The application of artificial intelligence has significant environmental impacts, as the training and operation of models rely on data centres with high energy and water demands. This can increase carbon dioxide emissions and the volume of electronic waste, particularly when energy is sourced from non-renewable resources. At the same time, AI can enhance the efficiency of industrial processes, energy management, and transportation, potentially reducing emissions overall.<\/p>
Reducing the ecological footprint of AI requires a thoughtful, deliberate approach: AI should be used only when it provides genuine added value and its application is planned in advance. Unnecessary, ubiquitous, and repeatedly executed processes should be avoided, as they disproportionately increase resource consumption. Preference should be given to smaller, task-specific models, the optimisation and reuse of results, and the use of energy-efficient infrastructure.<\/p>
Ultimately, conscious decision-making and moderate use make it possible to benefit from AI’s advantages while acting responsibly towards the planet\u2019s natural resources.<\/strong><\/p>","protected":false},"excerpt":{"rendered":" The application of artificial intelligence has significant environmental impacts, as the training and operation of models rely on data centres with high energy and water demands. This can increase carbon dioxide emissions and the volume of electronic waste, particularly when energy is sourced from non-renewable resources. At the same time, AI can enhance the efficiency<\/p>\n","protected":false},"author":58,"featured_media":0,"parent":818,"menu_order":3,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"_eb_attr":"","footnotes":""},"categories":[],"tags":[],"class_list":["post-1250","page","type-page","status-publish","hentry"],"acf":[],"yoast_head":"\n