Zine making with small data
Speculative Design, Product Design
COURSE NAME
CONVERSATIONS WITH MACHINES: LECTURE & WORKSHOP SERIES
An interactive map reflecting my relationship with my Amazon Alexa
COLLABORATORS
Individual
PROJECT YEAR
2024
Ideation
The dining experience is shaped not only by the food or the rituals around it, but also by the personal memories it evokes. Even an ordinary meal with family, friends, or loved ones holds deeper meaning. We wonder: What if we could capture these moments in a tangible form and share them with others?
Dining connects us to memories and sparks ideas of food, culture, and the stories that unfold around the table. Inspired by the art pieces shown, a tablecloth could serve as a canvas for documenting our meals —where we sit, what we eat, what we do, and who we share these moments with. This medium, simple to fold, pack, and gift, becomes a meaningful invitation. Our friends who receive it are invited to join us as guests to celebrate these intimate and cherished moments of our lives.
Dining connects us to memories and sparks ideas of food, culture, and the stories that unfold around the table. Inspired by the art pieces shown, a tablecloth could serve as a canvas for documenting our meals —where we sit, what we eat, what we do, and who we share these moments with. This medium, simple to fold, pack, and gift, becomes a meaningful invitation. Our friends who receive it are invited to join us as guests to celebrate these intimate and cherished moments of our lives.
PROCESS & DEVELOPMENT
We began by narrowing down to three ideas from our precedent study.
- On-the-go fine dining experience
- Using projection to enhance dining experience
- Designing utensils to simulate conditions that hinder eating to build empathy.
The final idea ended being a combination of aspects from the first two ideas: design and create a tablecloth that would transform to fit different table sizes and arrangements. We wanted to bring in elements of cultural exchange that we explored in the second idea, by drawing out how we eat back home with our family.
- On-the-go fine dining experience
- Using projection to enhance dining experience
- Designing utensils to simulate conditions that hinder eating to build empathy.
The final idea ended being a combination of aspects from the first two ideas: design and create a tablecloth that would transform to fit different table sizes and arrangements. We wanted to bring in elements of cultural exchange that we explored in the second idea, by drawing out how we eat back home with our family.
Our first prototype was a pill-shaped table linen that would cover the entire surface of the dining table. Placements for plates are marked on the linen to dictate the position of the plates on the mat. We sew on buttons and draw fold lines, which allows the user to fold the linen to serve variety of arrangements and numbers of guests. The paper prototype aimed to achieve a similar result, but in a rectangular form.
We discovered however, that in the process of creating these foldable linens, we lost our original vision for the project: To share my own personal dining experience to other people. The demarcations of plate placements made it sterile and typical. We explored using different types of fabric to allow varied arrangements, but we ended up backtracking to our very first idea. Instead of creating a table mat that can conform to any table size, we decided to simply create 1 table mat, designed for 1 person of 1 particular dining experience.
There are areas demarcated by different colors of clothes representing the family characteristics, with names attached to each plate. We also added placements for phones and tablets, with QR code to the show or app that they would often watch/use while eating. The compass in the corner is less about exact position of the table mat in reference to the Earth’s magnetic field, but rather to indicate where the TV, the center of family dinner ritual, should be in reference to the table. There is a flexible area for shared dishes defined by cute illustration.
Additionally, we made a manual to illustrate the dining experience on the tablecloth, including an introduction to the family, the legend for dishes, utensils, and accessories, and the scenario of everyday dining routines as storyboards. We encourage those who receive this gift to experience life on the cloth immersive by imitating the indirect dining settings.
The final product is a true collaboration, with every team member contributing to each stage—from sewing and pattern design to painting. Together, we have worked to preserve these memories, as if we ourselves were part of the family.
FINAL PRODUCT
The final tablecloth mat has different colored fabric stitched on, representing different family members. This particular mat represents Brie’s family. The Southeast corner is reserved for her brother, who often eats away from their family and in his own room. The corner is therefore detachable and reattached via buttons. Those receiving this can also scan the QR Code on the iPad area and cloth edge to see what the gift senders see during the meal and get the digital version of the manual.
Coming soon :)
THE PROJECT
An AI-driven web-based plugin that provides better communication between users and generative AI tools
Discover & UNDERSTAND
Our journey starts from the question below: As a designer, have you ever used Generative AI tools in design process? And have you ever felt misunderstood by Generative AI tools in design process?
We collected opinions from designers across different disciplines and integrated them into an affinity diagram. The takeaways from this status quo guided us to our design space: human-AI communication.
We collected opinions from designers across different disciplines and integrated them into an affinity diagram. The takeaways from this status quo guided us to our design space: human-AI communication.
define question
How might we ease the process of communication between designers and generative AI tools by fostering mutual understanding?
IMAGINE
Our proposal is to leverage a web-based plugin with language process ability. Users label the results after comparing the current outcome with their mind and iterate the suggestion on the plugin. The human-in-the-loop method will provide users preferred results by achieving consensus.
RAPID PROTOTYPING
Feature 1: User Domain Settings (web-based plugin)
Once the plugin is installed and logged in, the interface will prompt user to select their corresponding domain in design professions, which parameters will be applied on image generation and suggestion-making processes of the plugin.
