Why I’m Glad I Have a Cognitive Science Degree (and the Limitations)

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Why I’m Glad I Have a Cognitive Science Degree (and the Limitations)

Cognitive Science is a relatively new field that was formed from people of various backgrounds coming together to suggest theory of mind based on “complex representations and computational procedures.” Depending on what aspect of cognitive science is being investigated, it basically involves trying to understand how we process information and/or how we can make computing that replicates these functions. People primarily focus on models that can explain observed or desired outcomes. A section is also devoted to the context of these models which some cognitive scientists shy away from. The field gives you a fascinating and informed look at the world and how we view it.

Example of the interdisciplinary nature of cognitive science (via Wikimedia Commons).

Master of None

Through my experience in cognitive science, I have learned how to approach concepts that are new to me. I spent a good portion of my undergraduate doing introductory courses in different fields in which I had little or no previous experience. I was especially interested in a central theme of logic, perception, and decision-making. Sometimes this involved object-oriented programming in Java or computational neuroscience with MatLab. Other times it involved investigating sentence structure in linguistics or modal logic in philosophy.

Every jump between fields involved a shift in what objectives or assumptions are considered important. This meant that I did not become a full developer or spend years on a specific aspect of the human brain or mind. An adviser had told me in my final year that based on my goals and experience, I would probably spend years jumping around gathering experience to tie things together and I’m still very much in that stage.

What’s the Context?

Studying a range of fields and models allows you to become a better critic. Each model will inevitably fail at some point, so it’s interesting to think of things such as context, where the information is coming from, objectives of the model, and more. This is something some cognitive scientists neglect but is something I find crucial. This is why integrated data, social media, user experience are all topics I explore. This is why my neuro/tech/thought blog contains articles on politics and why linguistics and anthropology make up two of the six points on the cognitive science hexagon pictured above. As we get more advanced with our tools and algorithms, we still have to understand the human element and I believe that I was able to explore this a lot in my studies and early career.

Limitations

To put it explicitly, the cognitive science degree is not directly easy to promote in the early stage (i.e. after an undergraduate degree). There’s a heavy lean towards people that stay in academia to further expand on concepts and processes from undergraduate. The most practical, non-academic aspect of the degree is the computing and the likelihood of dealing with large datasets within context. Most advice I’ve seen suggests emphasising this to get a data analyst job even if it has nothing to do with the brain. Others suggest that if you have the tie or will, take the introductory/intermediate level of programming and expand on it to make you more attractive for technical roles since you usually won’t have a ton of example projects after undergraduate to show. This article from a few years ago details one cognitive scientist’s experience on the job hunt (and this was someone with a PhD). Even big tech companies sometimes don’t know what to do with a cognitive science graduate.

The Take Home Message

The cognitive science degree is not a straightforward one. Especially if you don’t see your future as an academic. The limitations are real but changing. Even if some people or companies aren’t specifically looking for “cognitive science” on a CV or resume, we are becoming more relevant in an age of AI, big data, and data science (outlined in this article). This introspection and evaluation of models and interest in applications is what excites me. The skills are there and the versatility is really where the degree shines. This is why I’m confident that things will only get more exciting on my current journey.

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-DAO

 

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