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This startup aims to improve workplace conversations with ’empathy as a service’ software

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This startup aims to improve workplace conversations with ’empathy as a service’ software
(Image from BigStock)

Most of us have had the experience of sending a text message or an email that seemed to sound insensitive or angry, although that was not our intention.

Unfortunately, the lack of social cues in such posts makes it much easier to be misunderstood. Depending on the communication, this can lead to misunderstandings, hurt feelings, or worse. That’s a Bellevue, Washington-based deficiency. pathetic wants to correct using empathic AI.

Drawing on knowledge and data sets gathered over the past decade, mpathic has set out to promote human connection and understanding in the workplace.

To do this, they have created plugins that relate to their cloud-based empathy as a service, or EaaS, to help humans talk to humans using real-time text corrections. In this way, text messages and emails can be reviewed and changes suggested before pressing “Send”. By adding these capabilities to platforms like Slack or Gmail, mpathic hopes to bring more empathy to the corporate communication landscape.

CEO and Co-Founder of mpathic Grin Lord. (photo mpatica)

“We realized that all of this could be mediated by an AI empathy engine, almost like Grammarly for empathy,” said the co-founder. Lord of the smile. “We’ve had amazing developments in AI that allow us to do this now in real time, so this is the first time in human history that we can get dynamic empathy correction in real time.”

In an example from a recent launch, the service suggested replacing an inflammatory message such as, “Why does Nic always schedule these meetings at the last minute? I’m right? with a more open question: “How do you feel about the meeting change?”

Based on years of research on human interaction, mpathic offers a unique approach to guiding users. Lord, who has a Doctor of Psychology degree, initially based the mpathic dataset on insights he gained from conducting research in the early 2000s at Harborview Medical Center in Seattle, the only Level I trauma center. in Washington state.

During that time, Lord was part of a group investigating empathic listening. After a car accident, DUI drivers frequently entered Harborview. Instead of giving drivers brochures or telling them what to do or embarrassing them, the researchers would listen to them, perhaps for 15 or 20 minutes, following specific protocols. In a randomized controlled trial, they saw a measurable drop in alcohol use by those drivers that lasted up to three years, as well as a 48% reduction in hospital readmissions. This not only helped the subject toward recovery, but also led to significant cost reductions, as well as increased public safety.

Since then, Lord has been involved with other startups, including Lyssn, a platform to assess the empathy and engagement of behavioral health providers during clinical sessions.

Before its release, the team behind mpathic started Empathy rocks, which builds a human connection using empathic AI through a gamified platform. The platform enables professionals to improve their empathic listening skills while earning continuing education credits.

But it was during Empathy Rocks’ initial seed funding stage that Lord and co-founder Nic Bertagnolli realized they already had a viable product in the underlying empathy engine for that platform. Spinning, they released mpathic to make the engine more available and more available.

By developing both “Grammarly for empathy” and an API, mpathic wants to do more than just promote good employee relationships. Given the expanding globalization of many corporations and the growing pool of employees from other parts of the country and the world, mpathic wants to provide human resources departments with a tool that can help facilitate employee onboarding. Since different regions have different ideas and attitudes about what constitutes civil and sensitive behavior, mpathic can be used to help you more quickly integrate new hires into your new team.

Lord is quick to point out that mpathic not only suggests text corrections, but also makes other kinds of behavioral suggestions. In this way, the user builds an understanding of empathic communication and behavior through context, use, and repetition.

“In fact, we make corrections that are very behavioral,” Lord said. “So it may not even be a word replacement or text transformation. Instead, the AI ​​may suggest calling a meeting or talking on the phone, because certain things don’t need to be in an email. “

Although mpathic grew out of Empathy Rocks, the gamified training platform continues to provide empathic listening training as it acquires new data that is used to train mpathic’s EaaS. The platform was designed by the team’s empathy designer, Dr. Jolley Paige, who points out the many factors that need to be considered at a time when AI bias is a concern.

“We were thinking about gender, age, culture, where you are in the country, but also different abilities,” Jolley said. “So if someone has a language processing disorder, how would that affect the way they interact with this game?”

While some people may have concerns about using artificial intelligence to modify human behavior, many companies see the value of this approach. “Some of our early business partners are looking to connect mpathic on their Slack, Gmail or whatever, mainly because they are interested in this idea of ​​rapidly incorporating cross-cultural and global teams,” Lord said. “I think it can be useful to unify the language of mission values ​​of a company.”

Last month, mpathic was one of 14 startups that launched at PIE Demo Day. CAKE (Portland incubator experiment) is led by CEO Rick Turoczy and seeks to provide founders, often first-time entrepreneurs, access to mentors and networks.

Empathy Rocks and mpathic intentionally obtain and curate their data to include underrepresented voices and are part of All technology is human as well as other communities committed to the ethical development of AI.

Empathic AI is part of a much broader field of computing, known as affective computing and more recently as emotional AI or artificial emotional intelligence. Originating from the MIT Media Lab and other research institutes some 25 years ago, AI for emotions involves systems that can read, interpret, and interact with human emotions. Since emotion and especially empathy are central to the human condition, such work has the potential to make our technologies interact more easily, humanely and responsibly with people, both at home and in the workplace.

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