Which system mimics the way human brains process information through interconnected processing units?

The correct answer is Artificial Neural Network (ANN) because it is specifically designed to replicate the way human brains process information. ANNs consist of layers of interconnected nodes, or neurons, which process input data through various mathematical functions, akin to how biological neurons communicate and relay information. This interconnected architecture allows ANNs to learn from data, recognize patterns, and make predictions, emulating the cognitive functions of the human brain.

Deep Learning refers to a subset of machine learning that utilizes neural networks with many layers (often referred to as deep neural networks) to analyze various forms of data. While deep learning operates on principles similar to those of ANNs, it doesn't entirely reflect the simple model of neural networks as described in the context of mimicking brain processes.

Generative Adversarial Network (GAN) is a specific type of neural network that consists of two competing networks, the generator and the discriminator. While GANs leverage neural network principles, they do not focus on replicating the human brain's processing. Instead, they are used for generating new data samples based on the input data.

Ethical AI encompasses a broader discussion about ensuring that AI systems are developed responsibly, addressing issues like fairness and bias. It does not concern itself with the mimicking of brain processes