In a comprehensive study conducted by the Amazon Web Services (AWS) AI Lab, a disconcerting reality has surfaced, shaking the foundations of internet content. Shockingly, an extensive 57.1% of all sentences on the web have undergone translation into two or more languages, and the culprit behind this linguistic convolution is none other than large language model (LLM)-powered AI.
The crux of the issue resides in what researchers term as “lower-resource languages.” These are languages for which there is a scarcity of data available for the effective training of AI models. The domino effect begins with AI generating vast quantities of substandard English content. Following this, AI-powered translation tools enter the stage, exacerbating the degradation as they transcribe the material into various other languages. The motive behind this cascade of content manipulation is a profit-driven strategy, aiming to capture clickbait-driven ad revenue. The outcome is the flooding of entire internet regions with an abundance of deteriorating AI-generated copies, creating a dreading universe of misinformation.
The AWS researchers express profound concern, eemphasising that machine-generated, multi-way parallel translations not only dominate the total translated content in lower-resource languages but also constitute a substantial fraction of the overall web content in those languages. This amplifies the scale of the issue, underscoring its potential to significantly impact dive
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