As artificial intelligence advances, the technology to generate human-like movements has become increasingly sophisticated. This project seeks to understand how we can distinguish between genuine human motion and machine-generated movements. We explore this question from two main angles:

- Expressing Perspective: How do humans convey "humanness"  through movements, aiming to be recognized as fellow humans by others?
- Perceiving Perspective: How observers can distinguish between real human motion and AI-generated movements?

Our approach blends qualitative and quantitative research methods to study the characteristics of motion and the criteria used by both performers and observers in making these distinctions. Understanding the nuances of body movements and their role in human recognition is critical for fields such as game development, computer graphics, virtual reality, and AI-driven motion design. This study not only deepens our understanding of human-like movements but also addresses an important gap in current research, offering practical guidance for enhancing the realism of AI-generated motion.