Artificial Intelligence for Sustainable Humanitarian Logistics

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Author(s): Ibrahim Opeyemi Oguntola (Dalhousie University, Canada)and M. Ali Ülkü (Dalhousie University, Canada)
Copyright: 2023
Pages: 14
Source title: Encyclopedia of Data Science and Machine Learning
Source Author(s)/Editor(s): John Wang (Montclair State University, USA)
DOI: 10.4018/978-1-7998-9220-5.ch177

Keywords: Data Analysis and Statistics / Information Science Reference / Knowledge Management and Library Science / Machine Learning

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Abstract

Artificial intelligence (AI) can improve operational processes by utilizing faster computational capabilities, data, and innovative algorithms. This article reviews the latest research on the applications of AI technology to sustainable humanitarian logistics (SHL) through the sustainability lens. In a broad sense, the cultural, economic, environmental, and societal pillars of the quadruple bottom line (QBL) are covered. Examples of AI-based logistics and supply chain tools already in use in non-profit, humanitarian organizations are emphasized. The authors then conclude that AI can assist SHL in its goal of saving as many lives as possible during disasters while embracing the QBL pillars. As for all emerging technologies, smoothening the collaboration between humans and AI during operations requires a fundamental change in mindset and culture. Moreover, all stakeholders involved in SHL (e.g., public, government, help organizations, the environment, cultures) are affected. There is therefore room for future research on why, when, where, and how to better utilize AI within SHL contexts.

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