kalyrama's blog
ch 3 reading response
I really like Artful Design’s Principle 3.5: Build complexity from simplicity. Design can often feel extremely intimidating when only the final product is observed and the process of creation is obscured. Just like the example in the book of the rainbow flares, complexity is just an amalgamation of many simple building blocks, and knowing that makes both design and engineering feel accessible.
In my computer science background, a fundamental concept underlying all of problem solving is the process of breaking down a complex problem into many simple problems, and building back up to a complex solution. This process demystifies relationships between moving parts, gives you clarity on what steps a problem requires, and allows for more modularization and scalability.
ch 2 reading response
I am struck by principle 2.1: Design for play and delight. Before reading this chapter, I associated artful design with perfectly intuitive functionality, as well as a standard of aesthetic that makes the experience sublime. Considering the zipper pencil bag example from the previous chapter, I agreed that design can inspire wonder in a user. What I didn’t consider, however, is the utility of play. Even using the word utility here somewhat defeats the purpose of this design principle. A pleasurable experience is “productive” in itself and does not necessarily need to have traditional utility to be valuable!
This principle makes me reflect on the best designs I’ve come across in my life, and how they optimize for play and delight.
ch 1 reading response
From this week's reading, I'd like to respond to meta-principle 1.4: expect no more precision than a subject naturally affords.
As a CS major primarily occupying spaces that are analytical and data-driven, I think this sentiment is often lost on my peers, and to some degree, myself. The book’s comparison of mathematical rigor vs. philosophical rigor is particularly pertinent here, because things that don’t provide explicitly measurable value are often overlooked. I can even take the example of computer science assignments that are graded on both style and functionality. Since functionality can be measured with automated tests that are applied equally to everyone, those points are optimized and weighted accordingly.