How we can use AI as an interdisciplinary tool

Recently before school began, I attended a short program held by the Ohio State University about cognitive science and humanities, hosted and created by professors Fredrick Luis Aldama and Andrew Leber.

Recently before school began, I attended a short program held by the Ohio State University about cognitive science and humanities, hosted and created by professors Fredrick Luis Aldama and Andrew Leber. The program was insightful in many ways, because I learned about many different fields, ranging from gender studies to storytelling, and how they all relate to cognitive science.

The biggest revelation I had during this program was how narrow-minded my approach was too artificial intelligence. I always just associated it with computer science and mathematics and judged it as a subject or field of study. While these are not incorrect ways to interpret AI, it certainly limits the potential of it. Artificial intelligence can and should be viewed as a tool, especially since nowadays it is so accessible and easy to use.

This revelation came to me after a lecture from Dr. Katherine Elkins and Jon Chu from Kenyan university. They teach a very unorthodox approach to writing. Jon Chu is primarily an artificial intelligence researcher, whereas Dr. Katherine Elkins’s main field of study is in writing. In their course, they teach the basics of writing and becoming an author and use AI to create and examine stories. In this case, AI isn’t a field of study but is akin to a hammer in a toolbox being used to build a house (the house being a story in this analogy).

cognitive-science computer-science data-science ai artificial-intelligence

Keeping up in the new silicon-based survival of the fittest

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There are many intersections and overlaps between AI and data science. AI has numerous subsets, like Machine Learning (ML), Deep Learning (DL), and Natural Language Processing (NLP). With many career opportunities in both fields, there are lots of conflicting perspectives on educational paths for starting a career in one of these fields.

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The agenda of the talk included an introduction to 3D data, its applications and case studies, 3D data alignment and more.