Can artificial intelligence mitigate environmental inequality? Evidence from leading robotic-driven economies using quantile-based methods

Objective: to identify the hidden ecological costs associated with the elaboration, implementation and development of artificial intelligence technologies, in order to ensure its sustainable and harmonious integration with various economic sectors by identifying optimal moral-ethical and political-legal strategies.Methods: the conducted research is based on an ecological approach to the development and implementation of artificial intelligence, as well as on an interdisciplinary and political-legal analysis of ecological problems and risks of algorithmic bias, errors in artificial intelligence algorithms and decision-making processes that may exacerbate environmental inequalities and injustice towards the environment. In addition, analysis was performed in regard to the consequences of natural ecosystems destruction caused by the development of artificial intelligence technologies due to the computing energy-intensiveness, the growing impact of data centers on energy consumption and problems with their cooling, the electronic waste formation due to the rapid improvement of equipment, etc.Results: the analysis shows a range of environmental, ethical and political-legal issues associated with the training, use and development of artificial intelligence, which consumes a significant amount of energy (mainly from non-renewable sources). This leads to an increase in carbon emissions and creates obstacles to further sustainable ecological development. Improper disposal of artificial intelligence equipment exacerbates the problem of e-waste and pollution of the planet, further damaging the environment. Errors in artificial intelligence algorithms and decision-making processes lead to environmental injustice and inequality. AI technologies may disrupt natural ecosystems, jeopardizing wildlife habitats and migration patterns.Scientific novelty: the environmental consequences of the artificial intelligence use and further development, as well as the resulting environmental violations and costs of sustainable development, were studied. This leads to the scientific search for optimal strategies to minimize environmental damage, in which legal scholars and lawyers will have to determine ethical-legal and political-legal solutions at the national and supranational levels.Practical significance: understanding the environmental impact of AI is crucial for policy makers, lawyers, researchers, and industry experts in developing strategies to minimize environmental harm. The findings emphasize the importance of implementing energy efficient algorithms, switching to renewable energy sources, adopting responsible e-waste management practices, ensuring fairness in AI decision-making and taking into account ethical considerations and rules of its implementation.

Climate change has been found to disproportionately affect rural communities across Africa, which, as a result, deepens existing socio-economic and environmental inequalities. As global efforts shift towards Artificial Intelligence (AI)-driven solutions to enhance climate resilience and adaptation, recent scholarship highlights their potential, such as predictive modeling, resource management, and disaster response. However, applying these solutions in African rural contexts, characterized by limited access to technology, infrastructure, and resources, remains a challenge. This challenge becomes more alarming when considering the human and social dimensions of climate vulnerability, where current AI-driven approaches often fail to engage with the lived realities, traditional knowledge systems, and unique challenges of rural populations.To address these gaps, this paper adopts a Complementary Framework that views AI and Indigenous Knowledge Systems not as opposing forces, but rather, as mutual which could coexist for productive outcomes. It does these shortcomings by critically evaluating the integration of AI-driven solutions into rural African settings. It emphasises the need for inclusivity and the recognition of indigenous knowledge and approaches through the use of machine learning. Hence, by identifying systemic barriers; technological, social, and cultural, that hinder effective implementation, the paper calls for a shift away from a purely techno-centric paradigm, arguing for a more inclusive and participatory model that considers the voices, needs, expertise, and overall reality of Africa’s vulnerable rural communities.

Despite urban economic growth and significant efforts to introduce «green» initiatives and a comfortable urban environment, most modern cities are becoming more unfriendly to people, and urban ecosystems are facing various problems. Industrialisation has provoked a global environmental crisis. It is obvious that fundamentally new and innovative approaches are needed to solve environmental problems of post-industrial agglomerations. The study analyses several cases such as the use of innovative photocatalysis technology, the isotope ratio method and satellite images to identify pollution of urban landscapes, the use of digital twins and artificial intelligence as part of the global concept of a smart city. Innovative technologies are poorly understood, the potential harm from their use can greatly exceed the visible benefits, in addition, they do not solve the pressing problems of cities. The emerging smart and technological city reproduces actual and perceived urban inequalities; affluent residential areas and new economy class spaces are becoming «smart», but most of the city is left behind. Moreover, on a global scale, it is clear that environmental inequality will only increase.

Digital technologies such as sensors, blockchain, and artificial intelligence are increasingly being used in global food production and consumption, including in urban contexts through the notion of the “smart city”. Food governance is addressed through logics of efficiency in supply chains, increasing profits for shareholders of large companies but doing little to address unsustainable social and environmental inequalities. Human–computer interaction (HCI) designers and researchers are increasingly interested in algorithmic governance of smart cities, raising concerns around issues of control, agency, access, and benefit. Against these concerns, some HCI researchers have also started to question a human-centred perspective to designing socio-technical systems, drawing on more-than-human perspectives to consider the interrelations and interdependencies between human and non-human others within the food web. In this chapter, these emerging perspectives within HCI are drawn together to consider the ways in which new technologies such as blockchain can be used in urban food governance. A case study of co-designing futures of algorithmic food governance with grassroots urban communities that account for multispecies actors, labours, and relationships is presented. The project surfaces new possibilities for computation to intervene in urban food governance in ways that are more sustainable and fairer.

