Part 4/11:
The idea that AI is infallible and always generates accurate results is dangerously misleading. While AI can handle vast datasets and accomplish certain tasks with great precision, it remains prone to errors due to biases, incomplete data, or algorithmic limitations. Recognizing that AI's output is dependent on the quality of its input data is essential for responsible development and deployment. Human oversight and rigorous testing are crucial, particularly in high-stakes environments like healthcare and autonomous vehicles.