Translating Tones: AI’s Approach to Emotional Context in Language
With the opening of public access to AI chat boxes like ChatGPT arose questions about the unique abilities of computers and humans, and whether there were some that we could say are exclusive. Certainly humans cannot process data or language with the speed, efficiency or scale as AI technologies, and that is AI’s greatest gift to humans. And on the other hand, AI is certainly not able to process emotion–that uniquely human thing– as well as humans themselves can.
We must also remember and recognize that human emotion is multidimensional, expressing itself in facial expressions, tone of voice and body language (that thing that AI cannot ‘read’). These ambiguities are also exacerbated– at least, in terms of the AI models– given that there are many cultural differences in how emotions are expressed. Additionally, every person has unique tendencies or emotional expressions, making it difficult for algorithms to pin down emotion or transform it into a data set. For this reason, there have been significant challenges in the development of the technology.
This article explores the way in which this may be changing. As AI technologies are quickly being developed all over the world, the gap left by emotional context in language processing is also quickly being filled. This is called AI Emotional Language Translation, and a few advanced chatbots have already begun to operate it. Emotional Language Translation is a technology that chatbots are now using to identify and interpret human emotions and nuances in language. Through this technology, AI is able to detect emotions, provide tailored responses and adapt their language in response to the emotion of the speaker.
Recent other advancements include developments in technology that is able to analyze sentiment by categorizing emotions into positive, negative and neutral. This, added to new computer vision and facial recognition programmes has led to the development of technologies that are slowly able to classify emotions. However, given that there are no urgent problems to be solved or no certain avenues for profit, this technology is slow to progress, and will advance when funding finds its way to it.
This will begin to change the dynamics of AI-Human interaction. With enhanced empathy, AI chats are no longer just sources of information. They may actually be able to provide users with company, thereby positively impacting their mental health. Given the growing loneliness epidemics in the modern world, some hopeful research has also been done to explore how AI can then be used to reduce loneliness. But beyond the more long term mental health goals we can have for AI, enhanced empathy will certainly make it easier for AI to provide personalized assistance.
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3. https://viso.ai/deep-learning/visual-emotion-ai-recognition/