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EQ Declines, How Business Leaders Can Leverage AI to Turn the Tides

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World’s EQ is Declining, but AI Can Help.

Over the past 50 years, emotional intelligence has declined globally. A 2018 ScienceAlert article by Peter Dockrill notes, “An analysis of some 730,000 results by the Ragnar Frisch Center for Economic Research in Norway reveals that the Flynn effect hit its peak for people born during the mid-1970s and has significantly declined ever since.” In other words, our EQ and IQ have been negatively impacted in our current world of technology – the rise of social media, always-on computing and an experience that neglects emotion.

Artificial intelligence has the potential to help humans improve not only their IQ, but their EQ as
well. However, vital components of human communication are often excluded when it comes to
technology, leading to a frustrating user experience, loss of valuable insights, premature or
uninformed decision making and ultimately a lower emotional awareness.

“We have a lot of neurons in our brain for social interactions. We’re born with some of those skills, and then we learn more. It makes sense to use technology to connect to our social brains, not just our analytical brains.” Stanford Professor Erik Brynjolfsson said. “Just like we can understand speech and machines can communicate in speech, we also understand and communicate with humor and other kinds of emotions. And machines that can speak that language — the language of emotions — are going to have better, more effective interactions with us.”

With the 4th Industrial Revolution in our wake, AI technology is learning to detect and interpret
verbal and non-verbal human emotional indicators such as tone, facial expressions and body
language. Algorithms have significantly improved due to advances in emotion detection, NLP, sentiment analysis, machine learning, and a greater combination with linguistics and psychology.

If Voice AI was the First Step, What’s Next?

Voice AI technology alone has already made its way into billions of end users’ hands through
innovations like Alexa, Siri, and Google Assistant. The voice technology industry is projected to
grow to a staggering $55B by 2026. With all these existing technologies at our fingertips, why
are we still getting frustrated when our messages are not heard?

The answer is simpler than we think. Existing technologies, are in essence, tone-deaf. They lack the ability to recognize the emotions behind our words. While our commands might be heard, our tone is not.

We may have incredible voice technologies that recognize and interpret the meaning behind
language and word choice, but we have also created machines that are missing part of the
picture. Words only make up 7% of human communication. Whereas tone of voice is the
number one passive indicator of what someone is thinking and accounts for nearly 40% of
human communication. A figure too high to ignore.

A new frontier of emotional understanding has arrived in the form of tonal analytics. Tone is
quickly becoming a standard necessity for automated analyses and the future of voice
communication. Voice is everywhere and conversational AI is growing exponentially. Tone, like
voice, is everywhere; however, tone is largely untapped. Tone of voice is needed to bridge the
gap between humans and machines. By incorporating tonal AI with other forms of conversational AI, such as text and body language software, a more comprehensive emotional understanding is generated. Together these technologies intelligently connect all facets of complex and unstructured data to paint a clearer picture of human communication.

Companies Leading the Way

Uniphore, a conversational AI unicorn, provides a customer service platform to improve corporate conversations across calls centers to through the sales process. Uniphore’s technology leverages voice AI, computer vision and tonal emotion. Today, the firm is valued at $2.5 billion with over $620 million in funding and is rapidly expanding internationally. Co-Founder, Umesh Sachdev, noted the importance of conversational intelligence, “Understanding conversations and the data and insights derived from them is essential to every business.” Conversations are only understood when all factors – word choice, body language, facial expressions and tone of voice – are taken into consideration.

Other, more medically-targeted voice AI companies, leverage the nuances in voice to help diagnose patients suffering from different diseases. Sonde Health analyzes vocal biomarkers to identify patients with Parkinson’s disease faster than ever before, allowing for quicker treatment. At CompanionMX, a phone application can help identify patients with depression by analyzing vocal patterns. The data generated builds a well-rounded concept of a patient’s mental state and the app format makes the technology more accessible to end users.

In the world of finance, startup Helios Life Enterprises is translating tonal nuances of executives’ voices into actionable insights to advance how investors make decisions. During earnings calls and other audio or video events, executives distribute a substantial amount of important information via speech. The tone of voice is a channel that leaks emotional information and it is extremely difficult to hide this. Helios is rapidly attracting attention in the finance industry due to its differentiated focus and the fact that it is the only company that generates tonal analytics of executives (more than 4K US equities). Helios accounts for those crucial tonal components necessary to being understood and has created an entirely new channel of insights within the alternative data space ($143.31 billion by 2030).

Consider Tone Today to Stay Ahead of Tomorrow’s Advances

From call centers to sales to medicine to finance, the use cases for tone are endless and the
question has become: how will tonal insights shape new industries and change existing ones?

As artificial intelligence develops a higher EQ via tonal insights, it is vital that leaders consider
how the technology will play a role in their firms and industries at large.