How Data Poisoning Breaks AI Models

Modern AI systems are powerful, but they’re not immune to hidden risks. A recent study revealed that inserting just a few hundred malicious documents into training data can introduce serious vulnerabilities, even in large AI models. This video explains how data poisoning attacks work, why they matter for organizations using AI, and the practical steps teams can take to reduce risk. Learn how attackers manipulate training data, what backdoor triggers look like, and how stronger data governance and monitoring can protect AI systems. Explore courses and resources to strengthen AI and data skills: https://bit.ly/4bjGpEB Achieve Your Goals with Coursera Plus: https://www.coursera.org/courseraplus If this video was helpful, consider liking the video and subscribing to the channel for more insights on AI, data, and emerging technology. 0:00 - Introduction to AI Data Tampering 0:14 - Anthropic Study Findings 1:15 - Defining Data Poisoning 2:14 - Business Risks and Real-World Impact 3:18 - Mitigating the Risks 4:47 - Conclusion and Final Takeaways #ArtificialIntelligence #AISecurity #MachineLearning #DataScience #AITraining #Cybersecurity #AITrends #TechEducation