4) Data Science at the Singularity

Assigned Reading

Reflections

bCourses Submission

Submit your answers—to the following questions—to the corresponding assignment in bCourses.

Accepted formats: PDF, HTML, MS Word (.docx), or Google Doc

Reflection 1

  • Think about your own recent workflow behavior for a class project or literature search.

  • Have you ever completely abandoned a high-quality scientific paper or tutorial simply because the link was broken, the data was paywalled, or the code required a clunky manual installation?

  • Is your personal “friction threshold” getting lower? Does a lack of an immediate download link make you view a researcher’s work as obsolete or untrustworthy?

Reflection 2

  • Reflect on a time you were working on a competitive coding problem, a video game, or a graded assignment tracking a metric.

  • Did you find yourself frantically tweaking tiny parameters or copy-pasting random “hacks” just to make the final number go up, without actually understanding why the changes worked?

  • How do you protect your own mindset from falling into “mindless scoreboard chasing” when your future job rewards execution speed over deep theory?

Reflection 3

  • Look at the skills you are currently trying to learn in college (e.g., fundamental Python/R syntax, data cleaning commands, formatting charts, machine learning model fitting).

  • If an automated system can handle those tactical execution steps robotically, what unique, human value do you bring to a data project?

  • How will you deliberately change what you focus on learning this or next semester(s) to ensure you are the “architect” directing the machine, rather than a “tactical data cleaner” replaced by a script?

Rubric

Important

Generic responses that do not mention a specific past assignment name or unique piece of code from your own experience will receive a score of zero.

  • Full Credit (5 Points): Response is highly specific, names unique personal or localized constraints, and explicitly connects the personal experience back to the prompt in each question. Clearly written by a human.

  • Partial Credit (2-3 Points): Response is correct but uses vague or generic examples (e.g., “I lost a file once” instead of naming the script). Sounds like a generic summary an AI could have written.

  • No Credit (0 Points): Response relies entirely on abstract definitions, fails to provide personal context, or uses copy-pasted text from a webpage or AI tool.