Michelle Zhou, Co-founder & CEO, Juji -
Chatbots get more human
We all know what it’s like talking to a chatbot. Or, dealing with an automated customer service phone assistant (and ending up yelling, “Representative!” in frustration just to speak to a human being!). Either way, the robot on the other end doesn’t really understand and treat us like a human. But what if it did? What if it had human “soft skills,” like empathy and humor? What if it actively listened and could read between the lines of your semantic subtleties? And, what if, like humans, it learned and got better at listening to and understanding you? That is exactly what Michelle Zhou has created. A computer scientist by training and an expert in human-centered AI, Michelle is the co-founder and CEO of Juji, a company that’s aiming to be “The Apple of AI” by building the world’s only no-code AI cognitive chatbot assistants. She previously spent 15 years working at IBM Research and is the inventor of IBM Watson Personality Insights. Michelle joins the podcast to talk about how she’s creating no-code AI chatbots that feel and act more human – and her mission to democratize AI so that it’s easy and affordable enough for any organization (or any person) to use.
LISTEN TO THIS EPISODE TO LEARN:
- Concerns over the growing “AI divide” between organizations that can afford expensive and scarce AI resources and those that can’t – and the consequences of letting this divide grow
- How cognitive AI assistants must have the right training data and use continuous observation to understand inherently human aspects of language and intention
- Why the most useful AI comes from “good stock” (the good genes of AI) and must be tended to with the right tools to maintain it
- Why it’s good practice to be upfront with customers that they’re talking to a chatbot, rather than trick them into thinking they’re talking to a human (hint: transparency helps set the right user expectations!)
- Minimizing the potential harm of algorithmic bias in AI with diverse sets of data from diverse populations in diverse contexts
- The need for sound policies and regulations that can mitigate AI’s ethical risks
- Where AI is headed next and the broader applications of this technology beyond chatbots in the years to come in areas like health care, education, and human resources
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