In recent years, the use and integration of Artificial Intelligence (AI) have grown significantly in all aspects of our lives. Professionally, AI aims to simplify, accelerate, and streamline processes that can be particularly demanding when performed by humans, reducing the chance of human errors often caused by tiredness or distraction. However, training AI to recognize human emotions based on biometric parameters measured on humans can be quite challenging. In response to specific emotional stimuli, our brain reacts with very specific actions, which in turn trigger biometric changes that can be assessed. Nevertheless, emotional responses are incredibly complex processes that depend on various factors; one of these factors is society. Society educates us on how to respond to certain emotions, and this is why children learn to respond to their emotions by observing how the adults around them react. It is also important to consider that emotional responses depend on and are mediated by our nervous system; this intricate neural network is influenced by biotic and abiotic factors, whose complexity and unpredictability cannot be overstated. All these elements pose significant challenges for AI when it is used to decipher and evaluate human emotions. Moreover, the use of AI will inevitably lead to moral and ethical issues that could undermine the purpose of using AI to improve our society. When AI analysis of emotions is used in the legal system, the issue becomes even more complicated. Given the very serious implications such analyses can have, relying solely on AI for these assessments should not be considered sufficient or reliable. It is necessary for human beings to perform emotional assessments, as they can not only compute the values of biometric changes but also integrate medical information and information from the social context. Additionally, a deep understanding of psychopathology, particularly the psychopathy of deviance, is essential. This allows for the implementation of analysis with an assessment of nonverbal communication, providing a comprehensive picture of the personality. This psychological profiling is crucial not only to comprehend a person’s past actions but also to predict future ones. In conclusion, to guarantee the best possible analysis and limit the possibility of moral and ethical issues, it is extremely important for a human to oversee this process. AI can be used to recognize emotions based on biometric alterations, but it should not go further than that. Relying solely on its conclusions would be sterile and incomplete, and from a legal standpoint, could impact the admissibility of the analysis in court. We are grateful for the possibilities that AI has opened up for us and for the major support it provides; however, we must not forget that AI is merely a tool that cannot and should not replace humans, especially in something as complex and important as the analysis of human emotions. While AI reaches its conclusions based on trends identified after analyzing vast amounts of data, what I do is fundamentally different. I use an individualistic approach that integrates what I know about the psychological status of the subjects, along with my knowledge of nonverbal communication and any other elements that can influence behavior. This is almost a “sixth sense” that can process information beyond statistical trends and is specific and characteristic only of us humans. In fact, not everyone possesses the ability to perform these analyses, not even all individuals working in the field of psychology. Even those who do have the ability and are able to conduct these analyses probably do so in different ways, using different methodologies and pathways to reach their conclusions. This is the core reason why the work on a human cannot be replaced by AI. We do not have an AI capable of computing all these elements, and I doubt we ever will. I would not feel confident using a program based on the same algorithms to reach conclusions on something as deep and personal as human emotions and behavioral responses. It would mean using a one-size-fits-all model when we know for a fact, as a community, that each of us is unique, even when exposed to the same stimuli.