We recently connected with Shannon Brownlee and have shared our conversation below.
Shannon, appreciate you joining us today. What’s the backstory behind how you came up with the idea for your business?
When we first started working together, my cofounder and I were still in college, in the middle of the COVID pandemic. Having made the switch to fully virtual classes and social interactions, we felt like connecting with our peers and gauging how our friends were feeling became harder. Thus sparked the idea to build technology to foster human connection and emotional communication in digital spaces.
Our first iteration was an app that communicated emotional tone through haptics, helping people better understand emotions in real-time. After our initial rounds of building and testing, we realized that the potential applications of this technology are endless. Emotions can be difficult to decipher across neurotypes, cultures, languages, and demographics, and this technology can help navigate all of those interactions. The world we live in is rife with emotional miscommunication and in our increasingly digital and global societies, more and more people are struggling to understand how those around them feel. So, as we’ve grown, we’ve been able to expand our use cases into many different sectors, from accessibility to conversational analytics, and it’s exciting to see how interested others also are in making technology more empathetic.
Shannon, before we move on to more of these sorts of questions, can you take some time to bring our readers up to speed on you and what you do?
I’m Shannon, cofounder and CTO of Valence, an emotion AI startup. My background includes AI and software engineering across broad disciplines and markets. Formerly at Microsoft, Lucid Circuit, and research labs at the University of Southern California, I have worked on projects ranging from operating systems to neuroscience to machine learning to genomics to signal processing to ecology. I am the former president of the Center for AI in Society’s student branch, an organization focused on teaching AI and applying these concepts towards social good projects. I’ve been working on computational social good projects since I was a teenager, and I am passionate about using AI to promote human connection and public benefit. All of this led me to start Valence with the goal of using technology to help people better understand one another.
Valence AI is focused on vocal tone analysis for emotion classification of audio data. Rooted in accessibility, we aim to improve emotional understanding across broad demographics to help people and companies be more empathetic in their actions. Our main goal is to provide conversational analytics to help bridge the gap between what people say and how they feel. I see our technology as a tool that can push people and companies to understand and care more about how their actions impact others and to help create more compassionate and understanding AI systems.
How’d you meet your business partner?
Chloe and I met while living across from each other in our college dorms. She was studying computational neuroscience, and I was studying computer science and quantitative biology. We’d spend late hours in the study lounges together and nerd out about computational biology and new biotech advancements we’d seen in the news. Later on, when Chloe wanted to do a neurotech hackathon and she needed a partner, she knew exactly who to ask! My experience in programming and AI and my interest in computational biology, paired with her neuroscience knowledge, made us a perfect pair for the challenge. From there, we did our brainstorming and built the very beginnings of Valence. We had received so much support during the hackathon and a lot of interest in the tech after, so we decided to keep pushing the idea and build out our products.
We often hear about learning lessons – but just as important is unlearning lessons. Have you ever had to unlearn a lesson?
As young founders, we had to learn a lot about running a business and raising funding very quickly. We did this primarily through asking for advice and feedback from professors, investors, industry professionals, and other founders. Thanks to a lot of helpful advice from many experienced people, we were able to learn how to run a startup and grow into the founders we are today. But, at a certain point, we had to learn that not all advice is good advice.
Everybody we spoke to had a different opinion on how to use our technology, what markets to go after, and even if our tech was worth building. We had investors tell us that no one would pay for our product, and that we should pivot and build our tech into something else, and then go on to say that we wouldn’t succeed if we didn’t follow their suggestions. We had people say we put too much emphasis on data diversity, even though that is a main factor that sets us apart from competitors today. Early on, there were times when we got stuck trying to follow the advice of everyone and ended up making nobody (including ourselves) happy with the direction we were taking. Though these mentors had more experience, they didn’t know our product or our company better than us. We had to learn when to trust ourselves over the external comments of other people. Not everybody understood the moonshot of our technology, and that was okay. We realized that no one understood our products like we did, and we created better systems to prioritize our judgements within the hierarchy of opinions we were receiving.
Contact Info:
- Website: https://getvalenceai.com
- Linkedin: https://www.linkedin.com/in/shannonbrownlee
- Twitter: @getvalenceAI
