AI · · 11 min read

Experiencing the next mutation: user characteristics, defining success, and a new way to research mutative patterns

I’ve talked to designers, developers, users, coworkers, and strangers about the theory and the practice behind mutative design and Selene’s nascent mutations.

Experiencing the next mutation: user characteristics, defining success, and a new way to research mutative patterns

In the months since launching Selene and the second post about Project Phoebe, a lot has happened. But most of that isn’t important.

What’s most important to me is that I’ve traveled from Mountain View California to New York City to Warsaw, Poland to talk about mutative design. I’ve talked to designers, developers, users, coworkers, strangers, my partner in crime Francisco Franco, and — yes — to myself about the theory and the practice behind mutative design and Selene’s nascent mutations.

At times it’s felt like I haven’t been getting enough work done on Project Phoebe to publish another piece, but it only feels that way because I’m having so much fun talking to people about it.

What I’ve experienced through all of this, though, is that people are excited about this possible future. The implications for accessibility (including situational limitations) and even more intimate experiences with the devices we carry and see around us are big and sound magical. But along with this enthusiasm, I’ve gotten a ton of great questions. Questions that pick out a lot of the fundamental problems we’ll need to solve to bring mutative design to its potential, and questions that highlight for me some of the unnamed or unexplained pieces of theory that will help us talk about mutative design in the future.

In this post I want to take a step back and define some terms, walk through some of the fundamental questions, and provide some possible answers before looking at what’s next for Project Phoebe.

Refining terms

Outside fundamental questions, I’ve gotten a lot of feedback that’s lead to new explorations for mutative design and feedback that’s illuminated new ways to talk about the concept. We’ll dig into some of that here, refining some of our existing terms to better express the methodology we already have.

Characteristics, realities, and behaviors

In the first two posts on Project Phoebe, I discussed “user realities.” The phrase was used interchangeably with “characteristics” to describe the fundamental facts about a user and their situation that impact the ways in which they use interfaces and systems.

But I think as we work toward researching and implementing more mutations, it might be necessary to break this down and separate the terms. While user realities refer to groups of factors that may impact interaction, we can zoom in further and see individual characteristics and attempt to understand how they might interact with one another.

A characteristic is part of a reality. It can be something as simple as exposure to bright sunlight, or as complex as literacy or familiarity with digital interfaces. Whatever it may be, a characteristic is just one fact about a user that Gaia uses to paint a complete picture of that person’s ongoing needs. Thinking of the term this way gives us greater freedom to explore and discuss how mutation happens.

Getting even closer, we can observe behaviors, or things the user does or experiences that don’t actually form an ongoing characteristic. These behaviors can manifest a true need for the user without becoming part of their ongoing reality. Behaviors may be things like driving a car, trying to use the device with soiled hands, or even navigating through an app a certain way.

Having broken out the user reality into these components, the obvious next question is — how does Gaia decide to trigger a mutation in response?

The mutative lifecycle

In one session, someone gave me the example of arguing with their girlfriend over text — the next day, after the argument, would some of the keyboard’s keys be dramatically larger or smaller in response to a long series of imprecise taps?

We can’t be sure if resizing key targets would really be a good mutation without further research, but to actually answer the question we have to define the mutative lifecycle a bit better. In other words, we should begin to explore how a mutation is born in response to user characteristics and behaviors and whether those inputs are significant enough to even cause a mutation.

In this particular case I think we would not expect to trigger a mutation. The argument in question took place once, over one night, so it should be clear to the system that this is a short-lived state, rather than a true characteristic or behavior. Furthermore the behavior ostensibly only impacts one component of the system — the keyboard.

Mutations for characteristics should ideally happen gradually, with speed increasing as we grow more certain of the characteristic. Mutations for behaviors, while more sporadic, should be executed even more cautiously, as a behavior that’s not based on a characteristic may pose a less pressing need for the user, and may be more difficult to confidently identify. That said, mutations for short-lived states should either happen instantly and continually until the behavior is done or not at all.

So it’s possible that in our text message argument example, the keyboard could change in the moment to better facilitate angry typing, but it’s also likely that change would be too risky and too specific and the system would avoid it altogether.


Desire paths

Something I’ve been asked about a lot is whether mutations might adapt to user preferences and not just realities, characteristics, or behaviors. For example, if I — as a user — consistently go into the settings menu to tweak one setting or another, might that setting get surfaced somewhere closer to the main screen so I can accomplish that task faster?