The article considers new forms of social inequality, interest in which emerged mainly in the late twentieth and early twenty-first century. Special attention is paid to the analysis of global, digital and environmental inequality. The reasons of sociological interest to these problems are considered, the most important of which are the technological progress, changes in the ways of assessing the level of social inequality, as well as the transformation of research optics and tools of cognition, including the emergence of artificial intelligence technologies.The main characteristics of the new forms of social inequality, their interrelation, levels and measurement criteria are presented. The article describes several perspectives of studying global social inequality. In sociological literature, most of them are related to the transition from the study of the nation-state as a key unit of analysis to the study of global social space. The analysis of digital inequality and the problem of the social divide now appears as a combination of several levels of research and is related to the consideration of access to technology, possession of digital skills, and the life chances and opportunities. Environmental pollution and climate change have led to research interest in socio-environmental inequalities, which are related to the unequal distribution of environmental risks. Environmental neo-colonialism is examined in the context of analyzing environmental inequalities as a factor that rein forces social inequalities.The article concludes that further sociological study of social inequality issues is necessary, analyzes the role of sociology in addressing these issues and actualizing the data.

Transportation is associated with environmental problems, economic losses, population health, and social inequities. This last problem, in particular, a negative impact on generates the urban public transportation of people with disabilities, which entails a methodology of interpersonal, social, technological and institutional challenge without neglecting the characteristics of design for disabilities, as well as sensory ones. The objective of this article is a design proposal for the public transport system of the Guayaquil city, in the field of artificial intelligence, the human factor and ergonomic design for the disabled with an inclusive model according to the World Health Organization and the World Bank. The needs of people with limited capacities in urban public transport are explored for recurring services and destinations. Through the experiences lived in the metrobus public transport service, based on two methodologies; “Intelligent urban public transport dedicated to accessibility for people with disabilities” and “The effect of transport accessibility on the social inclusion of wheelchair users: An analysis of mixed methods”. While modeling the behavior of people with disabilities is a complex task, it has a remarkable social and economic impact. Therefore, in this article, neutrosophic cognitive maps are explored to represent the behavior and functioning of such complex systems. This soft computing technique to model how Allows us make decisions based on travelers their knowledge of different modes of transport properties at different levels of abstraction. The results of the study will help transport are decision-makers to better understand the needs of people with disabilities and, as a result, help them to update their policy. At the end of the article, we discuss how the design proposal can be articulated metrobus within the urban transport system and the accessibility of the use of ICT to people with disabilities.

In an increasingly volatile, uncertain, complex, and ambiguous (VUCA) world, technology's role in delivering environmental justice has been examined. It has been argued that technological solutions are necessary to support environmental sustainability in the course of the entire world's effort to deal with the interlinked challenges of climate change, resource competition, and environmental degradation. Electricity is being produced differently and efficiently through renewable energy technologies (solar, wind,and hydropower), which has reduced the reliance on fossil fuels and the resulting emissions that are harmful to the planet and climate. However, while these technologies have clear environmental advantages, they may not necessarily result in improvements in environmental justice. The negative consequences for social, economic, and environmental inequalities of the current pace of technological innovation are that they affect marginalized and vulnerable communities as the marginalized groups (those most affected by environmental degradation) often find it difficult to access and benefit from the technical innovations. This research seeks to explore the link between technology and fairness by questioning whether advancements in technology can help alleviate or unintentionally worsen current disparities in society structures. The study investigates how tools like satellite sensing and artificial intelligence can boost surveillance and increase clean energy accessibility while reducing the adverse effects of pollution on underserved communities. Although these advancements offer hope, in tackling decline and promoting advancement scientists are currently encountering hurdles regarding fairness and inclusivity when putting them into practice in real-life situations. The study aims to explore whether the benefits of progress are evenly spread out and how they can be used to reduce inequalities, in healthcare and safety than making them worse. The main goal of this research is to examine how technology can be used to support equality while also addressing the challenges it poses in exacerbating disparities. The study will thoroughly explore the benefits. The downsides of technology, in the age of the Anthropocene were characterized by human-induced changes to the environment. This study looks into how technology can promote sustainability and social justice while providing suggestions, for approaches and technologies that prioritize equality and inclusivity to prevent marginalized communities from being left out in endeavors toward a future. In today's changing world characterized by volatility and unpredictability, there is a growing discussion, among experts on the role of technology in promoting or hindering justice efforts. The dynamic nature of the VUCA context poses obstacles, to ensuring sustainability. Consequently, the use of technology in approaches to pursuing environmental justice has captured the interest of scholars, policymakers, and activists.

Can artificial intelligence (AI) help enable a new pluralistic and multi-dimensional cost-benefit analysis (CBA) for complex human-natural systems? Yes, it can. This policy brief quickly summarizes the history of water economics and considers how environment and infrastructure planners and investors can exploit a new approach to address today’s climate, water scarcity and environmental inequity crises.

The uneven proliferation of artificial intelligence (AI) presents unexamined challenges to sustainable regional development. This study provides robust empirical evidence on how the inter-city AI gap influences environmental dynamics, specifically via transboundary air pollution. Using a framework based on the Technological Gap Theory, the results demonstrate that a wider AI gap significantly intensifies air pollution transmission between cities. The primary mechanisms are widening disparities in digital infrastructure and imbalanced flows of capital and labor. This effect is context-dependent and most severe for economically underdeveloped cities, creating a new form of environmental inequity. The analysis further reveals that while environmental regulations can mitigate this negative impact, technology-centric policies lacking green synergy may amplify it. The research’s findings offer a new theoretical lens on techno-environmental inequality and underscore the necessity of synergistic policies that simultaneously bridge the digital and environmental divides to foster equitable and sustainable development.