Once the plugin is installed and logged in, the interface will prompt user to select their corresponding domain in design professions, which parameters will be applied on image generation and suggestion-making processes of the plugin.
Feature 2: User-oriented Image Classification / Generation (web-based plugin)
Once user begin to execute text-based image generation processes, the plugin will provide users with tailored user-friendly image labels; which will allow the user to revise the labels based on one’s interpretation of content.
Once user begin to execute text-based image generation processes, the plugin will provide users with tailored user-friendly image labels; which will allow the user to revise the labels based on one’s interpretation of content.
Feature 2: User-oriented Image Classification / Generation(web-based plugin)
Image re-generation based on revised image classification labels will help users acquire updated contents more precisely; while helping the algorithm to learn user’s domain knowledge and pattern - providing data for the algorithm to improve performance overtime.
Image re-generation based on revised image classification labels will help users acquire updated contents more precisely; while helping the algorithm to learn user’s domain knowledge and pattern - providing data for the algorithm to improve performance overtime.
Feature 3: User Profile Settings (dedicated web interface)
The web-based plugin also provides a standalone website that allows the user to retrospectively review domains and labels associated with their profile, recycling previously removed parameters while gaining more insights about their interaction patterns.
The web-based plugin also provides a standalone website that allows the user to retrospectively review domains and labels associated with their profile, recycling previously removed parameters while gaining more insights about their interaction patterns.
PRECEDENT STUDY
We wanted to build an object and experience that would embody what it would be like to be underground. We explored diorama as a possible final product as we wanted to design an experience, but also build a physical prototype. We took heavy inspiration from underground, ant colony dioramas.
PROCESS & DEVELOPMENT
Our initial sketch consisted of three levels: underground, ground, and canopy. Both the canopy and the ground level would have holes cut through the base, which would allow us to drip water through to simulate rainfall. The trees we build would play a vital part, not just in terms of aesthetics but also in terms of the experience itself. We wanted to design it so that the water that falls from the canopy would drip down, saturate the tree and its roots, carrying the water all the way down to the underground level. We also designed a staircase inviting guests to imagine what it would be like to go down into a cave, covered with roots, soil, and the countless creatures hidden underneath.
For the underground level, we built the ‘cave’ with black aluminum foil, poured soil over around the edges, and punched holes on the ceiling through which we snaked through tube cleaners. This would carry the water from above ground to below ground, once saturated. We also cut a large hole in the front panel, inviting guests to reach in and touch the soil as the water drops from the cave’s ceiling. We wrapped the black foil over and around the opening in the center, to help keep the soil contained and sealed. The cotton was threaded through thin copper wires which hung over the two side walls.
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FINAL PRODUCT
The final model is completed with organic soil and manmade trees and clouds. The environment comes to life in our film through sprinkling water over the clouds and seeping into the soil through the tube cleaners. A play on both the Wildcard and Synthesis, this experience allows one to feel the senses of the Earth 6 ft under.
IDEATION
For this workshop, I chose my conversation history with Alexa as my small data set. As a graduate student living on a tight budget, I shared an old house with three roommates, which had no smart home devices installed. My primary interactions with Alexa were limited to playing music and setting alarms to wake me up in the morning. Despite living with the device for nearly a year, the data it contained was surprisingly sparse. This session gives me a good chance to reflect on my relationship with it - a companion spending endless days and nights with me.
This workshop provided an opportunity to reflect on my relationship with Alexa, a companion that silently shared countless days and nights with me. The day before the workshop, I downloaded my interaction data from Amazon and formatted it into three columns: content, date, and time.
During the session, I started by reviewing the most recent conversations. To my surprise, I discovered several interesting, and at times, puzzling, exchanges that had slipped past my attention. As a non-native English speaker, I noticed how miscommunications occurred between Alexa and me. Alexa, being far less sophisticated than today’s advanced language models, added another layer of complexity. These misunderstandings and the relationship we built inspired me as I worked on this zine.
I categorized the conversations into three themes:
Type 1: Correct recognition: lucky me :)
Type 2: Alexa's fault: Due to limited speech recognition ability, Alexa can't read ambiguous commands beyond its skill set and learning algorithm. In this case, it can't parse the command and show:
"Audio could not be understood."
But what happens more frequently is that I can parse what I say but wrong.
Type 3: My fault: Voice recording only works when I press the recording button, but my English skills can't help me figure out what to say in such a short period, so it often captures nothing, which is shown as:
"No text stored."
Sometimes, I would also overestimate its ability, so when I said something that it apparently can't recognize, this is what it thought:
"Audio was not intended for this device."
By examining the data within these categories, I naturally became curious about when these conversations occurred, how their frequency evolved over time, and how both Alexa's and my attitudes and impressions shifted after each interaction. This curiosity led me to focus on two key aspects for my data visualization:
1. A timeline of conversations within each category.
2. A trend map illustrating patterns across these categories.
However, diving into quantitative analysis too early felt restrictive to my creative process. Instead, I took a step back and imagined these trends in my mind, carefully reviewing the dataset and jotting down notes. Through this process, I found myself working as a detective: each conversation’s content and timestamp brought up vivid memories of what I was doing at that moment. These emerging stories felt so powerful and alive that I decided to represent this experience as an interaction within the zine itself.
