Role of Risks in the Development of Responsible Artificial Intelligence in the Digital Healthcare Domain

Abstract

The use of artificial intelligence (AI) in the healthcare field is gaining popularity. However, it also raises some concerns related to privacy and ethical aspects that require the development of a responsible AI framework. The principle of responsible AI states that artificial intelligence-based systems should be considered a part of composite societal and technological systems. This study attempts to establish whether AI risks in digital healthcare are positively associated with responsible AI. The moderating effect of perceived trust and perceived privacy risks is also examined. The theoretical model was based on perceived risk theory. Perceived risk theory is important in the context of this study, as risks related to uneasiness and uncertainty can be expected in the development of responsible AI due to the volatile nature of intelligent applications. Our research provides some interesting findings which are presented in the discussion section.

Functions of Artificial Intelligence, Income Investment Instrument, and Crypto Money in Era of The Fourth Revolution (ITALIC)

“…The National Association of Securities Dealers Automated Quotations Artificial Intelligence was created to control the performance of companies involved in Artificial Intelligence and robotics, including companies in technology, industry, healthcare, and other business sectors. As a result, these proxies captured the level of innovation in the market and the performance of the sector during the Fourth Industrial Revolution [11]. Well-known investments and safe havens for investors include oil, gold, the CBOE Mood Market Index, and the MSCI Stock Index.…”

Industry 4.0 vs. Industry 5.0: Co-existence, Transition, or a Hybrid

“…Consequently, our study has implications for practice and provides an example of how proof of use can be evaluated in a DSR project. Furthermore, the developed DPs make a novel contribution to the development of both responsible AI (Arrieta et al, 2020;Gupta et al, 2021) and ethical AI (see, e.g., the Montreal Declaration, 2017: montrealdeclaration-responsibleai.com/the-declaration; the Asilomar AI principles: futureoflife.org/ai-principles; Berente et al, 2021;Floridi & Cowls, 2019;Henz, 2021). Regarding the "responsibility" concept, we consider three dimensions: "taking over a responsibility", "being responsible", and "deciding responsibly".…”

Artificial Intelligence Model for Risk Management in Healthcare Institutions: Towards Sustainable Development

“…where the R value is one if there is any term that indicates risk in the sentence and zero otherwise; E, F, M and O refer to environmental, financial, market and operational risks, respectively, such that the value of any of them equals 1 if any term in the text refers to them and 0 otherwise; also e, f, m and o are positive numbers. The process of assessing risks can be shown by the Algorithm 2 as follows: Define a lexicon to determine the type of risk (3) Select the values of e, f, m and o for the four types of risks (4)…”

“…To achieve this not only requires the development of infrastructure and systems, but also needs appropriate management of potential risks [1,2]. Healthcare institutions may face different types of risks, especially those who present their services digitally such as operational risks, financial risks, technological risks, and so on [3]. Hence, identifying, assessing and handling these risks based on advanced techniques, such as artificial intelligence, are an essential step in delivering high quality services for both patients and employers [4][5][6].…”