As higher education faces technological advancement and environmental imperatives, AI becomes a key instrument for revolutionizing instructional methods and institutional operations. AI can improve educational outcomes, resource management, and long-term sustainability in higher education, according to this study. The research uses case studies and best practices to show how AI-driven innovations can minimize environmental impact, enhance energy efficiency, and customize learning, creating a more sustainable and inclusive academic environment. The document discusses AI ethics, including data privacy, algorithmic prejudice, and the digital divide. It emphasizes the need for strong ethical frameworks to use AI ethically and make decisions with transparency and fairness. The study also emphasizes the need for robust institutional rules and infrastructure to promote ethical AI integration, protecting student privacy and supporting fair access to AI technologies. The research also shows how AI-driven curriculum-building tools can educate students for future sustainability concerns and stimulate research innovation. The prospects and difficulties of AI in higher education are critically examined, including its potential to change traditional educational roles, improve academic performance, and maintain institutional profitability. Actionable recommendations for educators, politicians, and institutional leaders contribute to the education sustainability conversation. Focusing on AI and sustainability creates the framework for a future where technology and environmental stewardship are intimately connected, ensuring that higher education institutions can prosper in a fast-changing world.
Marine fisheries constitute a crucial component of global green development, where artificial intelligence (AI) plays an essential role in enhancing green economic efficiency associated with marine fisheries. This study utilizes panel data from 11 coastal provinces and municipalities in China from 2009 to 2020, employing the entropy method and the super-efficiency EBM model to calculate the AI index and the green economic efficiency of marine fisheries. Based on these calculations, we utilize fixed effects models, moderation effect models, and panel threshold models to examine the impact of AI on the green economic efficiency of marine fisheries. The study reveals that: (i) From 2009 to 2020, AI has significantly improved overall, while the green economic efficiency of marine fisheries has shown a fluctuating trend, with substantial regional disparities. (ii) AI significantly enhances the green economic efficiency of marine fisheries. (iii) Green finance, trade openness, and R&D investment act as crucial moderating variables, accelerating AI development and further improving the green economic efficiency of marine fisheries. (iv) The impact of AI on green economic efficiency varies across different intervals of green finance, trade openness, and R&D investment. These findings are crucial for understanding and advancing the informatization strategy of marine fisheries and hold significant implications for the sustainable development of global marine fisheries.
La guía Inteligencia Artificial Generativa (IAG) para los Objetivos Mundiales, creada por el Pacto Mundial de la ONU y Accenture, ofrece herramientas para que las empresas adopten la IAG de forma responsable y contribuyan al desarrollo sostenible. La guía destaca acciones para integrar la IA en estrategias empresariales, acelerando el cumplimiento de los Objetivos de Desarrollo Sostenible (ODS).