Ethical Artificial Intelligence for Digital Health Organizations

Abstract

This technical report describes the methods undertaken by a US-based Digital Health company (X2AI or X2 for short) to develop an ethical code for startup environments and other organizations delivering emotional artificial intelligence (AI) services, especially for mental health support. With a growing demand worldwide for scalable, affordable, and accessible health care solutions, the use of AI offers tremendous potential to improve emotional wellbeing. To realize this potential, it is imperative that AI service providers prioritize clear and consistent ethical guidelines that align with global considerations regarding user safety and privacy. This report offers a template for an ethical code that can be implemented by other emotional AI services and their affiliates. It includes practical guidelines for integrating support from clients, collaborators, and research partners. It also shows how existing ethical systems can inform the development of AI ethics.

The Sociotechnical Ethics of Digital Health: A Critique and Extension of Approaches From Bioethics

“…The first type of contribution to the bioethics of digital health literature that we identify we refer to as “ applying ethical theory .” In this body of literature, scholars adopt the perspective of an existing ethical theory and assess a subset of normatively relevant issues in digital health from that perspective ( 21 , 26 ). The most common is some form of principlist approach, one that relies on a series of bioethical principles to guide assessment of the ethical implications of any given area of human activity ( 23 , 24 , 27 , 28 ). The field of bioethics is dominated by a principlist approach to ethical thinking ( 20 , 29 ), and it is therefore not surprising that the bioethics of digital health would also be dominated by such an approach.…”

The Ethics of Psychological Artificial Intelligence: Clinical Considerations

“…AI requires regular improvements, or maintenance, driven by clinician‐ and programmer‐informed updates as well as by interactions with individual users and groups (Joerin et al, 2020). Controlled and continuous maintenance enhances the adaptability of the AI service as unique user needs become known and new capabilities become available.…”

Artificial Intelligence Project Success Factors: Moral Decision-Making with Algorithms

“…Access and redress are a way to investigate and correct erroneous decisions. It includes the ability to contest automated decisions, including expressing a point-of-view or requesting human intervention in the decision [1,2,27,37,40,56]. Decision accountability is knowing who is accountable for the actions when decisions are taken by the automated systems in which the algorithms are embedded [2,27,56].…”

“…It includes the ability to contest automated decisions, including expressing a point-of-view or requesting human intervention in the decision [1,2,27,37,40,56]. Decision accountability is knowing who is accountable for the actions when decisions are taken by the automated systems in which the algorithms are embedded [2,27,56]. Equitable treatment means eliminating discrimination and differential treatment, whereby similarly situated people are given similar treatment.…”