Ethics of AI in Healthcare: Discussing the Ethical Implications and Biases in AI Algorithms Used in Medical Settings

EasyChair Preprint 15120

Abstract

As artificial intelligence (AI) increasingly permeates healthcare, understanding its ethical implications and biases becomes paramount. This abstract explores the ethical considerations surrounding AI algorithms employed in medical settings, highlighting key areas of concern, including data privacy, informed consent, and accountability. The deployment of AI in diagnostics, treatment recommendations, and patient management raises questions about transparency and the potential for algorithmic bias, which can disproportionately affect marginalized populations. Moreover, the reliance on historical data for training AI systems may perpetuate existing disparities in healthcare outcomes. This discussion emphasizes the need for robust ethical frameworks and guidelines to ensure that AI technologies are developed and implemented responsibly, promoting fairness, accountability, and patient trust. By addressing these ethical challenges, the healthcare industry can harness the transformative potential of AI while safeguarding the rights and well-being of patients. This exploration underscores the importance of collaboration among stakeholders—including technologists, clinicians, ethicists, and patients—to create a more equitable and ethical healthcare landscape.

Keyphrases: Bias in AI Algorithms, Healthcare Disparities, algorithmic fairness, data privacy, ethical implications

@booklet{EasyChair:15120,
  author    = {Adeyeye Barnabas},
  title     = {Ethics of AI in Healthcare: Discussing the Ethical Implications and Biases in AI Algorithms Used in Medical Settings},
  howpublished = {EasyChair Preprint 15120},
  year      = {EasyChair, 2024}}