This workshop provided an opportunity to reflect on my relationship with Alexa, a companion that silently shared countless days and nights with me. The day before the workshop, I downloaded my interaction data from Amazon and formatted it into three columns: content, date, and time.
During the session, I started by reviewing the most recent conversations. To my surprise, I discovered several interesting, and at times, puzzling, exchanges that had slipped past my attention. As a non-native English speaker, I noticed how miscommunications occurred between Alexa and me. Alexa, being far less sophisticated than today’s advanced language models, added another layer of complexity. These misunderstandings and the relationship we built inspired me as I worked on this zine.
I categorized the conversations into three themes:
Type 1: Correct recognition: lucky me :)
Type 2: Alexa's fault: Due to limited speech recognition ability, Alexa can't read ambiguous commands beyond its skill set and learning algorithm. In this case, it can't parse the command and show:
"Audio could not be understood."
But what happens more frequently is that I can parse what I say but wrong.
Type 3: My fault: Voice recording only works when I press the recording button, but my English skills can't help me figure out what to say in such a short period, so it often captures nothing, which is shown as:
"No text stored."
Sometimes, I would also overestimate its ability, so when I said something that it apparently can't recognize, this is what it thought:
"Audio was not intended for this device."
By examining the data within these categories, I naturally became curious about when these conversations occurred, how their frequency evolved over time, and how both Alexa's and my attitudes and impressions shifted after each interaction. This curiosity led me to focus on two key aspects for my data visualization:
1. A timeline of conversations within each category.
2. A trend map illustrating patterns across these categories.
However, diving into quantitative analysis too early felt restrictive to my creative process. Instead, I took a step back and imagined these trends in my mind, carefully reviewing the dataset and jotting down notes. Through this process, I found myself working as a detective: each conversation’s content and timestamp brought up vivid memories of what I was doing at that moment. These emerging stories felt so powerful and alive that I decided to represent this experience as an interaction within the zine itself.
PROGRESS
With a clear purpose in mind, I began prototyping. To best represent a timeline, I decided on a long diagram, which naturally lent itself to a physical form: a multi-folded map. A set of memory cards served as keys, guiding viewers to pinpoint when the stories on the cards occurred. For the comparison between myself and Alexa, I designed a two-direction slider—an intuitive medium for examining the relationship between two entities. This slider also works as a protective cover for the delicate map. With these goals in mind, the physical form took shape smoothly and naturally.
Next, I moved on to visualizing the data using Python. To enhance readability, I focused on refining the design of the legends, selecting thoughtful color schemes, and optimizing the overall layout.
Next, I moved on to visualizing the data using Python. To enhance readability, I focused on refining the design of the legends, selecting thoughtful color schemes, and optimizing the overall layout.
First Functional Prototype
Data Visualization and Processing
Second Prototype: Test for Iteration
FINAL PRODUCT
The final product is a high-fidelity prototype of the zine described above. The colors represent the two entities: me and Alexa, and also subtly reflect the passage of time throughout the day (day and night). The cover is designed as a ruler, with key attitude shifts marked along. Readers are invited to explore these shifts by locating them on the map, creating an engaging, self-guided discovery experience.
REFLECTION
Due to time constraints, I didn’t have the opportunity to iterate further on the prototype, which is a bit disappointing. Additionally, I didn’t receive much feedback from the audience during the showcase. Reflecting on my work, I realized that trying to find a cohesive story in the chart might have been somewhat futile, as the chart itself didn’t provide any additional insights. Similarly, the trend map didn’t reveal the changes I had anticipated before visualizing the data.
It seems that my relationship with Alexa hasn’t evolved in the way I had imagined. Alexa hasn’t grown better at understanding me, nor have I become more adept at interacting with it. Moreover, the dataset from Alexa doesn’t include its own feedback, so the conversation is ultimately one-sided: focused solely on my questions. Although I recalled some amusing responses from Alexa, I couldn’t represent them due to the lack of corresponding data.
Overall, the workshop was a valuable opportunity for me to reflect on my relationship with personal artifacts and to approach them with an interactive mindset. Despite the limitations, it allowed me to think critically about these interactions in a new and engaging way.
It seems that my relationship with Alexa hasn’t evolved in the way I had imagined. Alexa hasn’t grown better at understanding me, nor have I become more adept at interacting with it. Moreover, the dataset from Alexa doesn’t include its own feedback, so the conversation is ultimately one-sided: focused solely on my questions. Although I recalled some amusing responses from Alexa, I couldn’t represent them due to the lack of corresponding data.
Overall, the workshop was a valuable opportunity for me to reflect on my relationship with personal artifacts and to approach them with an interactive mindset. Despite the limitations, it allowed me to think critically about these interactions in a new and engaging way.
Copyright © 2024
Hongfei Ji
Hongfei Ji
