Front-end AI vs. Back-end AI: new framework for securing truth in communication during the generative AI era

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.