Lab 2

I believe all humanities students should learn to code. More specifically, humanities students should learn how to code with a programming language rather than a markup language. Learning how to code comes with a lot of useful life skills such as problem solving and patience. As a computer science major and a CS lab assistant, I spend a lot of time looking at code everyday. Rather than writing code, most of my time is spent on debugging and brainstorming possible solutions on paper. Anyone can learn the syntax of any coding language easily and write lines of code. However, in order to become a stronger problem solver, working through mistakes and revising them is crucial step. The techniques you learn from programming can help you notice small details and work through problems that may seem impossible. Even as an artist, sometimes I feel more creative finding a working algorithm than drawing or sculpting.

More significantly, many of us in the humanities miss the extent to which programming is a creative and generative activity.

Matt Kirschenbaum, Hello Worlds: Why Humanities Students Should Learn to Program

An interesting discussion brought up during class was learning how to utilize AI vs learning how to code. I agree AI can occasionally generate some useful content especially for basic level information. However, in many cases, AI tools can be wrong which, without knowledge of code, can be easily overlooked. In addition, there are so many copyright concerns in regards to how the AI training data is collected, which can ultimately lead to potential lawsuits and discredibility. I’m against the use of AI, but instead of learning how to type prompts for blocks of code, learning how to code and edit AI generated code can prove to be less time consuming and risky in the long run.

import matplotlib.pyplot as plt
import matplotlib as mpl
mpl.style.use('ggplot')
plt.rcParams['font.size'] = '14'

fig = plt.figure(figsize=(10,6))
x = table['WAVELENGTH']
y = table['FLUX']
xlabel = 'Wavelength [Angstroms]'
ylabel = 'Flux'
plt.plot(x,y)
plt.xlabel(xlabel)
plt.ylabel(ylabel)
plt.xlim(1500,10500)

This is a python code snippet from Astronomy 110 I took last fall. Using code to generate a plot with a data set is a lot more efficient than manually plotting each individual point. In addition, computer computation is a lot more reliable than human computation especially with bigger numbers. Being able to analyze data can be very important in various humanistic work. Having a way to organize that data and easily plot them in different ways quickly can help conserve resources and labor.

While I don’t believe humanities students should be forced to learn how to code, spending some time to work through problems and learn new digital tools can definitely come in handy in a society that is becoming more dependent on constantly evolving technology.