Explainable artificial intelligence-based approaches for climate change: a review


Barutcu H. C., Çelik S., Gezer M.

INTERNATIONAL JOURNAL OF GLOBAL WARMING, cilt.35, sa.2-4, ss.244-260, 2025 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Derleme
  • Cilt numarası: 35 Sayı: 2-4
  • Basım Tarihi: 2025
  • Doi Numarası: 10.1504/ijgw.2025.145102
  • Dergi Adı: INTERNATIONAL JOURNAL OF GLOBAL WARMING
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, CAB Abstracts, INSPEC, Veterinary Science Database, Civil Engineering Abstracts
  • Sayfa Sayıları: ss.244-260
  • Anahtar Kelimeler: artificial intelligence, climate change, explainable artificial intelligence, XAI
  • İstanbul Üniversitesi Adresli: Evet

Özet

Climate change is a significant problem that requires urgent action to identify and mitigate its causes. While artificial intelligence (AI) algorithms offer a promising tool to identify these causes, 'black box' constructs often obscure the meaning and impact of essential elements. At this point, explainable artificial intelligence (XAI), which illuminates algorithms and allows understanding of which factors significantly affect climate change, can be a saviour. This study focuses on applying XAI to reveal the factors affecting climate change, starting with identifying the areas that AI technologies can affect based on the existing literature. The pros and cons of artificial intelligence are discussed before delving into the concept of XAI and its potential in climate change research. This research aimed to clarify how AI can be effectively leveraged to address the complexities of climate change through XAI, highlighting the role of XAI in making AI insights into climate change understandable and actionable.