Towards an Intelligent Tomorrow: Machine Learning Enabling Sustainable Development

Introduction

Sustainable development is an eminent challenge of our era, presenting a pivotal crossroad for the global community grappling with multifaceted issues such as climate change, resource depletion, social inequality, and environmental degradation (Nguyen et al., 2023). The global spotlight has converged on adopting and pursuing the SDGs, established by the United Nations in 2015 as a universal call to action (Erin et al., 2022). These goals, a critical roadmap for our future, ambitiously aim to end poverty, protect the planet, and ensure prosperity for all by 2030 (Vinuesa et al., 2020). Undoubtedly, the significance of the SDGs in the contemporary world cannot be overstated. Serving as a comprehensive framework transcending borders, they address challenges affecting nations at every level of development, embodying a commitment to leaving no one behind and recognizing the inherent interconnectedness of our global community. For instance, in environmental conservation, sustainable development promotes practices that minimize environmental impact, such as renewable energy use, waste reduction, and protection of ecosystems (Acaru et al., 2023; Hashemi-Amiri et al., 2023; Kalinaki, Malik, Lai, et al., 2023). Moreover, in ensuring economic stability, sustainable development aims for economic growth that is inclusive, resilient, and environmentally responsible, fostering long-term stability (Erin et al., 2022). Furthermore, sustainable development focuses on social inclusion and equity, aiming to reduce poverty, improve education, and enhance healthcare, among other things (Vinuesa et al., 2020). SDGs represent a shared vision for a more equitable and sustainable world (Nunkoo et al., 2023). The urgency of this international endeavor is underscored by a mounting body of evidence suggesting severe and far-reaching consequences of inaction, particularly in the face of climate change (Nunkoo et al., 2023). Figure 1 depicts the 17 sustainable goals.

Figure 1.

Sustainable Development Goals

While the SDGs provide a well-defined blueprint for a better future, translating these aspirations into reality proves formidable. Conventional approaches, rooted in incremental change and siloed sectors, often fail to address the complexity of contemporary global challenges (Balogun et al., 2020). The failure of conventional methods is attributed to factors such as the inability to deal with the interconnectedness of environmental, social, and economic issues (Huo & Peng, 2023; L. Zhang et al., 2021). Moreover, globalization has increased interconnectedness and exacerbated inequalities among nations and communities. Conventional developmental strategies may fail to effectively mitigate worldwide inequities, leading to disparate access to resources and opportunities (Gray Group International, 2023). Furthermore, traditional economic models often prioritize short-term gains and fail to account for long-term environmental and social impacts (Purvis et al., 2019). Also, Traditional development methods have often relied on the unsustainable use of natural resources, leading to depletion and environmental degradation (Yusuf & Lytras, 2023). This can have long-term consequences for ecosystems, biodiversity, and the planet's health.