Navigating Complexities Through Unveiling Sustainability Challenges in AI Using a Bibliometric Approach

Literature Review

There is a general trend that the most recent technological advancements, specifically machine learning (ML) and artificial intelligence (AI), are also being applied more and more to sustainability problems and the global climate crisis. (Allen et al., 2020), Artificial intelligence (AI) has undergone extensive development. It has affected nearly every facet of human existence and enabled previously unheard-of advancements in the fields of engineering, sustainability, communication, and medicine, among others. AI has the potential to drastically alter our world. AI offers opportunities to complement and supplement human intelligence and enhance the way people live and work. These advancements are coupled with advances in data collection and aggregation, analytics, and computer processing power (Intelligence, 2018). AI systems can improve people's ability to learn new skills, democratize access to services, design and deliver products more quickly, iterate cycles more quickly, use less energy, monitor the environment in real time for pollution and air quality, strengthen cybersecurity defences, decrease inefficiencies in the healthcare system, develop new types of leisure activities, and enhance real-time translation services that link people worldwide. Given the broad applications and effects of AI, a number of national governments have chosen to encourage and control the adoption of AI across a range of industries (Baum et al., 2023).