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Welcome to the latest edition of AI Weekly. This week, issues and innovations related to conversational AI and emotion AI were everywhere.
Here at VentureBeat, we discussed these issues:
- Why conversational AI is an effective listening tool
- How conversational AI makes customer service smarter
- A report that found that conversational AI bots should unify calling, messaging and analytics
Meanwhile, my latest feature, Emotion AI’s risks and rewards: 4 tips to use it responsibly, explores recent pushback around the use and evolution of emotion AI, which includes technologies such as voice-based emotion analysis and computer vision-based facial expression detection.
Two interesting discussions that I didn’t include in the story:
- Is emotion AI simply the next evolution of conversational AI?
Uniphore, a conversational AI company with headquarters in Palo Alto, California and India, is enjoying unicorn status after announcing $400 million in new funding and a $2.5 billion valuation back in February. In January 2021, the company acquired Emotion Research Lab, which uses “advanced facial emotion recognition and eye-tracking technology to capture and analyze interactions over video in real-time to enhance engagement between people.” Last month, it introduced its Q for Sales solution, which “leverages computer vision, tonal analysis, automatic speech recognition and natural language processing to capture and make recommendations on the full emotional spectrum of sales conversations to boost close rates and performance of sales teams.”
But computer scientist and famously fired-Googler Timnit Gebru, who founded an independent AI ethics research institute in December 2021, was critical of Uniphore’s claims on Twitter. “The trend of embedding pseudoscience into ‘AI systems’ is such a big one,” she said.
“Emotion AI is simply the next evolution of conversational AI.” That’s what Patrick Ehlen, VP of artificial intelligence of Uniphore, told me by email.“We believe that context is critical in human conversations, and by combining all of the modes of communication used for real-time human interactions, people and business will benefit from additional insights provided by conversational AI and automation solutions,” he said. “This is especially true in sales and customer success interactions where listening and understanding are mission critical for enterprise sales and customer retention.”
- Is emotion AI headed for the metaverse?
Chatter and coverage around digital avatars is everywhere at the moment. For example, this week VentureBeat’s Taryn Plumb covered Hour One’s efforts to use custom digital avatars to transform the future of work.
But the growing connection between digital avatars and emotion AI, leading to the possible emergence of virtual emotional beings, is a “fascinating” development, said Annette Zimmerman, VP analyst at Gartner.
“It’s still probably going to take a decade to evolve into a mature metaverse, but when it does, these virtual beings that project emotions are going to be a really important part of that,” she said. “At some point…you might not be able to distinguish whether you are sitting in front of a real person or an avatar.”
Theresa Kushner, data and analytics practice lead at NTT Data Services, also told me that she considers using emotion AI in conjunction with avatars that can respond like human beings is an “exciting” future use case.
“Digital humans can pick up on your unhappiness and, if programmed appropriately, respond in a way that alleviates said unhappiness,” she said. “Unlike real humans, digital humans never tire and don’t get irritated after a 10-hour shift – which is particularly important for customer service and experience. Another application for a better world might be if emotion AI could help identify people whose depression may lead to self-harm. This would particularly be helpful for call-in hotlines and online support, and allow these lifesaving resource centers to more easily identify at-risk individuals and respond accordingly.”
Thanks for reading,
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