Artificial Intelligence has been in the news a lot recently, and we’ve looked into it ourselves, as it seems poised to disrupt or fundamentally change a great many industries. One which we did not cover, but which is rather key to this entire discussion, is computer science itself.
There has been much talk about the ability of AI to write programs, and speculation on how this will change the field of computer science, and the career prospects for programmers. In this article, we’re going to break this down to the details; what we know for sure, what’s just hype, and how the growing presence and power of AI tools will impact students seeking to major in computer science. Let’s get started!
Note on Sources
While we here at Ivy Scholars are experts at college admissions, that doesn’t mean we know everything. This article was written in collaboration with our Computer Science Research Mentors, Doctors Farah Kidwai and Rebecca Beason. To learn more about them, and the research program they’re part of, see our page here.
Will AI Replace Programmers?
This is perhaps the most relevant question, because one of the major draws of CS as a major is the perceived career safety it offers. There is a big demand for experienced computer programmers, and any impact of AI on this job market will send aftershocks through colleges and beyond. So is this something you need to worry about?
Probably not.
As with all complicated questions, there is some nuance here, but in general, there will be no major shortage of programming positions caused by AI in the near future. There are several reasons for this, and we are not saying all careers are safe. We’ll break down what we know, and what AI can and cannot do currently.
Lag Time
Computer science is an incredibly fast moving field when compared to most other disciplines. In archaeology, for example, the people you’re studying aren’t getting any deader, so there’s no real rush to publish. Advances and discoveries happen, but at a sedate pace. In computer science, technology changes by the month, with new techniques, breakthroughs, software, hardware, and capabilities debuting regularly.
AI is built on large data inputs filtered in over time. This means it must generally lag behind the curve, as new discoveries are processed, analyzed, and finally fed into training data. Most of the data sets AI is built on are a year or two old. For most fields, this is only a small impact, but for computer science, this is a very long time.
Specific Skills
Currently, there are certain tasks Ai is very good at; querying databases, extracting and compiling data, and writing general programs are its main areas of strength. The more niche and specialized a request is, the less likely an AI will be able to complete it with any degree of competency.
Expertise in specific domains is not yet something AI can emulate, leaving a lot of leeway for subject matter experts. In addition, there are certain areas where we do not want AI operating for security or safety concerns. Terminator was just a movie, but that doesn’t mean we want autonomous decisions in military applications.
The Ouroboros Problem
Ouroboros, the snake eating its own tail, is an apt metaphor for one of the problems AI is beginning to run into. The strength of these models is only as good as the data fed into them, and feeding a model data generated by another AI is a major problem. The model begins to feed upon itself, and the outputs produced become less and less useful and viable. This is not yet a major problem, but is a significant weakness in AI, and is part of why the need for human programmers remains.
Will AI Impact Coding Careers?
Yes. A lot. Ai is a tool, a powerful one, with limits we’re still finding, and which are still expanding. While AI will not be able to unseat programmers, it will definitely impact the work they do and how they do it.
Some careers in data entry will likely be entirely replaced, as this is one of the things AI can reliably do. There will still need to be a person to check the numbers, but the long work of doing it will be easier to automate. Other careers in databases will likely be fully transformed or automated as well, or have a significant portion of their duties taken by AI.
In other careers, AI will fill other niches, as a research aid, or drafter, or a way to build scaffolding that will need to be fleshed out by a human afterwards. You cannot yet trust all of the information sourced through AI, nor does its code run reliably, but it is still a useful starting place for many tasks.
When and how AI will be used will vary a lot by field and discipline; those few programmers still working with COBOL will likely never make use of it, while others will need to interact and interface with AI tools quite often. In your time at college, you will be able to control just how much you will be expected to interact with AI, based on what you decide to specialize in within computer science.
How Will AI Impact Computer Science Majors?
As AI entwines itself with the entire field of programming, so too is it being felt in computer science departments and majors. Of course, each college is handling this differently, as they adapt to changing circumstances as they see fit. We will go through the changes we have seen already, and some we anticipate going forward.
New Specializations or Certificates
AI is increasingly its own subfield within computer science. Much like cybersecurity or data science, it too is something colleges are allowing students to specialize in. This is important for anyone who wants to work in this field; understanding the back end of these processes, what goes on behind the curtain is key for any student who wants a career dealing with AI.
These specializations are not a major in themselves, but may give you a slight leg up when angling for a career directly relating to AI. They can also be useful for students who want to make better use of AI tools in their own disciplines by understanding the code which underpins them.
New AI Majors
Some colleges are going further, and creating full majors to study AI, generally as a subfield within computer science or data science. These are rare still, but we expect the number offered to expand. Universities are old, and have a great deal of institutional momentum, so it takes them a long time to change and adapt.
These majors will cover much of the same ground as a standard computer science major, but with more of a focus on using and forming the code which underpins AI, and on understanding how the algorithms which govern its behavior operate. As with all niche majors this may limit your options slightly, but if you know you intend to work with AI, they are a great option for you.
Changes to Workflow
A change being seen across disciplines and majors is the increased use of AI for cheating, especially on homework assignments and essays. Some students have always been keen to find loopholes, but the ability of AI to evade many plagiarism checkers is opening new doors for academic dishonesty.
This is happening in computer science as well, as AI tools offer programmers some easy shortcuts. The code written by AI does not always work, and sometimes has questionable errors, but it can write code. The use of AI to cheat in these courses is lower than in purely text based classes, but it is occurring.
We recommend that students not use these shortcuts. There are various ethical reasons not to cheat, but there are also practical ones. The homework you are assigned is designed to help you practice and master certain skills, and tests then allow you to demonstrate that mastery. If you aren’t trying to learn and master these skills, then why are you at college in the first place? Every job you get will assume you have the skills associated with your degree, and if you relied overmuch on AI, then you may find yourself overwhelmed when you enter the workforce.
This applies to non-CS classes as well. Putting aside the overwhelming irony of cheating in an ethics class, the point of college is to help you learn to tackle complex problems. Outsourcing that skill means you don’t develop the mental muscles you need, and leaves you with a shortage of skills that employers expect from graduates of a top college. AI will impact the workflow of students in many majors, but we recommend avoiding its use in this way.
Final Thoughts
We are still in the development stages of AI, and waiting to see just how powerful it becomes as a technology. While it clearly has great potential, just how much of the hype will be realized is uncertain. It is certain, however, that while it will greatly impact the entire field of computer science, programming careers will remain relevant for quite some time.
Of course, the new popularity of AI is only driving an increase in the number of students who want to study computer science, and increasing competition for a limited number of seats at top programs. If you are looking for help with your own application, or creating the kind of candidacy that top colleges want from students, schedule a free consultation today. We have years of expertise at helping students apply to top colleges, and are always happy to hear from you.
