AI Innovation collapses biodiversity
Alokya Kanungo ’23, Ph.D in Scientific Correlation between the Impact of Climate Change on Soil Health and Sustainable Agriculture from K.I.I.T. University and an M.Phil. in Geography, “The Green Dilemma: Can AI Fulfil Its Potential Without Harming the Environment?” Earth.org, 07/18/2023, https://earth.org/the-green-dilemma-can-ai-fulfil-its-potential-without-harming-the-environment/ , Accessed 07/16/2024 by NT-SH
Recently, a study was conducted by researchers at the University of Massachusetts to determine how much energy is used to train certain popular large AI models. According to the results, training can produce about 626,000 pounds of carbon dioxide, or the equivalent of around 300 round-trip flights between New York and San Francisco – nearly 5 times the lifetime emissions of the average car.
The e-waste produced by AI technology poses a . contains hazardous chemicals, including lead, mercury, and cadmium, that can contaminate soil and water supplies and endanger both human health and the environment.
By 2050, the World Economic Forum (WEF) that the total amount of e-waste generated will have surpassed 120 million metric tonnes. To avoid environmental harm and minimise the release of dangerous compounds, proper e-waste management and recycling are essential. To ensure the secure processing and recycling of AI-related electronic waste and significantly reduce its negative environmental effects, more stringent laws and ethical disposal practices are required.
AI applications like and delivery drones pose a threat to animals and natural environments. Automation fuelled by AI may result in greater consumption as well as increasing waste in certain sectors, such as the e-commerce industry, which has normalised the rapid and frequent delivery of goods.
The rising use of AI in agriculture could result in the overuse of pesticides and fertilisers, contaminating the soil and water, and harming biodiversity. Implementing AI in agricultural practices to increase yields at the expense of maintaining ecosystem health could lead to monocultures and biodiversity loss.
Using AI for environmental management also raises ethical questions. Decisions made by AI systems could be biased if they were presented with inaccurate or incomplete data. For instance, if an AI system received instructions to value economic growth over environmental protection, it might choose to put short-term financial gain ahead of environmental sustainability.
People can build sustainable practises and make educated decisions by taking into account the potential environmental effects of AI adoption. AI’s advantages must be balanced with protecting our natural ecosystems in order for technology and nature to coexist.