The article opens by referencing Alan Turing's famous question posed in 1950, 'Can machines think?' and advances to a more complex inquiry of today's era: 'Can machines feel?' In the context of the fourth industrial revolution, artificial intelligence is at the forefront, particularly in a domain known as affective computing, which seeks to merge strict data analysis with the nuanced realm of human emotions. This highlights the need to reconsider our understanding of what machines can perceive when it comes to human experience.

To analyze emotions, AI utilizes a multi-layered approach that translates qualitative emotional states into quantitative values. The article outlines three main technological layers involved in this process: Firstly, computer vision employs convolutional neural networks (CNNs) to assess facial expressions by marking reference points on the face and comparing them with extensive databases like AffectNet to categorize emotions. Secondly, natural language processing (NLP) applies transformer models that evaluate text context and attention mechanisms to gauge emotional weight, discern sarcasm from earnestness, and more. This bifurcation of emotion into measurable components is vital for AI's understanding and responding to human feelings.

The ongoing exploration of AI's potential emotional capabilities raises significant ethical and practical questions for society. As machines become more adept at interpreting human emotions, it challenges existing paradigms of interpersonal relationships and how we interact with technology. This could also lead to broader discussions on the implications of integrating such technology into daily life, as well as the moral responsibilities associated with creating responsive machines that mimic human emotional responses.