Open Access Research Article
PROTECTING VULNERABLE POPULATIONS IN AI-DRIVEN HEALTH-TECH
Abstract
In recent years, artificial
intelligence (hereinafter referred to as “AI”) has emerged as a powerful tool
in health technology, promising improvements in diagnostics, personalised
treatment, and system efficiency. However, as AI systems become more embedded
in clinical and public health settings, there is a growing concern that
vulnerable populations, such as the elderly, low-income groups, people with
disabilities, racial and ethnic minorities, and those with limited access to
digital resources, may be disproportionately harmed or left behind. This paper
examines the complex risks faced by these populations when AI-driven health
technologies are deployed without sufficient safeguards. Through a systematic
review of existing frameworks, case studies of AI deployment in health
settings, and verified reports, the study identifies key challenges, including
algorithmic bias, data privacy gaps, limited transparency, unequal access, and
accountability deficits. The results emphasise the extent to which AI health
solutions, in spite of their good intentions, contribute to health inequality.
It is on the basis of this analysis that the paper is able to provide a roadmap
of principles and practical strategies towards the better protection of
vulnerable groups that includes: fairness auditing, inclusive data governance,
participatory data co-design, and regulatory oversight. It is aimed at making
sure that AI in health not only facilitate innovation in medicine, but it also
brings equity, dignity, and justice to everyone.
Published Paper
Author Details
Authors: ABHIGYAA SINGHRegistration ID: 1013613 | Published Paper ID: IJLRA13613Approved ISSN: 2582-6433 | Country: Delhi, India
Article Information
PROTECTING VULNERABLE POPULATIONS IN AI-DRIVEN HEALTH-TECH
Authors: ABHIGYAA SINGH
- Journal IJLRA
- ISSN 2582-6433
- Volume 3
- Issue 8
About Journal
International Journal for Legal Research and Analysis
- AbbreviationIJLRA
- ISSN2582-6433
- AccessOpen Access
- LicenseCC 4.0
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