Futures for all, not just for one

The events of this last week reflected many of the themes we’ve touched on here for over a year: the responsibility of platforms for the conversations they promote, the failure of imagination that occurs when leaders don’t listen to enough perspectives, and how online and offline influence each other to the point where the boundary is mostly meaningless. We are sure there will be much more to say as we all learn more about what happened and come to terms with these risks to our institutions, but make no mistake: nothing that occurred on January 6 was unpredictable.

In this issue we hope to inspire new ways of thinking about our futures: moving beyond a single user to a complex system, considering who defines what future we aim for, and adapting and inventing in the face of radical change. Hopefully these tools will help us be more imaginative about our possibilities, and steer our futures toward brighter, more collaborative outcomes.

—Alexis & Matt

1: Camera obscura: Beyond the lens of user-centered design

Over the holidays, Alexis — along with Devin Mancuso, Lis Hubert, and Diana Sonis — published a deep dive on the limits of user-centered design, and how we might integrate systems thinking into our design practices to create ethical systems that work better for everyone. While UCD has facilitated the design of some incredible products and services, it is only one framework. Any framework is a lens through which you see things — it allows you to see some things quite well, but almost always at the expense of obscuring others.

We identify three key gaps in user-centered design:

  • First, by focusing on the user, UCD has a tendency to obscure the experiences of other participants in the systems we design — those who aren’t end users, per se, but who interact with or are affected by the system.

  • Second, by focusing on ease of use, the approach obscures the friction in an experience. Often that friction doesn’t disappear, but instead gets offloaded on to others whose experiences are less visible or less privileged.

  • Finally, UCD’s focus on “successful” experiences obscures possibilities that lie outside of predetermined success metrics, preventing us from designing for uncertainty, failure, or experimentation in the ways we might.

We don’t advocate for throwing UCD out the window, but rather layering systems thinking on top of it to create a blended approach that can lead to more ethical and inclusive outcomes. The essay delves into how we might do so, ending with 5 tactical design strategies to help put this approach into practice.

“In effect, many of the problems that we see in product and platform design are not due to malice, but simply because UCD as a practice makes some problems more visible than others. There is a whole set of second-order experiences that we don’t actively design, but happen as a consequence of what we design. Which means that there’s the potential for a great deal of positive change that can be created simply by shifting how we look and what we look at.”

Camera Obscura: Beyond the lens of user-centered design


2: Loungewear, ghost kitchens, & co-presence

Alexis’s mentor and friend, John Maeda, is incredibly adept at finding interesting signals of what’s to come, as evidenced by his annual CX / Design in Tech reports. Here he has gathered a set of clues about trends in tech, home, fashion, and food for 2021. Some the most interesting and/or likely trends he calls out include:

  • New hardware/software combos that bring unprecedented co-presence experiences.

  • Browsability and discovery experiences will give way to more chat experiences.

  • Loungewear as an elevated category. What you wear below the Zoom line don’t matter.

  • Voluminous wear to make you feel extra big within a Hollywood Squares grid.

  • Ghost kitchens, ghost food halls, and touchless service — think OEM of food.

  • Hybrid restaurant models and bar quality “canned cocktails” are coming.

See the full list at the link below!

Surfing For 2021 Trends In Tech, Home, Fashion, And Food


3: Images of the future as a diagnosis of the present

We struggled to find a short summary of this essay, as it has several concurrent threads of analysis and scholarship that focus on the role of society’s imaginations of its futures. It was written prior to the events of 2020 — the novel coronavirus pandemic, the racial unrest surrounding a reckoning of police brutality and injustice, the horrific events of this last week at the Capitol — and was meant as a companion to an exhibit at the Walker Art Center in Minneapolis, which itself is now inaccessible due to Covid-19 restrictions.

These recent developments mirror a central premise in the essay, one we and other writers have struggled with throughout 2020. When a society has difficulty imagining its future, especially in positive, utopian ways, that society is at risk of collapse. In some cases this inability to imagine is imposed: the essay reminds us of how amidst the shiny technological futures of World’s Fairs, there were often displays of native peoples’ traditions that served to contrast with the corporate exhibits, effectively leaving anyone who wasn’t white and European out of the conversation. Who has the right to imagine a future is as important as who has the capacity and the optimism.

