AI-driven “Design”?

Via Kenny Chen’s newsletter, I learned about Tricycle, a set of tools “that help you design products powered by AI.” I remember seeing tweets last year from Jordan Singer (Tricycle’s creator) that highlighted some of this functionality. Now it looks like Singer is productizing a bundle of GPT-3-powered Figma automation tools.

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Tweaking Users’ Mental Models

Allison Johnson, writing in The Verge:

… the original Apple II version [of the video game Karateka] included a delightful little easter egg from the early days of PC gaming — putting in the floppy disk upside down would boot up the game upside down.

According to [Karateka’s creator Jordan] Mechner, the game’s developers hoped that a few people would discover it by accident, and think their game was defective. “When that person called tech support, that tech support rep would once in a blue moon have the sublime joy of saying, ‘Well sir, you put the disk in upside-down,’” Mechner was quoted as saying in a recent profile, “and that person would think for the rest of their life that’s how software works.”

It may seem disingenuous to suggest users would expect that flipping the software media would cause the software itself to flip. But I’ve been surprised at the many ways people misunderstand how computers work.

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Shipping the Org Chart

While reorganizing my library a few weeks ago, I came across a handout from a 2003 workshop by my friend Lou Rosenfeld titled Enterprise Information Architecture: Because Users Don’t Care About Your Org Chart.

Lots of ideas quickly become obsolete in tech. But after 18 years, the idea that users don’t care about your org chart is still relevant. Teams still ship systems that reflect their internal structures. IA is still crucial to addressing the issue.

Few teams set out to design inwardly-focused systems. Instead, they inadvertently arrive at solutions that feel “natural” — i.e., that mirror their structures. Subtly, the systems they design come to reflect distinctions inherent in their orgs.

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Design as an Effective Agent of Change

As software continues to eat the world, digital systems’ conceptual structures matter more than ever. It’s easy to nudge users towards particular choices by making them more prominent. We can use this power for good or bad.

For example, are we helping people eat healthier? Or addicting them to unnecessary services? Alas, choices aren’t always as clear. And even in “clear” cases, we may not be the best arbiters of “good.” Often, the lines between good and bad are blurry.

For example, some retailers tweak search results towards commercial goals. Is that wrong? It depends. Are customers still seeing relevant results? Will they benefit? Same with navigation: It’s easy to bury “undesirable” choices deep in menus.

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Abstraction and Implementation

Paul Dourish, in his book Where the Action Is:

Software systems are built from abstractions. The extent to which abstraction is fundamental to software systems can be hard to explain to someone who hasn’t built them; while to someone who has, it can be so ubiquitous as to have become invisible. But the very essence of software system design is the manipulation, combination, and creation of abstractions.

Essentially, computers manipulate information in terms of the presence or absence of energy, which we render as ones and zeros. There’s a wide gap between this binary way of representing reality and how human beings experience reality. We bridge the gap using abstraction.

The essence of abstraction in software is that it hides implementation. The implementation is in some ways the opposite of the abstraction; where the abstraction is the gloss that describes how something can be used and what it will do, the implementation is the part under the covers that describes how it will work.

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Machine Intelligence and the Design of Complex Systems

Adobe’s Patrick Hebron, in an interview for Noema (from September 2020):

If you’re building a tool that gets used in exactly the ways that you wrote out on paper, you shot very low. You did something literal and obvious.

The relationship between top-down direction and bottom-up emergence is a central tension in the design of complex systems. Without some top-down direction, the system won’t fulfill its purposes. However, if it doesn’t allow for bottom-up adjustments, the system won’t adapt to conditions on the ground — i.e., it won’t be actualized as a real thing in the world. What’s needed is a healthy balance between bottom-up and top-down.

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How to Work with Tension in Design

The ultimate purpose of a design project is to change something. It might be kickstarting sales, making stuff more findable, or addressing a competitive challenge. Whatever it is, the project exists because someone wants something to be different.

Changes reveal tensions. Often, teams are invested in the status quo. For example, sales may want product to introduce new features, while product wants a simpler experience. More capabilities increase complexity, so the two are in tension.

Projects are rife with such tensions — and they often go unacknowledged. Not surprising, since dealing with tensions can be uncomfortable. If you’ve ever been in a meeting with a surly stakeholder, you know how awkward these situations can be.

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Challenges in Designing for Emerging Technologies

Elizabeth Lopato, reporting in The Verge:

Neuralink, Elon Musk’s company focused on developing brain-machine interfaces, has posted a video to YouTube that appears to show a monkey navigating an on-screen cursor using only its mind.

The video is amazing:

As the article notes, it’s unusual for scientists to release such materials unaccompanied by peer-reviewed evidence. I take this as a cue to be skeptical. Still, if true, it’s an impressive demonstration — especially considering the implications for paralyzed people.

This video sparked two thoughts.

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Overcoming Objections to Modeling

Recently, I asked on Twitter,

What’s the best objection you’ve heard to making conceptual models as part of the design process?

A lively discussion ensued. Some respondents were unclear on what I meant by “conceptual models,” which speaks to the lack of mainstream awareness of this crucial design artifact. (Here’s my latest stab at clarifying.) Others, clear on what conceptual models are, pointed out that the process matters more than ‘deliverables.’ Great point.

But I’m especially interested in the objections. Here are some that represent what I see as the main gist. Chris Avore pointed out that conceptual models are seen as “too hand-wavey or theater-like,” and that they “lead to a few head nods but the world/plan/goal doesn’t change at the end.” To put it bluntly, as Hà Phan did, some people see conceptual models as “bullshit.” (My take: true insofar as they know about modeling at all; I suspect most people don’t.)

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