It seems like every day tech news is bustling about a new breakthrough in Artificial Intelligence (AI). Although the industry may be very new, it has already begun to cause change in many different industries such as e-commerce, manufacturing, finance, automotive, and education. As more and more companies wish to implement AI into their own business model, the number of available engineers knowledgeable in AI continually decreases, yet enrollment in computer science continues to increase. Furthermore, companies speak of a knowledge gap amongst new college graduates, so they now offer their own version of classes about artificial intelligence, ethics, math, and business. If students are paying exuberant amounts of money for a degree, why are companies claiming they do not have the necessary skills?
The answer lies in the infamous major of computer science. Computer Science invites students to learn how to program computers and promises a lucrative career. Students eagerly enter into computer science departments all over the country and learn languages such as Java, C++, Python, and JavaScript in hopes to live a life of luxury and job security. However, the skill of coding, in the traditional sense, is losing value as AI is more heavily implemented. The reason lies in the fact that AI is not based on code like a traditional computer program is. AI utilizes large amounts of data to assign weights to chosen variables and morphs over time as new data is obtained; AI uses more math and statistics than coding.
What does this mean for universities? It is time to heavily consider creating a major more applicable to the needs of the emerging AI industry. Classes focused on statistics, applied mathematics, data science, algorithms, and creative projects should be implemented so that students could develop relevant skills for jobs. The technology industry moves fast, but currently, the AI industry moves faster. Universities are not properly preparing students, so companies have taken it upon themselves to fill in the gap. Even though programming skills are still in need, soon companies will no longer need programmers; rather, they will need creative thinkers keen in statistics and mathematics ready to create new models. It is time for universities to stop preparing students for today, and instead, prepare students for tomorrow.