For years, AI has already been criticized for its inability to respond to intricate feelings. By 2023, Artificial Intelligence systems (AI) like OpenAIs GPT-3 or GPT-4 will understand and mimic a wide variety of human emotions derived from the text. But those are just patterns from data they were trained on — not an expression that understands feelings. According to studies of AI responses in emotional contexts, greater than 80% of responses are focused on empathy and support using comforting phrases or guidance.
The ability to mimic emotional intelligence is referred to in industry as affective computing. This is something that big companies like IBM, and Google have progressed in doing with AI applying reasoning and sentiment analysis to produce responses logically. For instance, there have been mental health applications devised with the help of AI-powered IBM Watson — with these applications providing some therapeutic conversations to users — but often accompanied by warning that AI lacks the depth of human-based therapy engagement.
Dr. Rosalind Picard, a pioneer of affective computing explained it as: "Artificial intelligence is not so much about imitating feelings but knowing what to say and do and free to respond in whatever way they can." It gives users an outlet to seek assistance during stressful or challenging experiences, but keep in mind that the AI still doesn't "feel" anything.
When you are talking to AI about complicated emotions, then the system is using data sources and algorithms to provide a contextual and useful response. As an example, the AI systems need to pick clues like Sadness and then respond with empathy. Some AI chatbots that communicated with empathy gained 30% more user satisfaction in customer services, according to a study by MIT researchers.
But the emotional depth AI can provide is limited. It may be able duplicitously simulate an understanding of emotion — even offer up resources like self-care tips or suggestions on how to practice mindfulness — but it does not hold a candle to the complex emotional intelligence that human beings possess. In actuality, for instance, just 15 percent of AI models applied in healthcare include elaborate emotional reactions; such models more frequently provide logistical or informational assistance.
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