While technology that deals with those feelings have come a long way when you talk to ai, it is far from perfect. Natural Language Processing (NLP) has come a long way in recent years and this advancement in NLP plays an important role for AI systems to understand emotion. Consider IBM Watson who uses NLP algorithms to identify emotions of humans based on their tone, wordings and even expressions during a video call. Watson can identify an emotional state in a conversation with around 80% accuracy, meaning there is still work to be done but progress made on the way, according to a 2023 study from MIT.
Sentiment analysis is an important part of how Ai handles emotions. Sentiment analysisAI can analyze patterns of text or speech to find out whether a conversation is positive, negative or neutral. For example chatbots like customer service ones can easily analyse from a users language if they are annoyed or happy and that can change what that chatbot says next. Salesforce research shows 67% of consumers expect AI to understand emotional cues in an interaction, signaling a growing expectation for emotional intelligence from algorithms.
If the AI detects some emotion of sadness or frustration, it can change its responses to show empathy. Antipodes like Woebot — an AI for mental health — responds to users in ways that echo compassion when people are emotionally vulnerable, utilizing the principles espoused by cognitive-behavioral therapy (CBT). According to the 2022 Woebot survey, 87% of Woebot users felt that "Woebot genuinely cared about how I was feeling." It illustrates the potential of AI to hold space for nuance and complexity – responding with empathy at the right level, rather than just ramming stuff down our throats in challenging conversations.
But does AI truly understand the nuances of human emotion — grief, anxiety? AI systems are improving but they will never feel like human beings. Researchers at Stanford recently found that even modern NLP models fail to understand context in emotionally dense scenarios (Stanford). For instance, in the case of someone who is grieving, their emotions may be expressed in a non-linear, fragmented style that does not align neatly with the logical constructs of AI programming.
Similarly, AI improves its understanding of how emotions work by incorporating feedback loops. AI gets better at this over time the more data it processes — adapting to emotional states. An example includes Amazon's Alexa, where feedback suggests the assistant now identifies mood transition according to tone of voice. According to a Statista survey in 2022, three-quarters of Alexa customers told they believed the AI was getting smarter with time and improving answers as the system learned.
Even the most advanced AI of today still falls short in its ability to process nuanced emotion. Either way, AI continues to advance — and with improvements in NLP and sentiment analysis — it will get better at engaging us emotionally. Interacting with ai is like talking to an intelligent person (even if we know that it is still a cutting-edge technology, we can tell that slowly but surely for certain types of questions or tasks this machine begins responding appropriately); who adjusts their non-verbal messages in reaction to our body movements and facial expressions.