Artificial intelligence: Historical background, types of tools, and applications for a sustainable future

This chapter attempts to trace the historical evolution of artificial intelligence (AI) through the last few decades, starting from its inception in the 1940s as artificial neurons to recent advancements in deep learning techniques. Then, it discusses the functions and applications of various types of AI tools, including machine learning (ML), neural networks (NNs), and natural language processing (NLP). Some ML methods such as random forest (RF), LightGBM, and XGBoost are discussed in detail. The chapter also examines how AI finds applications in promoting sustainability across diverse sectors such as healthcare, finance, transportation, and environment. In particular, this chapter aims to discuss the developments of AI in the field of environment and sustainability and covers subjects like renewable energy, climate modeling, ecological health monitoring, predictive weather and meteorological modeling, and disaster warning systems. Finally, the trade-off between AI and sustainability in terms of energy demand is discussed.