ep. 20: Anticipating futures with design research
6 min read
Last week, we explored futures thinking: a mindset and approach to explore, anticipate and plan for potential futures. We offered a primer in futures thinking, highlighted why we should practice futures thinking when designing emerging products, and offered three things you could start doing today to shift towards a futures thinking mindset.
Today, we share the second episode in this three-part series, exploring different futures thinking approaches and methodologies. We will focus on a design research method called anticipatory ethnography.
Origins in speculative design
Last week, we discussed speculative design - a futures thinking approach that focuses on designing for how the world could be, asking questions, finding problems, and designing for the future. Speculative design can be contrasted with traditional design, which designs for how the world is at present, answering questions, solving problems, and designing for production.
One speculative design approach is called design fiction, in which one designs with stories or within the world of a narrative. An example of design fiction is Spike Jonze’s science fiction movie Her, which explores the relationship between a man and his AI virtual assistant, in a future where AI is seamlessly integrated into daily life.
Anticipatory ethnography: a case study
Design fiction can be leveraged in design research using a method called anticipatory ethnography, developed by researchers at Lancaster University. Specifically, we can use design fiction “prototypes” (the movie Her would be one example) to study the process that created the design fiction, the content of the design fiction, and how the audience (e.g., design research participants) interact with or perceive a design fiction. For instance, if you were a team building an AI assistant, you could use the film Her as a prototype to gather early feedback on people’s attitudes around AI assistant technology.
I’ve applied anticipatory ethnography when leading design research for Adobe Aero (augmented reality (AR) authoring application). The research objective was to identify how participants, aligned with Aero’s personas (built through earlier research), sought to augment their reality, and by extension, the value (if any) they saw in an AR creation app. Importantly, most of these participants did not yet have experience creating in AR, so could not share first-hand experience with the medium. In other words, they were an anticipated audience.
This sample of an anticipated audience (all creative professionals) participated in creating a design fiction, via a prompt. Specifically, each participant was provided with three printed photos of scenes, one at a time, that one may typically encounter in day-to-day life (an empty apartment, a busy street, a room in a museum). For each image, they were given the prompt, “How would you make this ordinary scene extraordinary?” They then could use three different colors of markers to draw on a clear acrylic sheet, placed on top of the printed image of everyday scenes. What did participants draw?
Two clear patterns emerged across the sessions. First, participants whose design practice focused on environment design depicted static objects and focused on precise layout and measurement of objects in an environment. Second, participants whose design practice focused on UI/UX design included numerous interactive elements.
This prompt helped transport the participants into an alternate reality where anything was possible, simultaneously revealing what they sought to create in an AR application, and if and how an AR app could bring them value. As participants drew on the acrylic sheet, they also started to build a narrative around the scene, such as how they got there, and whom they would invite into this virtual world. Without this approach, it would have been difficult to gauge what participants would value in an emerging technology they were unfamiliar with, and for which no product prototype yet existed.
These insights and recommendations from this study led to specific features being developed for the application, such as a code-free system for building interactive experiences. One example was support of audio and visual files, and the ability to have videos orbit around a target without needing to use code - all capabilities that would be required to actualize the outer space scene.
Takeaways
The exploration of futures thinking through the lens of anticipatory ethnography and design fiction can help teams better anticipate user needs, design more engaging and interactive experiences, and navigate the uncertainties of future technologies with greater confidence. Methods like anticipatory ethnography are key to creating products that are not only technologically innovative but also deeply connected to human needs.
Three key takeaways from the practice of anticipatory ethnography are:
Identify design fiction that would serve as learning material for your product: If you were building an AI assistant, you could use the movie Her to learn how people might feel about or interact with such technology in the future. Identify what a design fiction (e.g., prototype or narrative) would look like for your product area. This requires aligning on the future vision of the product, and envisioning different potential futures in which that product could exist.
Leverage design fiction for early feedback: Use design fiction to help you gather feedback from your anticipated target audience on your emerging technology before it’s fully developed. The Adobe Aero design research case study we explored here showed how the audience can participate in creating this design fiction together with the people building the technology, helping the team build a desirable solution.
Learn from the process of speculative design: In addition to anticipatory ethnography, teams can design a speculative prototype as a way to explore potential futures, focusing on designing for how the world could be, asking questions and finding potential problems.
Stay tuned for next week, where we share our third and final episode in this three-part series, exploring different futures thinking approaches and methodologies.
Human Computer Interaction News
Generative artificial intelligence, human creativity, and art: Researchers investigated the implications of incorporating text-to-image generative AI into the artists’ creative workflows. Generative AI significantly boosted artists’ productivity and led to more favorable evaluations from their peers. While average novelty in artwork content and visual elements declined, content novelty increased, supporting that generative AI helped facilitate idea exploration.
AI-generated images and video are here: how could they shape research? Tools, like Midjourney, Stable Diffusion, and DALL-E, are being used by research scientists to create visuals for papers and presentations. This article cautions about the risks of fake data and inaccuracies, and discusses backlash from certain scientific communities and the evolving policies of journals regarding the use of AI-generated content.
Design2Code: How far are we from automating front-end engineering?: The authors created a benchmark of 484 real-world webpages to test the ability of multimodal large language models to generate code based on screenshots. GPT-4V performed the best on the task, relative to other models tested. Human evaluators thought GPT-4V generated webpages could replace the original reference webpages in 49% of cases in terms of visual appearance and content. In 64% of cases, GPT-4V-generated webpages were considered better than the original reference webpages. Areas of improvement for open-source models include accurately replicating visual elements and layout.
That’s a wrap 🌯 . More human-computer interaction news from Sendfull next week.
Building a product for anticipated audiences? Sendfull can help. Reach out at hello@sendfull.com