Communicating With Humans and Machines

Meet New MOST Policy Fellow and Missouri Scientist, Hannah Elder

Hannah Elder is MOST’s newest policy fellow focusing on employment security and insurancewith the Missouri Department of Labor and Industrial Relations. She is working to organize large amounts of data to be more useful for the Department of Labor employees.

“I’m helping their internal staff create a dashboard so it’s easier to navigate and make decisions based on the data that’s here,” Hannah said.

The Department of Labor’s data concerns a variety of factors and information based on unemployment throughout Missouri.

“Since this is a completely new position, I’m trying to figure out how to best support them in this project,” Hannah said. “This past week I’ve been focused on analyzing the amount of data they have and doing everything I can to understand and master the process of unemployment.” 

Hannah’s educational background gave her the tools she needed to tackle such a broad and complicated undertaking. She received her bachelor’s degree in psychology from the University of Münster, located in Münster, Germany. This program sparked her interest in human factors, or ergonomics, in which she is pursuing her master’s degree. 

Hannah discovered the field of human factors while researching a paper for her undergraduate degree. She describes human factors as the intersection between engineering and psychology, mostly focusing on how humans and machines interact. 

“A lot of what I look at is how you design an interface so that people can interact with it intuitively,” Hannah said. 

Hannah is currently a research scholar at the Missouri University of Science and Technology in Rolla, Missouri working on her master’s thesis that tests how people react to recommendations from artificial intelligence (AI). 

“An AI recommendation can be anything now,” Hannah said. “If you ask Alexa what the weather is going to be today and she says it’ll be rainy, then the question is are you going to take an umbrella or not?”

There are many ways that AI systems communicate with people, whether that be through code, written language, or speech like Amazon’s Alexa. 

“It’s amazing to see all the studies out there about AI and human interaction,” Hannah said. “It doesn’t matter if it’s an Alexa or a more complicated system like a self-driving car, I’m focused on how people engage with the system or how they react when the system makes a mistake.”

She is combining this with her lifelong passion for basketball by studying how people react to an AI recommending which basketball team to place a bet on as part of her master’s thesis.

“With MOST and the Department of Labor I get to interact more with the numbers side of things, data crunching and mathematics,” Hannah said. “For my studies I got to focus on the output of the AI and how those numbers were communicated to the user.”

This communication varies by the audience and the information, sometimes it’s more helpful for a bar chart to be used while other times, a video or a sentence would communicate the message better.

“The reason I’m so passionate about my studies is that I can actually create something physically that helps people do their job,” Hannah said. “I felt like I was lacking the physical creation component when I was in my undergraduate classes. With human factors I can create a physical outcome, like the dashboard to streamline communication for the Department of Labor.”

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