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The use of Artificial Intelligence in environmental sustainability would include both problem-solving and decision-making. Every intelligent being, be it natural or artificial must develop some logicolinguistic ontology, in its cognitive structuring. The intelligence is inclusive of perceptions and reactions. How the technology can help in conservation, management and sustainability is a deeper space to explore. The impact of efficient machines and sensitivity of human necessities bring forth the much-awaited policies for economic, social and environmental sustainability. In the world of consumerism and technological maximalism, where is the space to breathe? Ensuring resources and owning responsibility for climate change falls on our shoulder. Human consciousness is as remote as that of an intelligent machine. Where our way of life is automated and unconsciously participative in environmental degradations. Can we stop behaving like Robots, and realize that our sustenance depends on air and water. The paper tries to discuss the conceptual relevance of how machines can be useful and whether we should depend on them for a secure future under the ambit of a regulatory framework. [ABSTRACT FROM AUTHOR]

The paper aims at investigation of the nexus between Industry 4.0 (I4.0) and environmental sustainability in addition to exploring the long-run and short-run effects of Industry 4.0 on CO 2 emissions. For this end, energy consumption, internet and communication technology (ICT) exports, research and development (R&D), artificial intelligence (AI), ICT technology patents and bitcoin are taken as control variables of Industry 4.0 for a panel of 9 countries that contribute to 62% of the total CO 2 emissions in the world. For this purpose, the paper follows two approaches. First, the paper proposes utilization of AI and ICT technology patents, technology-related R&Ds and ICT exports as variables of I4.0 in addition to investigating the effects of economic growth, energy consumption and bitcoin. Second, to control structural changes and nonlinearity in the cointegrating relations and existence of degenerate cointegration, Fourier panel bootstrap autoregressive distributed lag model (FPBARDL) is utilized. Afterwards, FPBARDL based long, short and strong causality analyses are conducted. The empirical findings revealed positive impacts of all I4.0-related variables on emissions in the long-run. Though I4.0 related AI and ICT innovation has no direct effect in the short-run, its effects are determined through increased energy consumption towards emissions. The strong positive effects of energy consumption and positive effects of economic growth, ICT exports and R&D are observed both in the short and long-run. In addition to positive impacts of I4.0 on environment, the findings favor insufficiency of policies focusing on lowering emissions in I4.0 context.Policy recommendations include strong commitment to energy efficiency and renewable energies and trade policies with environmental concerns. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) can transform health care by delivering medical services to underserved areas, while also filling gaps in health care provider availability. However, AI may also lead to patient harm due to fatal glitches in robotic surgery, bias in diagnosis, or dangerous recommendations. Despite concerns ethicists have identified in the use of AI in health care, the most significant consideration ought not be vulnerabilities in the software, but the environmental impact of AI. Health care emits a significant amount of carbon in many countries. As AI becomes an essential part of health care, ethical reflection must include the potential to negatively impact the environment. As such, this article will first overview the carbon emissions in health care. It will, second, offer five reasons why carbon calculations are insufficient to address sustainability in health care. Third, the article will derive normative concepts from the goals of medicine, the principles of biomedical ethics, and green bioethics—the very locus in which AI in health care sits—to propose health, justice, and resource conservation as criteria for sustainable AI in health care. In the fourth and final part of the article, examples of sustainable and unsustainable development and use of AI in health care will be evaluated through the three‐fold lens of health, justice, and resource conservation. With various ethical approaches to AI in health care, the imperative for environmental sustainability must be underscored, lest carbon emissions continue to increase, harming people and planet alike. [ABSTRACT FROM AUTHOR]