Trust Score for Generative AI Outputs: A Cross-Platform Framework with NLP and Sentiment Analysis
Published: 2025
Author(s) Name: S. Saritha, N. Anjaneyulu and Gandikota Durga Rao |
Author(s) Affiliation: Computer Science and Engineering, Swarna Bharathi Inst. of Science and Tech., Telangana, India.
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Abstract
It’s amazing how generative artificial intelligence (AI) systems can make works of literature, art, and other creative things that look like they were made by people. These outputs nevertheless need to be correct, reliable, and in line with ethical standards if they are going to be widely used. To solve this challenge, the idea of a Trust Score has been put forward as a way to quantify the quality, openness, and dependability of generative AI systems. The trust score combines numerous factors into one number that lets customers judge how reliable AI-generated content is and make smart choices about how to use it. This kind of approach not only promotes responsibility and responsible AI use, but it also makes users feel more confident in many areas, including business, healthcare, education, and the arts.
Keywords: AI dependability, Artificial intelligence. Explainability, Reliable AI, Trust score.
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