Artificial intelligence vs COVID-19: limitations, constraints and pitfalls

Area of Science:

• Medical Informatics
• Public Health
• Artificial Intelligence

Background:

• The COVID-19 pandemic highlighted the potential of Artificial Intelligence (AI) in healthcare.
• Early applications of AI were explored to combat the virus and its effects.

Purpose of the Study:

• To conduct an early evaluation of Artificial Intelligence (AI) applications against COVID-19.
• To identify key areas for AI contribution and assess its current impact.

Main Methods:

• Literature review and analysis of existing AI applications in the context of COVID-19.
• Discussion of challenges and limitations in AI implementation for pandemic response.

Main Results:

• AI has not yet demonstrated significant impact in the fight against COVID-19.
• Key challenges include both data scarcity and data overload, alongside privacy concerns.
• Effective human-AI interaction is critical for successful implementation.

Conclusions:

• Current AI applications are unlikely to significantly aid the ongoing COVID-19 pandemic.
• Future pandemic preparedness requires robust data collection strategies and a balance between data privacy and public health needs.
• Developing effective human-AI collaboration is essential for leveraging AI in future health crises.