Emotion AI: CX's Next Frontier?
Sentiment-driven CX has been tagged as one of the top CX trends in 2024. (If you’re not familiar with sentiment analysis, it’s basically using AI to identify trends in consumers’ feelings, often via text data. The Around the Web article on Using Sentiment Analysis for Insight-Driven CX will give you a thorough background on the subject.)
Understanding what people think and feel about your business / product / service / experience is essential to meeting their needs. With the shakeup around generative AI in 2023, many CXers are wondering what impact Emotion AI (aka affective computing) will have in 2024 and beyond.
What is Emotion AI?
AI is a broad term that entails training machines to reason and carry out tasks in a similar way to humans. Emotion AI is a subdiscipline of AI that deals with training machines to recognize, respond to, and even replicate human emotions. The ability to respond to and simulate emotion is what sets emotion AI apart from sentiment analysis, which is mostly concerned with identifying and classifying emotions.
Is Emotion AI a thing? Yes, it is – albeit a thing that’s still in its practical infancy. It’s not as widespread as analytical or even generative AI, but there are several current examples of its use. These include monitoring customers’ reactions to advertisements (with the customers’ explicit consent) and helping people identify moments of stress and use calming techniques to de-escalate.
For human-focused fields like CX, it’s easy to see how Emotion AI can make customer service (and particularly customer-facing chatbots) more sensitive to users’ needs. But before we start advocating wholesale embedding of emotion AI in all processes, there are limitations and potential problems to examine.
Ethical and practical considerations
If you’ve been experimenting with ChatGPT or similar programs, you’ll know the first potential problem with Emotion AI: it can produce flawed results. We’ve seen this over and over again, from Amazon’s AI-powered hiring tool that was biased towards male applicants to speech recognition systems that struggle to understand Black speakers. Obviously, there are very negative potential consequences if AI is not trained and used appropriately.
In addition to the usual privacy and consent concerns that surround AI, Emotion AI comes with critical issues around mental and emotional health – and health-related data. Even with user consent, this has the potential to be an ethical, legal, and regulatory minefield.
So, what’s the takeaway for CX professionals? Keep an eye on Emotion AI – but take a “wait and see” approach before you embed it in your CX processes.
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