Emotional intelligence allows a leader to channelize team members as per their strength and make the project successful. Gartner VP Annette Zimmermann claimed that your personal device will understand your mental situation more than the loved ones. Moreover, the affective computing market has a growth potential of $41 billion by 2022. Amazon, Google, Facebook, and Apple would be the major investors. In this article at Harvard Business Review, Sophie Kleber discusses how AI is gaining ground in emotional intelligence (EQ).
Working on Emotional Intelligence
Two months after Zimmermann’s declaration, University of Ohio announced that their algorithms can understand emotions better. Affectiva, BeyondVerbal, and Sensay have developed sentiment analysis software. Facial analysis, voice pattern analysis, and deep learning are helping AI to understand emotional intelligence. Though brands might connect more with customers, this also raises privacy concerns. So, before you avail the emotionally intelligent applications, ask yourself these questions:
- Will knowing the customer’s emotions help you serve them better?
- What kind of interactions do you generally encounter from the customers?
- Do your customers know that you are analyzing and story their emotional data for your reference? If they have given permission, can they control what data and withdraw support when needed?
- Will your system catch the nuances of human emotions perfectly by integrating these applications?
- What are the challenges you might face if the system crashes? Who will pay the price—the brand or the user?
Following are the three types of applications that can read emotional intelligence:
Detecting Emotions: These AI applications adjust their responses as per the emotions they detect. Conversational IVRs and chatbots can directly route the customers to the escalation channels when they detect anger. Affectiva’s AutoEmotive and Ford are launching cars that could take over when their AI detects anger or unfocused mind. This would reduce accidents or violence.
Analyzing Emotions: Philips and a Dutch bank launched Rationalizer, a bracelet that could heightened emotions, in 2009. This would monitor the stress of the wearer by analyzing the pulse. It would stop a trader from making impulsive decisions. Brain Power’s smart glasses allow citizens with autism to understand the emotional and social cues easily. This type of applications would identify the emotions and communicate with the wearer. Emotional learning systems help understand the emotional intelligence of the group.
Impersonating Emotions: AI services use “I” to socialize better with the customers. These applications use behavioral therapy to guide people undergoing an emotional crisis. For example, While Ellie helps soldiers with PTSD issues, Karim soothes traumatized Syrian refugees. Digital assistants also help elderly citizens to feel less lonely. Microsoft’s XiaoIce, Google Assistant, and Amazon’s Alexa are more commercially inclined, though.
There is a fine line between service and privacy encroachment. Designers and brands must brainstorm, analyze, experiment to find the perfect balance.
To view the original article in full, visit the following link: https://hbr.org/2018/07/3-ways-ai-is-getting-more-emotional