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A deepfake is synthetic media — typically video or audio — created using deep learning to convincingly replace one person's likeness or voice with another's. The technology can produce content that is extremely difficult to distinguish from genuine recordings.
Deepfakes pose serious risks to trust, security, and democracy — from financial fraud to political disinformation — making detection tools and media literacy increasingly vital.
In 2024, scammers used a deepfake video call impersonating a CFO to trick an employee at a Hong Kong firm into transferring $25 million.
Generative Adversarial Network (GAN)
A generative adversarial network consists of two neural networks — a generator and a discriminator — that compete against each other. The generator creates synthetic data while the discriminator tries to distinguish it from real data, and through this competition both improve.
AI Bias
AI bias occurs when a system produces results that are systematically prejudiced due to flawed assumptions in the training data or algorithm. It can reflect and amplify existing societal inequalities, leading to unfair outcomes for certain groups.
Responsible AI
Responsible AI is an approach to developing and deploying AI systems that prioritises fairness, transparency, accountability, and societal benefit. It encompasses practices and principles designed to minimise harm and ensure AI serves people equitably.
Our programme follows a structured Level 4 curriculum with project-based learning, practical workflows, and guided implementation across business and career use cases. Funded route available for UK citizens and ILR holders.