I think there are a couple of answers to this question, but my general instinct would be that we need more information — as designers — about that feature. It might be the case that the feature shouldn’t be in settings at all. Maybe most users are tweaking this setting and whoever builds the interface just isn’t analyzing it explicitly. Ignoring whether we’d break mental models or muscle memory by moving features, is it mutative design’s responsibility to solve for bad or ineffective design?

The short and very easy answer is “no.” But the more thoughtful and realistic answer is that the question is more complex than it lets on. When speaking with designer/developer Nick Butcher recently, I learned about a design experiment done with a sort of dashboard interface, where panels would actually respond to frequency of usage by — for instance — taking on more saturated colors while other panels gave up focus. This approach is kind of like allowing a “desire path” to form through the UI. When people feel like the sidewalk is too cumbersome, they cut through the grass until a path starts to form.

It isn’t outside the realm of possibility that this sort of thing could be a mutation of its own, but ultimately we have to continue asking — is this really responding to a user’s needs and helping them more successfully use the interface? How could we know the answer to that? We’ll explore this later in the post.

Characteristic collision

One great question I got during a talk at IDEO was about conflicting characteristics. Is it possible for two mutations — both responding to a real need — to collide in a way where one conflicts with the other? Of course the answer to this is yes. But how does Gaia respond to this?

The example given was from Selene. The app has a “contrast mutation” provided by Gaia that enhances contrast by shifting certain color values in response to changing light conditions. What, someone asked, would happen if the user had low vision and therefore special contrast requirements? This example was fairly easy to solve for — in this case, the vision characteristic would take priority over the contrast mutation. Since enhanced contrast would likely be part of Gaia’s accounting for low vision, that would be the baseline, leaving little room for the contrast mutation to play out in response to light.

There are “harder” examples than this, but ultimately characteristic collision is just a thought exercise for now — we can’t yet predict exactly what mutations will prove successful for every given reality. And this limitation leads into something that I think will be at the core of mutative design’s tangible implementation: determining whether a mutation is successful for a given need.

Gaia and determining success

Gaia, introduced in the last post on Project Phoebe (and the Selene sample app), is ultimately intended to become a platform for mutative design, so that mutations would be managed centrally, rather than being the responsibility of each individual app.

We aren’t there yet, but it is important to go a little deeper on how Gaia should work so we have a clear vision for what to try next.

Basically, Gaia would be responsible for managing, containing, and distributing instructions for mutations to connected apps. It would then gather information about the “success” of each mutation from those apps, and from that analysis adjust mutations for future iterations.

This cycle mimics the existing cycle of testing, feedback, iteration, and rollout that we already do as software designers and developers, but automates and distributes those changes in a way that allows the experience to really belong to and actually help every user. And that sounds great.

But if we think about it for a minute, the complexities immediately become apparent. Perhaps the most fundamental challenge here — ignoring for now the code behind such an undertaking — is determining what “success” means for a mutation.

This determination of success will influence how users experience the mutation and whether the mutations are truly serving their needs. To figure out how we might define this, let’s first look at what we know about our goals for mutations.

  1. After the starter state, we want mutations to happen over time, not in great leaps.
  2. Mutations should balance impact with perceptible change. We want the greatest impact with the smallest perceptible change.
  3. Mutations should only happen in response to a real and ongoing need, not in response to situations that are one-off or very rare for the user.

So ideally, “success” means meeting all three of those criteria and quantifiably improving the rate at which users are able to accomplish goals in your app.

Points 1 and 3 relate to the intent of the mutation, or its reason for existing. An appropriately long timeline for determining whether a mutation should happen validates whether it’s happening in response to a true need and protects the user from “great leaps” of change in the interface.

For example, in Selene, the intent of the contrast mutation is to improve text readability in difficult lighting situations. The “onboarding” mutation’s intent is to help the user learn to create a note, fulfilling the purpose of the app.

We could then define the mutations’ goals as “helping users read efficiently in bright light” and “helping users create a note for the first time.” Success is then based on whether users have performed those actions more with the mutation in place.

These mutations represent two possible paths for defining goals (and by extension success) for mutation.

