What are the limits of machine learning in emergencies?

What are the main limitations of using machine learning during emergencies?

Machine learning can struggle with data quality, real-time processing, and ethical considerations in emergencies.

Can machine learning algorithms adapt quickly to changing situations in a crisis?

While some algorithms can adapt, they often require extensive training on relevant data, which may not be available in real-time.

How does data bias affect machine learning in emergency responses?

Data bias can lead to ineffective or harmful decisions, as algorithms may not accurately represent all affected populations.

Are there any successful examples of machine learning in emergency management?

Yes, machine learning has been used in disaster response for predicting floods and optimizing resource allocation.

What ethical concerns should we consider when using AI in emergencies?

Ethical concerns include privacy issues, accountability for decisions made by AI, and the potential for exacerbating inequalities.