Explore the concept of facial beauty from both computational and aesthetic perspectives. "A Comprehensive Review of Facial Beauty Prediction Using Multi-task Learning and Facial Attributes" focuses on how artificial intelligence, particularly C and convolutional neural networks, predicts attractiveness based on facial attributes like symmetry and hairstyle. It also highlights challenges such as data biases and the subjective nature of beauty. Concurrently, "AI's Grasp of Beauty: Algorithms, Virtual Humans, and Bias" expands on AI's ability to measure attractiveness using mathematical principles like the Golden Ratio and facial symmetry, create virtual humans, and adapt to cultural preferences, while critically examining inherent biases in training data and their societal impact. Finally, "Golden Ratio Face: Facial Beauty & Proportions" provides a more traditional, plastic surgery-oriented view of beauty, explaining the historical and practical application of the Golden Ratio and other proportional measurements in achieving aesthetically pleasing facial features, distinguishing between male and female beauty standards and discussing cosmetic procedures for enhancement.