The first being an implicit acceptance of mutations from Gaia that are reflected across the system. If a user has the necessary reality for contrast enhancement, any component with a background color could automatically receive the instructions for enhancing contrast for certain scenarios.

The second is an explicit statement of intent from the app. Part of the information the app would provide back to Gaia would be a statement defining the goals for certain components. In this case the app would tell Gaia that the goal for the FAB is to create a new note, and it will therefore accept instructions for mutations that will accomplish that goal.

I think both of these paths would be executed concurrently and on an ongoing basis.

Changing how we feel about change

One of the most common and foundational questions I’ve heard about mutative design so far centers on users’ acceptance (or, more commonly, rejection) of change.

An unspoken kind of functionality that — like the mutations themselves — takes hold before we even know it’s there…

Right now in the climate of interface and experience design, change is often met with negative sentiment. As I’ve written before, we live in a reality where updates to something like YouTube’s channel page are described by some users as “utterly horrifying,” sparking backlash and petitions before users eventually convalesce and learn to use and accept the new design.


Measuring a concept like mutative design against this reality paints quite a dire picture, but to measure future possibilities against current expectations is to approach mutative design from the wrong angle.

First, to avoid the issue of backlash or discomfort entirely, we must establish that ideal mutations happen so deliberately and over such time periods as to be almost invisible to the user. From the “starter state,” we’ve already made most of the adjustments we need, and as the interface adapts to the user’s ongoing reality, they’ll only notice an underlying thread of good, usable experiences, rather than great leaps of change. In Selene for example, we balanced impact with perceptible change when implementing the contrast mutation — the change in color is noticeable, but doesn’t negatively impact the experience. Notes are still distinguishable and the layout doesn’t change, but the user gets a better experience in bright light than one otherwise would.

But from a higher level, mutative design has a long road ahead. As the capabilities of personal devices change, so will our perceptions and expectations as users.

As we move from predictive technology to actually intelligent technology, and as we rely more on technology that assists us by knowing us, our attitudes about the capabilities and indeed the responsibilities of interfaces and experiences will change. Like so many individual interface elements that have been born and worked their way into common use and understanding (see: the floppy disk transcending actual metaphor to become its own discrete glyph), mutative design can eventually exist as an expectation. An unspoken kind of functionality that — like the mutations themselves — takes hold before we even know it’s there, providing that no-compromise vision of UIUX for everyone in a way that feels organic and in tune with our changing expectations.

This is a very long road. Between now and then we’ll have a long period of sorting out how mutations work, implementing them, and working on a system like Gaia that can intelligently select mutations on its own. Users have already begun seeing traces of mutations in the apps and systems they use (see Apple’s “Night Shift”), and these kinds of changes will only feel more natural and expected as we move forward.

Announcing Helios

Part of moving toward a future where we don’t just welcome the kind of change mutative design promises but actually expect it is getting a feel for where we are now. There’s plenty to find out about how people will experience mutation, how they will perceive and describe that experience, and how mutative patterns might modulate those things.

To begin this exploration, developer Francisco Franco and I are collaborating on Helios, a test suite for mutative patterns.

The app will allow researchers to adjust and — side-by-side with users — test a growing set of mutation patterns to better understand how mutations work and how the experience changes when we go from a normal interface to a customized one, both all at once and gradually.

Of course the ulterior motive for Helios is to demonstrate that implementing mutative patterns right now doesn’t have to be a complex or intensive process. In the open source sample app Selene, we showed that something as impactful as the contrast mutation doesn’t require major upheaval to implement, and Helios will demonstrate even more intricate patterns that will give users a truly personal experience, and how those patterns interact with one another.

Until the next mutation…

So what’s next in the more immediate term? From here I’m going to continue engaging the community on Project Phoebe and mutative design. Speaking about the possibilities of mutation with amazing and talented developers, designers, and users has taught me so much about what we still need to figure out. And with collaboration from the community, videos, writing, new mutative explorations and demos, and just plain talking, we will eventually see Gaia come to life as a platform for mutative design.

One reaction that has stood out to me since I started talking to people about Project Phoebe was when someone asked, essentially, how we could ever hope, realistically, to make mutative design a reality. Beyond the theory, the concepts, and the samples, how could something like this actually become feasible on the scale we’ve described?

“…I mean, it seems like it would be almost impossible to implement this,” a man in the audience said.


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