The Role of AI in the Future of Coding and Higher Education
The decision to major in English can be put to the test if you have a diverse family background or pragmatic relatives who question its practicality. As a college freshman, my extended family of Salvadoran immigrants and midwesterners doubted that being able to recite Chaucer in Middle English would secure a job that could help me pay off my student loans and save for retirement. Despite their concerns, I pursued my passion for English. However, when the Great Recession hit and I found myself graduating with a B.A., their worries seemed justified.
Computer science and STEM degrees have long been seen as the safest paths to job security in the 21st century, while degrees in English were often dismissed as less lucrative. The tech industry offered abundant coding jobs with competitive salaries, especially when compared to mid-career English graduates. According to the Federal Reserve, the average starting salary for someone with a computer science degree far exceeds that of an English major. Entry-level software engineers at companies like Google reportedly make $184,000, not to mention the additional perks such as free meals and massages. The rise of computer science and STEM has significantly influenced higher education over the past two decades, leading to a decline in humanities enrollments across the United States and the potential elimination of entire departments.
However, the advent of generative AI, specifically chatbots like ChatGPT, has shifted the landscape. These AI systems can now compose full essays in an instant and even write lines of code in different programming languages. While they may not produce a fully playable video game upon request, programmers have already created basic smartphone apps with the help of AI. It is ironic that software engineers, who contributed to the development of AI, are the ones most concerned about its impact on their livelihoods, as revealed by a survey from the Pew Research Center. Learning to code may not be the guaranteed path to success it was once perceived to be.
Although ChatGPT cannot yet outperform human authors in essay writing or expert developers in coding, its introduction has had a noticeable impact. Coders now utilize AI as an advanced assistant to expedite routine tasks like code debugging. A study showed that software developers with access to GitHub’s Copilot chatbot were 56% faster in completing coding tasks compared to those working alone. In the next decade or even sooner, coding bots may be capable of doing much more.
According to Matt Welsh, a former Harvard computer science professor and entrepreneur, people will still find jobs, but they may not be as lucrative. Automation could increase the number of jobs in software development, with more people guiding machines towards faster production. However, Welsh also explains that an expanded talent pool could alter the economics of the field, potentially leading to lower pay and reduced job security. This uncertainty poses a challenge for students as they try to anticipate the long-term implications of their chosen careers.
Timothy Richards, a computer science professor at the University of Massachusetts at Amherst, has expressed concern about the future of undergraduate computer science programs. He believes that the way computer science is taught needs to evolve and acknowledges the difficulty of determining if learning to code is still valuable. Students’ ability to effectively cheat using chatbots like ChatGPT has made teaching coding more complex. Richards has adjusted his approach by having students use AI similar to a calculator in math, with full transparency on the prompts they use and requiring explanations for their choices. Additionally, classroom-based assignments under supervision have replaced take-home assignments.
Adjusting the computer science curriculum may not be enough to maintain coding’s position as the pinnacle of higher education. “Prompt engineering” has emerged as a lucrative job option, involving the input of phrases into large language models to make their responses more human-like. This area may be better suited for English majors than computer science graduates. Ben Royce, an AI lecturer at Columbia University, argues that machines lack creativity and are, at best, sophisticated derivatives. When faced with novel coding problems, chatbots struggle and produce inadequate solutions. As AI becomes more advanced in coding capabilities, programmers may need to lean into the conceptual aspects of their job rather than relying solely on technical know-how. Those with entrepreneurial and inquisitive mindsets may be less susceptible to automation in the workforce.
The potential decline of coding as a career path does not mean that technologists are doomed or that English majors were correct all along. The rise of AI presents an opportunity for students to focus on conceptual thinking and problem-solving enabled by technology. The next groundbreaking innovation in Silicon Valley could come from a humanities graduate without coding expertise or from a computer science graduate with extensive technical skills. Coding has always been about more than just programming languages like Python and C++; it involves identifying patterns and piecing them together creatively.
The future of higher education may lie in what machines cannot do. Moravec’s paradox, which highlights that AI excels at high-level reasoning but struggles with basic skills, emphasizes the importance of human curiosity-driven instincts in the creative process. These instincts are not disappearing in an AI-driven world; rather, they are becoming more crucial than ever. Fortunately, students have numerous avenues to cultivate these skills.
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