Getting a Degree in AI at WSU

Whether you are a college-bound high school student or a working professional looking to reskill, the best advice I can offer on choosing a degree is this: pick something that (#1) can support you financially, and (#2) is interesting and fulfilling to you. According to LinkedIn data, the “typical AI job posting lists a base salary midpoint of $177K, more than double the $80K for non-AI positions."

In other words, AI degrees certainly meet criterion #1. However, criterion #2 is much more subjective. Beyond the paycheck, I will discuss why I believe pursuing a degree in AI is both interesting and fulfilling. But before we can get there, let’s consider what an AI degree looks like.

What is an AI Degree?

At the undergraduate level, AI degrees are often a specialization of computer science that focuses on the fundamentals needed to understand and work with AI. Put another way, in addition to important computer science topics, an AI degree would also cover topics like applied mathematics and data science.

If this sounds daunting, remember that a computer science-based AI degree is not a math degree, but it does require knowing some math and statistics.

An AI Degree Lets You Do Interesting Things.

Within the last five years, large language models (LLMs) like ChatGPT, Gemini, and Claude have become very popular, leading many to think that AI is large language models. On one hand, the association is understandable: these models are very impressive. On the other hand, it’s a shame because the field of AI is much more than figuring out how to build and use LLMs.

Beyond text generation, there are other exciting specializations in AI that are solving interesting and important problems. Here are just a couple of interesting areas: 

• Neurotech: Neurotech bridges the brain-computer gap, allowing hardware to respond to and stimulate brain activity. AI acts as the translator, turning complex brain signals into digital actions.

• Drug Discovery: Drug discovery creates new treatments for diseases. Today, AI accelerates drug discovery by analyzing massive biological datasets, both to repurpose existing therapeutics and to design entirely new molecules from scratch

There are a lot of interesting and important problems that are reserved for those who understand how AI works.

An AI Degree Lets You Do Impactful Things

The current AI boom only goes back about two decades, when researchers were playing around with the foundational building blocks of LLMs: neural networks. Coupled with the dramatic uptick in the amount of data we track and store, there are plenty of opportunities for impactful AI systems. As an example, consider the benefits just from work in Neurotech and Drug Discovery:

• Neurotech: Though neurotech is an emerging field, its promise is profound: helping stroke survivors regain mobility and detecting neurological diseases early enough for effective intervention.

• Drug Discovery: AI can make drug discovery faster and more efficent, resulting in treatments that help alleviate problems much sooner . For example, consider the non-profit organization Every Cure. Every Cure uses AI to find existing, clinically tested drugs that can be used to treat rare diseases. These rare diseases may have no treatment otherwise due to the high cost of drug development.

Given how young the technology is, there are many opportunities to steer this technology toward the public good. We just need skilled and responsible AI experts to discover them.