Draft:Disproportionate Impact of Global AI Waste
| Submission declined on 2 December 2024 by CoconutOctopus (talk). This submission is not adequately supported by reliable sources. Reliable sources are required so that information can be verified. If you need help with referencing, please see Referencing for beginners and Citing sources. This submission reads more like an essay than an encyclopedia article. Submissions should summarise information in secondary, reliable sources and not contain opinions or original research. Please write about the topic from a neutral point of view in an encyclopedic manner.
Where to get help
How to improve a draft
You can also browse Wikipedia:Featured articles and Wikipedia:Good articles to find examples of Wikipedia's best writing on topics similar to your proposed article. Improving your odds of a speedy review To improve your odds of a faster review, tag your draft with relevant WikiProject tags using the button below. This will let reviewers know a new draft has been submitted in their area of interest. For instance, if you wrote about a female astronomer, you would want to add the Biography, Astronomy, and Women scientists tags. Editor resources
|  |
Artificial Intelligence entails the programming of computers to perform tasks often executed by human intelligence, including prediction, reasoning, comprehension of visual or auditory stimuli, and collaboration with humans and machines. Artificial intelligence is driven by machine learning, a study domain where computers are trained on historical data to forecast output values. This allows software, such as search engines or spam filters, to enhance accuracy without explicit programming.
AI encompasses not only intangible aspects but predominantly tangible ones that result in detrimental effects on the environment and society, including environmental injustice and the e-waste crisis, which is further intensified by the unequal distribution of AI waste between the global north and global south. The extraction of rare minerals for AI technology severely impacts ecosystems and indigenous communities, particularly in resource-abundant yet economically impoverished areas such as the Democratic Republic of Congo and Chile. These regions have biodiversity decline, water scarcity, and pollution resulting from mining and manufacturing activities. The swift technological advancements in AI hardware produce substantial e-waste, a significant portion of which is informally recycled in the Global South. This results in perilous conditions, encompassing toxic chemical exposure and poisoning of land and water, disproportionately impacting marginalised groups.
This phenomenon distinctly produces unequal advantages in the utilisation of AI. AI systems are mostly created and implemented in the Global North, tailored to address the requirements of these countries. The South incurs the environmental burden without fair access to the economic or technological benefits of AI. To address the issue, it is essential to promote lifecycle-based environmental assessments of AI systems, implement stronger international e-waste rules, and establish policies that guarantee sustainable resource extraction and recycling procedures.