As businesses increasingly embed AI in our operations, one unexpected trend is the rise of “emotion AI”—technology designed to help AI better understand human emotions. According to a recent Enterprise SaaS Emerging Tech Research report from PitchBook, this technology is gaining traction as companies seek ways to make their AI bots more emotionally intelligent.
Emotion AI builds upon sentiment analysis, a precursor technology that distills human emotions from text-based interactions, particularly on social media. But emotion AI takes this further, employing visual, audio, and or sensors alongside machine learning and psychological insights to detect and interpret human emotions during interactions.
the reasoning is simple: with AI increasingly playing roles in customer service, sales, and even executive assistance, the bots need to differentiate between an angry tone and a confused one to function effectively.
New Wave of Emotion AI in the Workplace
Companies are starting to deploy emotion AI to enhance human-AI interactions, enabling more sophisticated responses from bots. PitchBook’s Derek Hernandez, senior analyst of emerging technology, writes that emotional AI will play a crucial role in future workplaces by providing “more human-like interpretations and responses” through AI assistants and bots.
Major AI providers like Microsoft and Amazon already offer emotional AI services. For instance, Microsoft Azure’s Emotion API and Amazon Web Services Rekognition service are examples of how developers can integrate emotion AI into our platforms. While these tools aren’t new, the rise of AI in the workforce has given emotion AI more significance and potential.
Hardware Behind Emotion AI
Cameras and microphones are critical to hardware powering emotion AI, and they can be found in devices like laptops, smartphones, or even wearables. Hernandez also suggests that as emotion AI expands, it could make use of wearable hardware to enhance its capabilities beyond standard devices. This could mean that your customer service chatbot might ask for camera access to better gauge your emotions.
Several startups are emerging in this field, including Uniphore, MorphCast, Voicesense, Superceed, Siena AI, audEERING, and Opsis. Some of the companies have already raised significant funding, with Uniphore leading the pack with $610 million in total, including a $400 million raise in 2022.
Challenges of Emotion AI
Despite the excitement around emotional AI, challenges remain. Some researchers question the very premise of technology, arguing that human emotion cannot be accurately determined by facial movements alone. In a 2019 meta-review, researchers highlighted the limitations of trying to detect emotions based on facial expressions, body language, or tone of voice.
Furthermore, regulation could pose a significant hurdle. European Union’s AI Act already bans the use of emotion detection systems in certain sectors, such as education, while U.S. state laws like Illinois’ Biometric Information Privacy Act (BIPA) prohibit the collection of biometric data without consent.
Future of AI in the Workplace
As emotional AI continues to evolve, its impact on the workplace remains uncertain. Businesses are keen to implement emotionally intelligent bots to handle tasks like customer service and HR. However, the effectiveness of such systems remains to be seen. If emotion AI falls short of expectations, businesses may be left with bots that resemble the likes of Siri from 2023—helpful but far from understanding human emotions.
As Silicon Valley races toward this AI-everywhere future, only time will tell if emotional AI becomes an integral part of the modern workplace or a well-intentioned technology that fails to deliver on its promise.
