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    Artificial Intelligence and Environmental Impact: Moving Beyond Humanizing Vocabulary and Anthropocentrism
    (Mary Ann Liebert, Inc, 2025) Karakas, Umit; Ozdemir, Vural
    Artificial intelligence (AI) and its applications in digital health, bioengineering, and society have significant material impacts on the environment owing to AI's vast energy demands and energy consumption, carbon footprints, and water usage to cool data centers and generate electricity to power the data centers. Yet, the environmental footprints of AI remain underappreciated and inadequately acknowledged. This is significant, particularly in this era of climate emergency and ongoing threats to planetary energy and water supplies. The vocabulary attached to AI often aims to mimic positive human capacities such as warmness and care. However, these attempts to humanize AI and digital technology come with an anthropocentric gaze and blind spots that bracket out the environmental impacts and footprints of AI and privilege humans and technology over nonhuman animals and planetary ecological limits. In medicine, the environmental impacts of large language models range from water consumption and carbon emission to rare mineral usage. This commentary and innovation analysis question and queer the popular imagination of AI and digital technology as things that only exist in the immaterial world of cyberspace. In the course of research on AI in planetary health, we must be cognizant of its materiality, ecological impacts, and massive energy and water demands. We argue that moving away from anthropocentric narratives and vocabulary in AI design and praxis would bode well to live within planetary ecological limits so that AI and emerging digital technologies best serve robust and responsible science and all life on the planet Earth.