Abstract
The proliferation of artificial intelligence (AI) in digital platforms has complicated the concept of truth in communication studies. The article presents the dichotomic framework of Front-end AI and Back-end AI to tackle the complexity of distinguishing truth. Front-end AI refers to AI technology used up-front, often as the face of a product or service, challenging the authenticity and truthfulness of content. In contrast, Back-end AI refers to AI technology used behind the scenes, which can generate misleading or biased content without disclosing its AI-generated nature. Addressing these challenges requires different approaches, such as verification and ethical guidelines for Front-end AI and algorithmic transparency, bias detection, and human oversight for Back-end AI.
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