AI-Powered System for Simplifying and Analyzing Terms and Conditions

Abstract

Terms and Conditions (Ts&Cs) are foundational legal documents governing digital interactions between users and service providers. Despite containing critical information related to user rights, data privacy, and liability, these documents remain largely inaccessible due to their legal complexity and verbosity. This paper presents an AI-driven mobile application that leverages advanced Natural Language Processing (NLP) and Large Language Models (LLMs), particularly GPT-based architectures, to automate the simplification and risk analysis of Ts&Cs. The system provides end-users with concise summaries, risk flags, and contextual indicators for informed consent. The mobile application supports multiple input modalities, including document uploads, web URL parsing, and app-based term extraction. Evaluation was conducted using ROUGE and BERTScore metrics, achieving high fidelity in semantic summarization. Usability testing demonstrated that the system improves comprehension, fosters transparency, and reduces the time required for users to interpret legal documents. This work contributes to the broader discourse on algorithmic transparency, digital fairness, and ethical AI deployment in consumer protection. Experimental results indicate significant potential for scaling such tools across diverse jurisdictions and languages.