Artificial intelligence and smile design: An e-Delphi consensus statement of ethical challenges.

PURPOSE: Smile design software increasingly relies on artificial intelligence (AI). However, using AI for smile design raises numerous technical and ethical concerns. This study aimed to evaluate these ethical issues. METHODS: An international consortium of experts specialized in AI, dentistry, and smile design was engaged to emulate and assess the ethical challenges raised by the use of AI for smile design. An e-Delphi protocol was used to seek the agreement of the ITU-WHO group on well-established ethical principles regarding the use of AI (wellness, respect for autonomy, privacy protection, solidarity, governance, equity, diversity, expertise/prudence, accountability/responsibility, sustainability, and transparency). Each principle included examples of ethical challenges that users might encounter when using AI for smile design. RESULTS: On the first round of the e-Delphi exercise, participants agreed that seven items should be considered in smile design (diversity, transparency, wellness, privacy protection, prudence, law and governance, and sustainable development), but the remaining four items (equity, accountability and responsibility, solidarity, and respect of autonomy) were rejected and had to be reformulated. After a second round, participants agreed to all items that should be considered while using AI for smile design. CONCLUSIONS: AI development and deployment for smile design should abide by the ethical principles of wellness, respect for autonomy, privacy protection, solidarity, governance, equity, diversity, expertise/prudence, accountability/responsibility, sustainability, and transparency.

A Comprehensive, Valid, and Reliable Tool to Assess the Degree of Responsibility of Digital Health Solutions That Operate With or Without Artificial Intelligence: 3-Phase Mixed Methods Study.

BACKGROUND: Clinicians' scope of responsibilities is being steadily transformed by digital health solutions that operate with or without artificial intelligence (DAI solutions). Most tools developed to foster ethical practices lack rigor and do not concurrently capture the health, social, economic, and environmental issues that such solutions raise. OBJECTIVE: To support clinical leadership in this field, we aimed to develop a comprehensive, valid, and reliable tool that measures the responsibility of DAI solutions by adapting the multidimensional and already validated Responsible Innovation in Health Tool. METHODS: We conducted a 3-phase mixed methods study. Relying on a scoping review of available tools, phase 1 (concept mapping) led to a preliminary version of the Responsible DAI solutions Assessment Tool. In phase 2, an international 2-round e-Delphi expert panel rated on a 5-level scale the importance, clarity, and appropriateness of the tool's components. In phase 3, a total of 2 raters independently applied the revised tool to a sample of DAI solutions (n=25), interrater reliability was measured, and final minor changes were made to the tool. RESULTS: The mapping process identified a comprehensive set of responsibility premises, screening criteria, and assessment attributes specific to DAI solutions. e-Delphi experts critically assessed these new components and provided comments to increase content validity (n=293), and after round 2, consensus was reached on 85% (22/26) of the items surveyed. Interrater agreement was substantial for a subcriterion and almost perfect for all other criteria and assessment attributes. CONCLUSIONS: The Responsible DAI solutions Assessment Tool offers a comprehensive, valid, and reliable means of assessing the degree of responsibility of DAI solutions in health. As regulation remains limited, this forward-looking tool has the potential to change practice toward more equitable as well as economically and environmentally sustainable digital health care.

Artificial intelligence for sustainable oral healthcare.

OBJECTIVES: Oral health is grounded in the United National (UN) 2030 Agenda for Sustainable Developement and its 17 Goals (SDGs), in particular SDG 3 (Ensure healthy lives and promote well-being for all at all ages). The World Health Organization (WHO) Global Strategy on Oral Health calls for prioritizing environmentally sustainable and less invasive oral health care, and planetary health. Artificial Intelligence (AI) has the potential to power the next generation of oral health services and care, however its relationship with the broader UN and WHO concepts of sustainability remains poorly defined and articulated. We review the double-edged relationships between AI and oral health, to suggest actions that promote a sustainable deployment of AI for oral health. DATA: Concepts regarding AI, sustainability and sustainable development were identified and defined. A review of several double-edged relationship between AI and SDGs were exposed for the field of Oral Health. SOURCES: Medline and international declarations of the WHO, the UN and the World Dental Federation (FDI) were screened. STUDY SELECTION: One the one hand, AI may reduce transportation, optimize care delivery (SDG 3 "Good Health and Well-Being", SDG 13 "Climate Action"), and increase accessibility of services and reduce inequality (SDG 10 "Reduced Inequalities", SDG 4 "Quality Education"). On the other hand, the deployment, implementation and maintenance of AI require significant resources (SDG 12 "Responsible Consumption and Production"), and costs for AI may aggravate inequalities. Also, AI may be biased, reinforcing inequalities (SDG 10) and discrimination (SDG 5), and may violate principles of security, privacy and confidentiality of personal information (SDG 16). CONCLUSIONS: Systematic assessment of the positive impact and adverse effects of AI on sustainable oral health may help to foster the former and curb the latter based on evidence. CLINICAL SIGNIFICANCE: If sustainability imperatives are actively taken into consideration, the community of oral health professionals should then employ AI for improving effectiveness, efficiency, and safety of oral healthcare; strengthen oral health surveillance; foster education and accessibility of care; ensure fairness, transparency and governance of AI for oral health; develop legislation and infrastructure to expand the use of digital health technologies including AI.

