How does someone pivot from a career in teaching English as a foreign language to designing conversational AI systems? For Tara Nair, the transition required a keen understanding of how humans use language to communicate.
Tara analyzes the way people naturally communicate and creating the strategy for training AI to understand these linguistic patterns. “I would say my teaching experience has been very applicable for understanding and assessing users,” Tara says. “As a designer I have to consider my users’ mental models. What do they understand about the interaction? How can I design an experience that takes into account what my users know and what they want to get done?”
Tara believes that the key to creating successful AI solutions is ensuring that the design is intuitive and valuable to its users, which requires user research and strategic planning.
“I used a similar process as a teacher by assessing the needs of my students and creating my lesson plans to address their knowledge gaps,” Tara explains. “It’s about understanding the person on the other side. I think I have a strength in that, which was honed by my teaching experience.”
The transition wasn’t always a natural one. When Tara moved to a career in AI, she had a lot to learn in short order. Before Charles Schwab, her position as an intent recognition designer at Amelia, an IPsoft Company, was a relatively new role that has evolved as AI technology has matured. While Tara grew her understanding of intent recognition through guidance from her expert teammates and lots of trial and error, she noticed there was an opportunity to improve her work with Amelia clients.
“I saw that as something we could improve to give [Amelia] clients better training as well,” she says. “They’re implementing Amelia but they don’t always have a full picture of how to select the best use cases or how to organize their data before putting it into Amelia. We could facilitate that by developing some more training on the design process [and] on intent recognition.”
Future Opportunities for Education and AI
Although Tara enjoyed teaching, she wanted to apply her graduate degree in Applied Linguistics to innovative work. She viewed NLP (natural language processing) as the new frontier in the sphere of linguistics, and she wanted to be part of the latest advancements that connect the way humans and machines communicate.
Now that she has professional experience in education and AI design, Tara sees additional crossover potential for the two fields. “I see AI benefitting the field of education by synthesizing classroom data to allow teachers to better understand their students’ progress and gather feedback on engagement,” she says. “Teachers can use this information to create more personalized learning plans for students.”
Tara also sees potential for AI to streamline teachers’ many administrative tasks, some of which need to be done on personal time due to demands in the classroom. This includes items such as documenting lesson plans, filing behavioral reports, writing assessments and more. “Having tools that allow these jobs to be done more efficiently gives teachers time back to focus on what’s happening in the classroom,” she says.
Luckily for teachers, one of their own is on the frontlines of AI design making this vision a reality.