The [Lake Erie] ecosystem underwent a series of changes, each of which were related. There was an increase in the human population; which led to higher phosophorus levels in the water; which led, at last, to an increased level of algae in the lake. In effect, Lake Erie’s ecosystem was rewritten. Changed by human activities into…something else.
But Franklin cites the study because it’s doing something slightly novel: applying Selye’s principle of stress to ecological systems, suggesting that they are, much like humans, just as susceptible to external stressors. And I’ve been thinking about that a lot lately, especially this week. Because Franklin’s suggesting that the work begins not by “fixing the system.” Rather, she suggests it’s about shifting the priority a little: to removing whatever stress you can.
In the early days, design systems promised us more consistent interfaces, more collaborative teams, and improved shipping times. While they’ve certainly delivered on some of those fronts, they’ve introduced new challenges too. Let’s talk through what’s working well—and what could be working better—as we take a closer look at the systems between us and our work.
Like a programming language interpreter, GPT-3 translates the designer’s intent from a language they’re already familiar with (English) to one they need to learn (Figma’s information architecture, as manifested in its UI.) This can be easier for a new/busy designer, much like Python is easier and faster to work with than assembly language.
But that’s not “designing” — at least not any more than compiling Python code is “programming.” In both cases, all the system does is translate human intent into a lower level of abstraction. Sure, the process saves time — but the key is getting the intent part right. I’ll be convinced the system is “designing” when it can produce a meaningful output to a directive like “change the product page’s layout to increase conversions.”