Information and Communication Technology Use in Suicide Prevention: Scoping Review.

BACKGROUND: The use of information and communication technology (ICT) in suicide prevention has progressed rapidly over the past decade. ICT plays a major role in suicide prevention, but research on best and promising practices has been slow. OBJECTIVE: This paper aims to explore the existing literature on ICT use in suicide prevention to answer the following question: what are the best and most promising ICT practices for suicide prevention? METHODS: A scoping search was conducted using the following databases: PubMed, PsycINFO, Sociological Abstracts, and IEEE Xplore. These databases were searched for articles published between January 1, 2013, and December 31, 2018. The five stages of the scoping review process were as follows: identifying research questions; targeting relevant studies; selecting studies; charting data; and collating, summarizing, and reporting the results. The World Health Organization suicide prevention model was used according to the continuum of universal, selective, and indicated prevention. RESULTS: Of the 3848 studies identified, 115 (2.99%) were selected. Of these, 10 regarded the use of ICT in universal suicide prevention, 53 referred to the use of ICT in selective suicide prevention, and 52 dealt with the use of ICT in indicated suicide prevention. CONCLUSIONS: The use of ICT plays a major role in suicide prevention, and many promising programs were identified through this scoping review. However, large-scale evaluation studies are needed to further examine the effectiveness of these programs and strategies. In addition, safety and ethics protocols for ICT-based interventions are recommended.

Évaluer les besoins des femmes enceintes : une étude-pilote du dispositif Ariane.

INTRODUCTION: The organization of perinatal prevention in France is based on a system of universalism. Maternal and child protection services are thus open to all, at the risk of excluding people who do not know where or how to find them. Targeted preventive corrective measures, based on risk factors, correct some of this inequity but create other negative effects. PURPOSE OF RESEARCH: This article presents an innovative social protocol in public health: the Ariane systematic prenatal contact. It is based on the principle of proportionate universalism. Ariane consists of a text message and a phone call at the beginning of pregnancy. Aimed at all pregnant women, it allows information to be transmitted orally on public systems of prevention and support for parents. It also makes it possible to assess the needs of families, along eight axes. METHOD: This article presents the results of the pilot study of this system, conducted in Moselle. In total, 14 midwiwes ant 11 parturients who were contacted during their pregnancy participated in post-project interviews. RESULTS: The results show a very high level of acceptability of the calls by all parties. According to the midwives, Ariane has made it possible to increase the relevance of the identification, making it possible to move from a prevention logic based on criteria to a prevention logic based on the needs of families. The contact was easy, according to both the women and the clinicians. CONCLUSION: Our results show that the Ariane protocol make possible to establish a relationship of trust between the families and the services. Implications for outreach policies are also presented in this article.

The Darknet and suicide.

CONTEXT: The Internet contains both public content ("Surface Web"), and private content ("Deep Web") sometimes hosted on exclusive networks ("Darknets") only accessible using dedicated software such as TOR (The Onion Router). This software makes it almost impossible to identify its users. Information media have reported on suicide-related aspects of Darknets, for example when poisons that can be used to kill oneself are offered for sale (Le Garff et al., 2016) when users discuss ways to kill oneself in anonymous forums (Ferrara, 2016; Franceschi-Bicchierai, 2015) and suicides that follow bullying or "doxing" (online divulgation without consent of intimate personal information) (Bartlett, 2015). Several recent studies have analyzed the nature of suicide content on the Surface Web, but to date, there have been no systematic investigations of suicidal content available on Darknets. OBJECTIVES: The object was to document the nature and accessibility of suicide-related information available on the TOR Darknet or via the TOR software. METHODS: We replicated the methodology used by Biddle et al. (2008, 2016) in their studies of the Surface Web, using TOR on the Darknet. We identified and chose nine search engines used on the TOR Darknet: TORCH the TOR search engine, Notevil, Ahmia, Candle, Hidden Wiki, Darknet (onion.link), Duckduckgo and Grams. Two research assistants independently coded the first 30 results of searches using the keywords, "suicide" and "suicide methods". RESULTS: There were 476 "hits" in the search for "suicide" and "suicide method" using TOR, with fewer sites dedicated to suicide (4%), compared to the Surface Web (23.1%) (Biddle et al., 2016). Over half of the sites proposed by the TOR search engines (252, 52.9%) were outdated, inaccessible or not containing content pertinent to suicide or suicide methods. Several of the TOR search engines provided access to forums ("chat boards") where suicide was a topic (70, 14.8%). These were usually pro-suicide, are blocked or filtered by most of the Surface Web engines (e.g. Google). DISCUSSION: Persons concerned with suicide prevention should conduct further investigations of pro-suicide forums that are accessible using TOR and their users, comparing them with the Surface Web. New strategies to prevent suicide may need to be developed for Darknets.