ETHICS AND LEGAL DIMENSIONS OF ARTIFICIAL INTELLIGENCE IN HEALTHCARE: TECHNICAL, BUSINESS, AND EDUCATIONAL PERSPECTIVES

Abstract

AI is making significant progress in the medical industry, enabling advanced diagnostics, forecasting, personalized healthcare services, and operational excellence. However, AI devices are causing issues with ethical and legal concerns: bias in algorithms, lack of transparency, data privacy breaches (including fraudulent claims), and unclear accountability. This research is focused on the ethical and legal considerations of AI in health care, technical, business (and even education). The research is based on a thorough study of the literature and reviewing 120 peer-reviewed articles, regulatory directives and industry reports in order to gain insight on the main issues and propose ways to work around them. Additionally, the primary resulting discoveries provide that 38 percent of AI healthcare models expand beyond the natural algorithmic bias and 45 percent or more of analyzed systems have no degree of explanation, resulting in the need for the concept of explainable AI and implementation of steps needed to ensure the neutrality of algorithms.

The absence of any structured A.I. governance framework in 56 percent of healthcare institution mentions possible need for better compliance formulations, risk management and stakeholder initiatives. Upon learning that only two out of three health-workers have a full-fledged grasp of AI ethics and regulations, the educational research community found itself at the Crossroads of increased need and adoption of training and curriculum development program.

Besides technical solutions, cross perspective evaluation reveals policies and teaching activities in organisations which may enhance ethical and legal standards. The inquiry extends the reasoning promoted by developers, policymakers, and educators to ensure that AI work well with responsibility, safety, ethics; hence, building trust and equity that ultimately would lead to superior patient outcomes.