We encourage you to read this deeply, as there’s a lot to consider. For us, we were struck with how deciding on a single vision of the future can exclude so many other alternatives, and that to build an equitable future one must consider multiple futures, each extending a different cultural present and its assumptions into the realm of new possibility.

Defuturing the Image of the Future


4: Clam sensors & moth drones

Most of our metaphors about intelligence are reflections of technology mapped onto biology. We think of a brain as a living computer; we joke about how learning a new fact may overwrite an older one; we consider the mind to be the control center for the body, issuing instructions to the more mechanical motion of the body. Taking lessons from biology and applying them to computation is far more rare, but as these stories show, could bear very interesting results.

First we find researchers attaching an antenna from a recently-deceased moth to a small quadcopter. The antenna is the source of the moth’s keen sense of smell, and when attached to these circuits, the antenna will create electrical impulses — just as it did for its moth host — when it catches the scent of a flower. By borrowing navigational techniques from the moth, and even mimicking how it uses its wings to draw air across the antenna, the quadcopter can hone in on a scent with 100% accuracy. That is, it can for the four hours the antenna remains “alive” following its removal.

Second, we find a much lower-tech, but far more humane, partnership between animals and machines. In Poland, clams have been used to monitor the quality of local drinking water. The clams are then put into the flow of the city water supply; the clams are very sensitive to impurities, so if the water becomes contaminated, the clam’s shell will shut, triggering a shutdown of that water source. Each clam is only borrowed for the role for three months, and when that time is up, it is returned from its original lake and marked so that it isn’t chosen for service again in the future.

This Drone Sniffs Out Odors With a Real Moth Antenna

Someone Explains How Poland Uses Clams To Control Its Water Supply And It's Pretty Crazy


5: AI and disability

In this episode of the Mixtape podcast, Sara Hendren, Meredith Whittaker, and Mara Mills discuss how AI presents particular questions and challenges in the context of disability, especially when understood through medical vs. social models of disability. The medical model perceives disability as a deficit or aberration that needs correction, whereas the social model of disability sees the deficit in how society and the environment support a wide variety of human bodies and needs.

When we look at AI, machine learning largely works by analyzing large sets of data and learning to understand what’s average or “normal”. They are by definition designed to ignore or discard outliers. This reification of existing norms is a problem for AI in multiple contexts (racial and gender bias, for example), but notably so in the realm of disability, where it is likely to understand disability as an outlier or problem rather than as a signal that the larger system needs to adapt.

When we look at the history of technological innovation, there are many notable examples where innovative technologies were initially developed as adaptations for disability. If we’re using AI as a substrate for innovation, how might the current models for machine learning be limiting us? Focusing on current norms leads to further cementing those norms. We lose sight of opportunities that come from focusing beyond the “average”, and it diminishes the role of alternate perspectives in developing truly innovative change.

Mixtape podcast: Artificial intelligence and disability


6: Submit your homework in Red Dead Redemption

It’s been a long ten months of Zoom and Google Meet for workers and students alike, so it’s no surprise that teachers are taking to Instagram, Tik Tok, Among Us, and other collaborative social and gaming platforms to better reach their students. This story touches on many of the creative ways that teachers and office workers are adapting beyond “online meetings” into new, compelling adaptations of technology.

This evolution of how we collaborate has certainly been accelerated by the pandemic, and creativity has often been borne out of necessity. This phase of invention is encouraging, and one that has been seen with most other disruptive technological advancements. When televisions were first developed, actors would dress in suits and gowns to read radio play scripts, and our current use of Zoom to put a traditional meeting online isn’t far off from this mapping of an old concept onto a new platform. We’re excited to see people — teachers, in particular — investigating the possibilities of these new interactions to create brand-new models for what learning and cooperation can feel like.

Kids are sick of Zoom too—so their teachers are getting creative


One magical mystery tour

The latest link in our “enjoying the computational gaze” series is this AI-generated album in the style of The Beatles. It’s very accurate and yet SO wrong at the same time. Take a listen!

An album in the style of The Beatles, generated by OpenAI Jukebox

An album in the style of The Beatles, generated by OpenAI Jukebox