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Can AI Forecasting Stop Wasteful Flood Projects? Scientist Stresses Data's Role

From PhilStar · () English

Translated from English, summarized and contextualized by DistantNews.

At a glance

News Named sources Context piece
  • Scientist Mahar Lagmay questions whether the P1B forecasting model can prevent wasteful flood-control projects.
  • Lagmay emphasizes that despite advancements in AI, effective flood science still relies heavily on accurate and comprehensive data.
  • The article suggests a need for better data collection and utilization to ensure flood-control investments are efficient and impactful.

Scientist Mahar Lagmay is raising questions about the efficacy of the P1B forecasting model in preventing inefficient flood-control projects. While artificial intelligence is gaining attention, Lagmay asserts that the core of successful flood science remains grounded in the quality and availability of data.

Lagmay's perspective suggests that technological solutions, such as AI-powered forecasting, are only as good as the information they process. He implies that without robust, reliable data, even sophisticated models may not lead to optimal decision-making in flood management, potentially resulting in misallocated resources.

The scientist's comments highlight a critical tension: the drive to adopt cutting-edge technology versus the fundamental need for sound scientific principles and data integrity. The article implies that focusing solely on AI might distract from the essential groundwork of data collection and analysis required for effective and sustainable flood-control strategies.

AI gets the spotlight, but flood science still depends on good data.

— Mahar LagmayExplaining the continued importance of data quality in flood forecasting despite AI advancements.
DistantNews Editorial

Originally published by PhilStar in English. Translated, summarized, and contextualized by our editorial team with added local perspective. Read our editorial standards.

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