Freddie Kato
Computers are everywhere. One day, robots will be, too. But who decides what computers and robots can do? As Freddie Kato’s students at Governors State University (GSU) quickly learn, it might be up to them.
A University Lecturer in Computer Science, Kato cheerfully brings 20 years of experience in the field, as well as a passion for artificial intelligence, which piqued his interest when he was a child. “I got interested and involved with computers and computer science because I’ve always been a sci-fi buff,” he said. “I recently built a small robot that I’m still refining. And I’m refining requirements for achieving artificial cognizance—getting computers to the point where they can not only regurgitate information they’ve been given, but that they can extrapolate more of the meaning, like we do.”
Kato also understands what it’s like to be a student at GSU, where he earned his bachelor’s and master’s degrees while working full-time in a booming Computer Science industry. With three years of college completed, he took a job at Sears to make money to finish his degree. But the position turned into an interesting full-time job that led to him developing critical computer systems for the Sears launched Discover Card.
“In this field, there’s always something new, something you’re learning. There’s never going to be a good time to go back to school. You just have to decide you’re going to do it.”
He enrolled in GSU’s Interdisciplinary Studies program, earning substantial course credit for all his corporate experience, and decided to pursue his master’s degree there as well. “I had fun coming back to class,” Kato said. “I was getting more detail about things I had been working with in industry. I remember taking the class on data structures and algorithm analysis. I was like, ‘Wow, if I’d had this course just a few years ago, it would’ve taken me through some projects faster.’
The class is among the courses Kato now teaches.
GSU Newsroom: How did you decide to switch from your industry to teaching?
Kato: I was always good at explaining things, even in grade school. However, I had other things I wanted to do first. After Discover Card, I worked at a number of small companies and then at Ernst & Young, which was known for accounting but was starting a side company for computer development. I’d always wanted to work for Lucent Technologies. After about a year, they downsized and shelved the research department, where I worked.
I had 20-plus years of industry experience and had always wanted to get into teaching, so I became a part-time teacher at City Colleges of Chicago, then went full-time there, which gave me a foundation for moving on to a university. I did advising, workshops and tutoring, which helped prepare me for GSU. I came on as an adjunct for the summer in 2015, then went full-time that fall.
GSU Newsroom: What are you working on in the classroom?
Kato: I teach data structures and algorithms, which are ways to format your data that you’re going to process. And I teach certain programming languages, which go hand in hand with that course.
I teach artificial intelligence (AI) for grad students. These days, AI has picked up in the industry so undergrads need an intro to that, and I’m developing the requirements for that class. I also teach machine learning, which falls under AI. It’s a special topics course now and I’m writing requirements for it to be listed in the catalog for both grads and undergrads.
GSU Newsroom: You develop the senior capstone project, a new course. How is it different?
Kato: This is “show me what you can do with what you learned in class.” Students come up with their own projects. In some classes, we just brainstorm. Students come in with a problem, and some other students chime in and say, “I had that problem, too, and a buddy showed me this site.” They start exchanging information so much that I’m just facilitating.
Unless they really get stuck in the mud, I encourage them to figure it out. Yes, it’s difficult. But it’s not too difficult.
That’s going to be what charges them up—solving the problem. When you get out there, employers don’t expect you to know it all. They expect you to leverage what you know to get the job done. I’ve had students say, “I’m about to graduate and I’m terrified of the interviews, so can we do a mock interview?” But once we started the senior capstone project, students were saying, “I can’t wait for them to say, “Tell me about a project you did.”
GSU Newsroom: Where are we headed with artificial intelligence and robots?
Kato: You can have intelligence and knowledge, but understanding is different. For instance, you can ask Siri questions and she might respond right to the first or second one. But by the time you get to the third or fourth question, Siri starts giving answers that don’t make sense because Siri can’t follow a conversation. That’s the goal of artificial cognizance, and refining requirements is the first step, so, I’m refining my master’s thesis on artificial intelligence.