Government Accounting Office (GAO) found that machine learning, a type of artificial intelligence (AI) that uses algorithms to identify patterns in information, is being applied to forecasting models for natural hazards—such as severe storms, hurricanes, floods, and wildfires—that can lead to natural disasters. A goal is to improve the warning time for severe storms.

 GAO identified potential benefits of applying machine learning to weather forecasting, including:

• Reducing the time required to make forecasts.
• Increasing model accuracy.
• Reducing the uncertainty of model output.

Forecasting natural disasters using machine learning GAO also identified challenges to the use of machine learning. For example:

1. Data limitations hamper the training of machine learning models and can reduce accuracy
2. A lack of trust and understanding of the algorithms as well as concerns about bias
3. Limited coordination and collaboration create challenges for fully developing some machine learning models.
4. Workforce and resource gaps also create challenges.

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Teaching Suggestions:

• Make a list of potential benefits of machine learning to weather forecasting in relation to insurance costs.
• Make a list of potential dangers using machine learning in forecasting natural disasters in relation to insurance costs.

Discussion Questions:

1. Do you believe that insurance premiums should be calculated based upon forecasting models for natural hazards. such as severe storms, hurricanes, floods, and wild fires? 
2. What are some challenges to the use of machine learning in forecasting natural disasters?