- Public confidence in AI weather forecasts is far lower than for numerical and physics-based methods
- Just 11% said they were “very confident” in machine learning weather prediction, compared with 30% for tried-and-trusted methods
- The Met Office has been using machine learning techniques in weather forecasting for some years
A survey of 6,000 UK adults has found that the majority don’t fully trust the idea of AI weather forecasts. While machine learning techniques have been a factor of weather forecasting for some years, the survey found that people are more relaxed about traditional Numerical Weather Prediction (NWP) as opposed to Machine Learning Weather Prediction (MLWP).
Predictive technology has increased considerably thanks to AI, and the Met Office has already begun to evaluate AI models for augmenting its existing forecasting methods.
However, the “confidence gap” in the results of the survey, which appears to be based around questions over accuracy, could undermine the use of AI for weather forecasting, which researchers suggest can be challenged with clear demonstrations of the methods working successfully.
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AI-based weather models
The Met Office research was published in a study, Artificial Intelligence for the Earth Systems, which explores the public’s confidence in the reliability of AI-based weather forecasting and prediction. Future studies are planned to assess how attitudes change toward AI-backed weather reports.
Responses to the report are not entirely negative. While 87.7% of respondents felt confident about weather reports using NWP, the 49.4% in favour of MLWP isn’t a bad result. Rather, it demonstrates that people are comfortable with tried-and-tested methods.
Dr Edward Pope, a Met Office Science Fellow and the lead author of the paper, said the report, “deepens our understanding of current public perceptions as we approach a crucial juncture where AI-based weather models are demonstrating their potential to work alongside physics-based methods. This was a unique opportunity to compare public perceptions of established and emerging approaches to forecasting the weather.”
The consequences of the “confidence gap”
The gap in confidence between the maths-based predictive forecasting and modern AI modelling is a challenge that the Met Office is addressing directly.
Dr Pope explained that “The gap in confidence and perceived accuracy highlighted in the paper demonstrates the need to clearly and transparently demonstrate the value of new approaches in ways that matter to people.”
In Pope’s view, AI practices will contribute to weather forecasts in the future, “but these improvements will only be fully realised if the public continue to have confidence, and importantly act on, the weather forecast they see.”
The Met Office research considered the “perceived accuracy” of reports, and its Chief AI Officer Professor Kirstine Dale implied that progress with AI weather modelling is subjected to evaluation and validation: “We are exploring ways of blending physics-based and AI-based modelling to deliver the forecasts that we all rely on. As with all science developments, we will robustly evaluate and validate any changes to our approach to weather forecasting before we introduce them into the model.”
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