COMBATING GENERATION OF MISINFORMATION USING AI ENABLED DEEPFAKE TECHNOLOGY

The rise of social media and digital platforms has amplified the spread of misinformation, posing significant social, economic, and political risks. Artificial intelligence (AI) has emerged as a promising solution for detecting, analyzing, and combating misinformation online. This paper explores the various AI-driven techniques and algorithms used to identify false information, such as machine learning (ML), natural language processing (NLP), and deep learning models. These technologies can identify patterns in text, image, and video content, allowing for more accurate recognition of fake news, Deepfakes, and manipulated media. AI systems can also analyze the spread patterns of misinformation to predict and prevent future outbreaks. However, while AI shows considerable potential, it faces several challenges, including issues of data quality, algorithmic bias, and ethical concerns around privacy and freedom of expression. This paper outlines the how the misinformation is generated using Deepfake technology. Through this, we aim to highlight review of literature related to improve the effectiveness and fairness of AI-driven solutions in combating misinformation.