You Ask, I Answer: Merging Liberal Arts with Computer Science?

In today's episode, Mbeza asks, merging liberal arts with science helps make what one has to offer unique. How can I merge the liberal arts with what I want to do in order to have a unique skill or product to offer? So fundamentally a successful marketer has to be both qualitative and quantitative. That is half art, half science. There really is no way to be successful going forward.

And the reason for that is that artificial intelligence continues to make such substantial strides that within the span of our lifetimes many individual tasks will be turned over to machines to do. Now that doesn't necessarily mean that we are going away per se, but it means that we will need fewer far fewer of us in order to get work done. Challenges, of course, you only need one conductor in the orchestra, uh, whereas you have lots and lots of musicians. But if all the musicians are uh performing narrow specializations, like violin or clarinet or whatever, then you don't really need uh people for those other roles. So to be a successful marketer going forward, to plan well for the future, and quite frankly, to be um well structured for whatever challenges come your way, um, I really do believe that that liberal arts education uh that broad spectrum of uh knowledge is important.

And yes, you will find not every subject's exciting. Um certainly uh I that was my experience, but you have to be half art, half science, uh creative and quantitative, um, rigorous, but also able to vary outside the rules when you need to. And the first step to making that determination is to figure out what you're weak at. Uh where are your vulnerabilities. Think about what marketing uh and business to a greater or lesser degree fundamentally is it's about communication, right?

It's about communication and people, which means that we need to understand people, and we need to understand communication. So that means subjects like anthropology and ethnography, being able to understand how people interact with each other, um, and sort of the history of their ability to do that. Um that means understanding psychology and sociology. Uh again, individual behaviors, group behaviors. Um that means understanding uh communications methods, uh, visual auditory kinesthetics, uh, music, art, literature, dance.

Um, not necessarily doing those things, although it certainly doesn't hurt, uh, but at the very least, understanding what those things are and how they've evolved, especially uh in a global economy. One of the challenges that a lot of students will face is that uh their learning materials tend to be skewed towards a certain point of view. This is especially true in the United States, where uh everything is overly centered uh centered on uh the United States and kind of ignores the rest of the world, which is why eleven percent of students in America can't find America on a map. Anyway, um, music, art, literature, dance, uh all the different ways that you can communicate with people visually, auditorily, uh, kinesthetically, uh, to convey messages to them. Uh and then absolutely on the hard sciences, uh, you're talking about statistics and probability, uh, mathematics, all the way up through things like linear algebra uh and advanced calculus.

Uh you're talking about uh the scientific method. Uh to some degree understanding things like biology and things like chemistry and physics actually do have relevance to marketing, to understanding why things happen the way they do. Uh, especially when you start to get into um really complex subjects like why, like how machine learning works, machine learning and AI, uh coding, uh being able to write in Python or R, being able to use databases. Marketing is essentially how to interact with the human race. Right.

And so everything that is in the human experience is something that you can study and it will have value for understanding certain groups of people. Um I wouldn't be so worried about a you know a product to offer, and at this point, you know, I would not be uh terribly concerned about having a specific unique skill to develop. Uh what you want to be able to do is have a broad um base of knowledge to draw from that you can bring to a variety of situations uh that will uh really help inform uh problems that you're asked to help solve and be extremely versatile. So whatever the challenge is, you have some level of competency uh that can make the challenge a little bit less daunting. Um that's why things like you know, technical skills, being able to do to write code, but being able to interact with something like music together are much more difficult for machines to copy.

AI is very bad at broad knowledge. AI is very good at narrow domains. If you can have that broad knowledge that lets you develop multidisciplinary domain expertise, it's very hard for a machine to copy. Uh it's very hard for a machine uh to create because most people are not that way. And because we train machines on past existing data, uh, if you can create things that are net new that are not part of the machine's previous corpus of learning, uh, or not uh in a substantial enough way, um, you can add value that the machines simply cannot.

So that's a lot to tackle. Again, figuring out where your weak uh where you're weakest as a as a learned person is the first step. What are all the things that you could study? What are the things that are likely to be important? And I forgot to mention in there, one other area is that's really important, particularly if you are in marketing, is the ability to study business, right?

Uh everything from operations to management to finance. I can't tell you how many marketers I've met who have absolutely no idea how to compute ROI, how to compute uh net profit, things like that. So those basics are super important as well and are definitely lacking. So where are you weakest? And where where are you also strongest?

Where are the areas that are so appealing to you that if you could just do those things or study those things deeply, um, how can you bring other disciplines into those areas of study? For example, I've spent a lot of time on analytics, I spent a lot of time on in data science, but I also spent a fair amount of time doing natural language processing. So understanding literature and styles and writing and all these things is important to being able to do that well. Not necessarily just to be able to write the code, but also to know what to look for, um, to know uh to be able to judge the merits of something based on the outputs it gives. I'm working on a piece of uh code work that deals within stylometry, which is the measurement of writing styles.

And if you didn't know anything about how you know different authors have different styles and you weren't able to uh have that knowledge base, then when the machine spits out its results, there's no way of knowing whether it did a good job or not. But if you have some level of domain expertise in that, you can qu you can fact check the machines. So that's a lot to tackle. Uh again, start with the evaluation, figure out where you're weakest, and then and then double down on what you're strong at and mitigate where you're weakest. If you have follow-up questions, leave them in the comments box below.

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