Barriers to the widespread adoption of diagnostic artificial intelligence for preventing antimicrobial resistance

Area of Science:

• Public Health
• Bioethics
• Health Informatics

Background:

• Antimicrobial resistance (AMR) is a significant global public health threat, exacerbated by antimicrobial overuse.
• Ethical considerations surrounding AMR may impede the integration of advanced technologies like artificial intelligence (AI) into healthcare.
• Understanding public perception is crucial for the successful implementation of AI in combating public health challenges.

Purpose of the Study:

• To investigate the ethical dilemmas influencing the adoption of diagnostic AI in the context of AMR.
• To assess public preferences for different AI approaches in healthcare settings.
• To explore demographic variations in public opinion regarding AI in public health.

Main Methods:

• A web-based survey was conducted across eight countries/regions.
• Participants were presented with two hypothetical AI scenarios: one prioritizing individual health and another addressing the global AMR threat.
• Public preferences, including attitudes towards AI standardization, were analyzed, with attention to gender and age demographics.

Main Results:

• A societal preference emerged for utilizing both individual-focused and global AMR-focused AI types, indicating a complex balance between personal and collective health priorities.
• Significant differences in AI preferences were observed based on gender and age.
• A majority of respondents opposed the standardization of AI in treatment protocols.

Conclusions:

• The integration of AI into public health strategies for AMR faces challenges due to conflicting public sentiments.
• Public acceptance and ethical considerations are paramount for deploying AI effectively in addressing global health issues like AMR.
• Future AI development and implementation must consider diverse public preferences and ethical nuances to ensure successful public health outcomes.