Editor’s word: Throughout the 2025-26 tutorial 12 months, RED’s Future-proof collection will concentrate on real-world outcomes, neighborhood wants and the essential function public universities play in making ready college students for the roles of tomorrow.
Angela Fleenor mastered the artwork of precisely capturing and captioning spoken language in court docket reporting college, solely to have her profession plans disrupted by the arrival of latest automated know-how.
“I initially went into it because I wanted to do captioning,” she mentioned, “but AI and voice recognition software have mostly replaced live captioners.”
These days, Fleenor, a senior majoring in Computer Science at Metropolitan State University of Denver, is feeling a way of déjà vu as enterprise leaders lay off workers and switch to synthetic intelligence instruments to write code, diminishing the necessity for brand new programmer hires.
“I feel apprehensive,” she mentioned, relating to her job prospects after commencement subsequent spring. “I don’t have statistics right now, but I believe the layoffs have disproportionately affected women in tech. I feel nervous about it.”
A labor market report from the Federal Reserve Bank of New York lends weight to Fleenor’s concern. Recent pc science graduates face the next unemployment price, about 6%, than these getting into different professions.
While the times of Computer Science majors being assured of good-paying entry-level positions coding software program may quickly be a distant reminiscence, there’s no cause to panic, mentioned Daniel Pittman, Ph.D., affiliate professor in MSU Denver’s Department of Computer Sciences.
“We can do more with fewer people now in intro-level programming jobs because AI can automate, but that does not eliminate the profession of software development,” he mentioned. “It doesn’t eliminate the human, but it does make the humans that remain more efficient.”
But the excitement round AI is driving many companies to undertake the know-how with out totally appreciating potential downsides, Pittman mentioned.
“These CEOs go out there and say, ‘We don’t need an intro-level programmer anymore,’” he mentioned. “You can say that all you want, and maybe for a little while, that’s going to be fine. But then all these senior developers are going to retire, and then what? You’re like, ‘Well, I need somebody to replace them,’ but they gave nobody a chance to get any experience. So that’s not a sustainable statement.”
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When AI is used to write code, it attracts on an unlimited trove of on-line information, basically predicting what the following component in a set of directions needs to be. While the blinding pace with which it generates content material might speed up undertaking completion, it isn’t all the time correct, Pittman mentioned, and that implies that there’ll all the time be a requirement for individuals skilled in pc science who can spot the errors.
Pittman’s assurances however, Fleenor’s fellow Computer Science main Monica Ball and Emma Tran, a sophomore Biology main with a Computer Science minor, share her apprehension and voiced some skepticism concerning the widespread embrace of AI.
“I’m not sure that it will be long-term financially viable to shift everything to AI for software development,” Ball mentioned. “I also think that a lot of code that gets created is not always going to be very secure. You’re always going to need someone else checking through it to make sure it does what you think it does, how you think it does it, and it does it without compromising any of the ‘CIA triad’ — confidentiality, integrity and availability.”
Tran famous that as a result of generative AI remains to be new and imperfect, enterprise leaders needs to be cautious about embracing it.
“It’s still being tested and looked at and criticized,” she mentioned. “It’s something that’s in development. I think that when people think we should just ditch everything and rely on it, that is kind of pushing it.”
Two years in the past, in anticipation of the AI revolution, the division of Computer Sciences added a serious in Data Science and Machine Learning, and beginning subsequent semester will launch a serious in Computer Security, Pittman mentioned, including that planning for the DSML main had been underway when he joined the division 4 years in the past.
“The DSML degree has been pretty timely,” he mentioned. “Before ChatGPT was really a thing, they were creating this degree because we knew that people were using other forms of AI to make sense of their data.”
The Computer Security main likewise builds on the truth that AI was already getting used to detect threats and anomalous on-line habits, Pittman mentioned. Large language fashions reminiscent of ChatGPT even have a task to play in serving to firms and establishments discover the appropriate stability of safety for his or her programs.
“How much money do you want to invest in security versus how much risk exposure do you want to have? It’s a classic conversation, because no one wants to spend money on security,” he mentioned.
Despite these efforts to broaden course choices, may the continuing AI-driven transformation of data know-how render pc science majors’ skillsets out of date inside a number of years?
“First and foremost, I’d say computer scientists are trained to be problem solvers,” Pittman mentioned. “That’s really what we try to make our students understand. It’s not about learning one programming language. It’s not about learning one tool because tools do change, especially in software.”
That identical problem-solving skill might be important sooner or later, he mentioned. “It’s just instead of you handwriting everything, it might be more in collaboration with an AI, generating something together and then assessing its correctness for what you’re trying to do.”
Learn extra concerning the Computer Science program at MSU Denver