Nicholas Gahman loves the challenge of exploring new frontiers in technology.
"I feel like I have the most fun when I'm out in the wilderness. I have no idea what I'm doing, and I have to figure something out," he said.
His undergraduate courses in machine learning and artificial intelligence (AI) sparked his interest in learning more about these novel tools. As a Schreyer Honors student at Penn State Abington, he was able to create his own custom integrated undergraduate/graduate degree, combining his bachelor's in computer science with a master of AI through Penn State Great Valley.
"All of the professors are really enthusiastic," Gahman said. "They genuinely seem to love what they do, and they seem to love us, the students. And so when they encourage us and teach us things, and we work with them, we get infected by that enthusiasm."
He said he enjoyed the challenge of his capstone project, in which he and a team of classmates investigated whether machine learning models could accurately reduce the number of cybersecurity alerts that professional analysts needed to triage. Gahman and his team used hyper-parameter tuning to train machine learning models on a large hierarchical dataset of cybersecurity incidents to predict whether a given incident was a benign alert or an actively malicious cyberattack.
"These results indicate that integrating machine learning into cybersecurity workflows can significantly reduce the workload on human analysts and improve the scalability of incident response systems," Gahman and his team wrote.
Through hands-on projects like this one, Gahman said he has become more proficient at dataset cleaning and selecting and implementing appropriate AI models for specific tasks. This experience has given him a deeper understanding of the principles of AI and how training works, he said.
"I feel like [the master's program] gave me the tools to understand what was happening. AI wasn't so much of a black box," he said. "You have to understand why it comes to a given conclusion."
Otherwise, he said, people may uncritically accept the output an AI tool gives them, without considering how reliable it is.
Gahman mentioned the classic example of an AI-powered job applicant tracking system that uses historical data about employees to identify traits to help select future employees. If the data came from companies that discriminated against diverse populations in their hiring practices, the system could take irrelevant demographic data, such as race, gender and sexual orientation, and perpetuate human biases by continuing to deny job opportunities to minoritized groups. Or the system could make a variety of mistakes and draw inaccurate conclusions from the data, leading to poor decisions, Gahman said.
"There are so many good things about AI, but there's also a lot of risk," Gahman said. "The ethics of AI course that I took gave me a lot of food for thought about how to use AI responsibly."
AI explainability, or understanding why AI tools come to a certain conclusion, is one of the keys he learned in his ethics course for mitigating risks and improving the tools' performance.
"The only real way to prevent AI from making poor or unjust decisions in these complex situations is to know why the AI is making a decision, so its decision can be thrown out if the reasoning is faulty," he said.
With an awareness of its potential pitfalls, Gahman said he is amazed by the power of AI and its myriad applications - automated driving, cancer and disease detection, stock market predictions, language translations and much more.
"It's affecting our lives in all sorts of ways. There's so much about it that's cool, and there are so many things it could be used for. We're sort of living in science fiction," he said.
Gahman finished his master's degree last December and landed a job in the space industry at Lockheed Martin as an AI research engineer, which he began this month.
"It's kind of my dream job. I'm going to be learning so much, and it's going to be so much fun and so interesting," he said. "I am more than happy to be on the cutting edge of technology. I'm very much looking forward to being able to use my skills in real-world situations, out in that 'wilderness.'"
