologies in dentistry. Shared decision making with patients is a recommendation of Australian Government health care advisors 15,16,17 . In 2014, the Australian Government National Lead Clinicians Group reported despite numerous randomised controlled trials, there is poor quality evidence for the effect of CDSS on processes of care and patient outcomes and there is moderate- high quality evidence for the role of patient decision aids in preference-sensitive and shared decision making contexts 15 . Their recommendations for Common­ wealth action comprised: i Develop and implement CDSS standards, and ensure they align with evidence-based guidelines. ii Exercise caution over broader implementation of CDSS until their strengths and weaknesses are better understood. iii Encourage the development and implementation of shared decision- making tools for preference-sensitive decisions. iv Show leadership in the development of provider and consumer awareness and training, which should be developed alongside the tools themselves. In 2017, a similar group of authors noted, shared decision making (SDM) is now firmly established within national clinical standards for accrediting hospitals, day procedure services, public dental services andmedical education inAustralia, with plans to align general practice, aged care and disability service 16 . The Australian Commission on Safety and Quality in Health Care states decision support tools bring together high-quality information about particular conditions. They can be used by consumers and healthcare providers to inform discussions about treatment options, explore the consumer’s preferences and share decision making 17 . Australian Health Practitioner Regulation Agency collaborates with organisations such as the National Health and Medical Research Council, universities and the Digital Health Cooperative Research Centre for research in healthcare regulatory issues such as risk, as well as digital health solutions for patients and enhanced performance feedback for clinicians 18 . Our time in this area is too early for professional indemnity insurance providers to offer any guidance or insights from the Claims experience 19 . The Australian Dental Association’s position statement on the use of artificial intelligence 20 serves as a pioneering conscience for responsible AI and leads our profession of dentistry in the establishment of social and ethical infrastructure of AI in our clinical and educational practices. The ADA Dental Informatics & Digital Health Committee acts as a peak professional body to set policy for ethical and responsible AIML in dentistry, in accordance with safe, equitable and transparent delivery of professional clinical services with patients 21 . It ensures professionals are represented in the disruption, through leadership and policy influence. In 2018, a group from MIT published a report 22,23 of the largest experiment in moral psychology ever: the Moral Machine, an interactive website that has allowed millions of people from 233 countries and territories, to make choices within detailed motor vehicle accident scenarios. Hypothetical passenger and pedestrian demographics included babies, children, and pregnant women. Responses were grouped in accordance with western, eastern and ‘southern’ cultures. Some differences were noted amongst these,whencomparingwhich lives the respondent would save, considering age, gender and socioeconomic factors. A 1996 author 2 described one function of decision support systems as to hold a specialised body of knowledge in computerised form such that the non-specialist can obtain expert-level information. In 2022, the context of specialist compared with non-specialist may also apply to the professional compared with non-professional. Programming of AI/ML systems in diagnosis, planning and interventions of dentistry and health care require safe and efficient operations, and also critical decisions socially and culturally adapted for the community which it is designed Prosthodontics and dentistry 2041 This three-article series provides a brief insight into some predictions which the author believes are relevant for prosthodontics and dentistry over the next twenty years. Part Three. Responsible AI and Social-Ethical Infrastructure By Dr Ken Hooi