What Are High-risk AI Systems Under New Regulations? - AI and Machine Learning Explained
Автор: AI and Machine Learning Explained
Загружено: 2025-10-31
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What Are High-risk AI Systems Under New Regulations? Have you ever wondered how new regulations aim to keep artificial intelligence systems safe and fair? In this informative video, we'll explain everything you need to know about high-risk AI systems and the rules that govern them. We'll start by defining what high-risk AI systems are and which applications fall into this category, such as facial recognition, credit scoring, hiring tools, and critical infrastructure management. We'll discuss why these systems require special oversight due to their potential to cause harm if they malfunction or are biased.
We'll also explain the key requirements for providers of high-risk AI, including conducting detailed risk assessments, maintaining transparency through technical documentation, and using high-quality data to prevent unfair outcomes. The importance of human oversight and activity logging will be covered, along with ongoing monitoring to ensure continued safety and fairness. Additionally, cybersecurity measures are emphasized to prevent malicious attacks.
For general-purpose AI models like ChatGPT and DALL·E, the rules focus on transparency and safety, especially when these models pose systemic risks. We'll outline how these regulations aim to balance innovation with responsible development, ensuring AI tools are used ethically and safely. Whether you're an AI developer, user, or enthusiast, understanding these regulations helps you stay informed about how AI impacts society and what safeguards are in place.
Join us for this detailed overview, and subscribe to our channel for more insights on AI and machine learning advancements.
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About Us: Welcome to AI and Machine Learning Explained, where we simplify the fascinating world of artificial intelligence and machine learning. Our channel covers a range of topics, including Artificial Intelligence Basics, Machine Learning Algorithms, Deep Learning Techniques, and Natural Language Processing. We also discuss Supervised vs. Unsupervised Learning, Neural Networks Explained, and the impact of AI in Business and Everyday Life.
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