AI causes in increase of emissions, e-waste, and destroys our environment, causing extinction

As datasets and models become more complex, the energy needed to train and run AI models becomes enormous. This increase in energy use directly affects greenhouse gas emissions, aggravating climate change. According to OpenAI researchers, since 2012, the amount of computing power required to train cutting-edge AI models has doubled every 3.4 months. By 2040, it is expected that the emissions from the Information and Communications Technology (ICT) industry as a whole will reach 14% of the global emissions, with the majority of those emissions coming from the ICT infrastructure, particularly data centres and communication networks. These data demonstrate the urgent need to address AI’s carbon footprint and role in environmental deterioration.

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 serious environmental challenge. E-waste 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) projects 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 driverless automobiles 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.