The Case for Data Science as the Modern Liberal Arts

Often lost in thought, or lost in the woods. Sometimes both.

The Case for Data Science as the Modern Liberal Arts

Data science and the liberal arts - Alexander Titus

Liberal arts education has been around for a long time. Back in a time when our understanding of natural phenomena was limited, it took integrated training across the arts, sciences, and humanities to be able to make sense of the world. As we began to understand more about specific fields, we required more depth of expertise to make advances in that field.

Modern science has again moved toward the benefit of a liberal arts education. It’s why data science is now modern liberal arts. The breadth of expertise required of data scientists is often criticized as the kind of training that simply can’t exist. In reality, however, the liberal arts have provided broad integrated education to young minds around the world, and modern data science is the emergence of a new form of liberal arts careers.

liberal arts and the craft of telling a story

The demands of being a data scientist

Data science has been widely accepted as one of the hottest jobs of the 21st century. To be good at your job, you’re expected to be an expert in computer science, statistics, data engineering, data visualization, executive presentations, and persuasive writing. The world is flustered at all the expectations, largely because they expect “expert” in all of that. What the technical world is coming to terms with is that when you have such breadth of application, you end up not knowing where to apply your skills. Similarly, when you are presented with an abundance of data, you have to systematically cull through it all to make sense of it.

The demands on data scientists require the breadth of training similar to the liberal arts

Liberal arts education has been teaching breadth and synthesis for decades

When I started college at the University of Puget Sound, I walked onto a small liberal arts college without a lick of understanding of what that means. Four years later, I took classes in history, writing, biology, chemistry, math, computer science, and technology & society. I even took a class called “The Search for Extraterrestrial Intelligence”.

Spoiler alert: its called “the search” because we still haven’t found it.

The fundamental skills in the liberal arts are the ability to read, synthesize, and write. Damn, talk about a broad skill that you can apply all over the place. But after training on how to hone research, sifting through thousands of pages of material, to then build a cohesive and persuasive argument, I started to get pretty good at it. Eventually, I could craft a narrative about the cultural norms of the Manhattan Project as easily as I could about an organic chemistry synthesis.

University of Puget Sound - The Search for Extraterrestrial Intelligence

Liberal arts and its relationship with data science

As we move farther into the data-driven sciences, the field looks more and more like the liberal arts. In the past, almost all data needed to be collected before being able to make a “data-driven” decision. We did this largely through hypothesis testing as we do in the scientific method. With the modern explosion of data in every part of our life, we’re moving more and more towards the need to explore data that’s already there.

At the advent of the printing press, the world started storing massive amounts of data in the form of books and the written word. To make sense of all that, and the natural world around us, the liberal arts taught how to interpret, synthesize, and communicate.

Sound familiar?

Every day, we write more about the intersection of data science and effective communication. How do we interpret, synthesize, and effectively communicate all the great stuff we are discovering through our data wrangling, machine learning, and artificial intelligence approach to life?

A well-crafted liberal arts degree is the perfect training to be a data scientist

I’ll go out on a limb and make a claim. The perfect data science degree would look like an English degree, heavy on writing and reading. It should be paired with a minor in statistics/math/computer science and a second minor in a field to provide domain knowledge (e.g. biology, chemistry, marketing, physics, etc).

Once a student has mastered the ability to write effectively (code or essays), they then have the ability to tell a story. Effective data science is only as good as our ability to communicate our results. Once you bring the ability to craft and write a story together with domain expertise, you get a potent ability to lead towards data-driven decisions.

Data Science as the Modern Liberal Arts

Lets train liberal arts students in data science as much as we train engineers in communication.

The world needs more data scientists. However, our current definition of who makes a good data scientist is too narrow. Lets bring in the history and English majors, the writers, the crafters, and the people who spend their lives culling through massive sets of data with their own network of neurons. (Not to be confused with neural networks). We spend a lot of time and energy to train engineers to communicate more effectively. Lets spend as much energy training liberal arts majors how to write code and derive algorithms.



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