Artificial intelligence (AI) or augmented intelligence? How big data and AI are transforming healthcare: Challenges...

Area of Science:

• Medical Ethics
• Health Informatics
• Artificial Intelligence in Healthcare

Background:

• The traditional doctor-patient relationship is challenged by big data and artificial intelligence (AI).
• Transition to electronic health records, wearables, and mobile health apps enables massive data collection.
• AI systems, powered by complex neural networks, are increasingly integrated into healthcare.

Purpose of the Study:

• To examine the ethical, legal, and social challenges posed by AI and big data in healthcare.
• To highlight the need for context-specific governance frameworks, especially in low- and middle-income countries.
• To address the potential for AI to exacerbate global health inequities.

Main Methods:

• Review of current trends in healthcare data collection and AI implementation.
• Analysis of existing and emerging global guidelines for AI governance.
• Examination of legal and ethical implications of AI and robotics in medical practice.

Main Results:

• AI and big data present significant ethical, legal, and social challenges in healthcare.
• Global AI governance guidelines are emerging, but many nations lack specific frameworks.
• The digital divide risks widening health disparities between high- and low-income countries.

Conclusions:

• Urgent development of legislation is needed to address liability and accountability for AI and robotics in healthcare.
• Context-specific frameworks are crucial for equitable AI implementation globally.
• Addressing the digital divide is essential to prevent AI from exacerbating health inequities.