The Fake News Arms Race - How AI Can Create, and Detect, Fakes

Overview

Explore the AI-driven battle against fake news, from deep-fake creation to detection technologies. Learn how machine vision and NLP combat misinformation at scale.

Syllabus

• Introduction to Fake News
Definition and history of fake news
Impact of fake news on society
• AI in News Creation
Generative models and deep fakes
Natural Language Processing (NLP) for text generation
Case studies in AI-generated fake news
• Machine Vision and Deep Fakes
Understanding deep fake technology
Techniques for creating convincing media fakes
Ethical implications of media manipulation
• NLP Techniques for Fake News Detection
Overview of NLP and misinformation detection
Sentiment analysis and fact-checking algorithms
Leveraging large language models for detection
• Machine Learning Models for Misinformation Detection
Supervised learning techniques
Unsupervised and semi-supervised learning for anomaly detection
Evaluation metrics for fake news detection systems
• The Role of Social Media Platforms
Detection algorithms used by major platforms
Challenges in real-time detection and mitigation
Strategies for combating misinformation on social networks
• Case Studies in Combating Fake News
Analysis of successful detection systems
Lessons learned from past misinformation campaigns
Future prospects for AI in fake news detection
• Ethical and Societal Implications
Privacy concerns and data ethics
The balance between censorship and freedom of speech
Global perspectives on AI-driven misinformation
• Hands-on Projects and Lab Sessions
Developing a simple fake news detection model
Experimenting with image and video manipulation tools
Building a fact-checking chatbot using NLP tools
• Course Conclusion and Future Directions
Recap of key learnings
Potential future developments in AI and misinformation
Preparing for a career in AI-driven combat against misinformation

Subjects

Conference Talks