Understanding what AI can and cannot do in practice
Welcome to this lesson on AI capabilities and limitations. As AI systems become increasingly integrated into our daily lives and work environments, it's important to understand what these systems can and cannot do. This knowledge will help you make informed decisions about when and how to apply AI in your organization.
Key strengths and capabilities of current AI systems
AI excels at finding patterns in large datasets that would be difficult or impossible for humans to detect, making it valuable for data analysis, fraud detection, and predictive maintenance.
AI can process and analyze vast amounts of data much faster than humans, making it ideal for tasks like document review, customer data analysis, and scientific research.
AI can automate routine and repetitive tasks with high accuracy, freeing up human time for more creative and strategic work. Examples include data entry, basic customer service, and content moderation.
Modern AI can generate text, images, audio, and video that closely mimics human-created content, useful for drafting documents, creating marketing materials, and assisting in creative processes.
These capabilities make AI particularly valuable for scaling operations, improving efficiency, and handling data-intensive tasks that would be time-consuming or error-prone for humans.
Important limitations to consider
AI systems can identify correlations but struggle with understanding cause and effect relationships. They can tell you what factors appear together but cannot reliably determine why something happens.
AI lacks the human ability to understand complex ethical nuances, cultural contexts, and societal values. This is particularly important in fields like healthcare, law, and social services.
AI typically performs poorly on unusual or rare scenarios it wasn't specifically trained on, making it unreliable for situations that deviate from common patterns.
Despite recent advances, AI still struggles with basic common sense reasoning that humans take for granted, such as understanding physical constraints, temporal relationships, or intuitive physics.
Special considerations for AI systems in regulated domains
The EU AI Act categorizes AI applications based on their risk level. High-risk applications require special attention to ensure safety, fairness, and compliance with regulations.
For these applications, organizations must implement:
When considering AI implementation, it's important to match the technology's capabilities with appropriate use cases. Here are some guidelines:
Remember that AI works best as an augmentation to human capabilities, not as a complete replacement. The most successful implementations combine AI's processing power with human judgment and expertise.
In this lesson, we've explored the capabilities and limitations of AI systems. Key takeaways include:
Understanding these strengths and limitations will help your organization make informed decisions about AI adoption and implementation, avoiding common pitfalls while maximizing potential benefits.