Project team
Kitty He, Veronica Wojnas, Jade Zhao
Role
Product designer
Timeline
8 Weeks (Feb.2020 - Mar.2020)
Joybite is portable smart utensil and a companion app to help people have allergies and dietary restrictions to discover new flavors and food
As part of this speculative technology-driven project, we looked at how to design the data life cycle for AI and mitigate ethical risks
Guided by Oscar Murillo ,the class explored how speculative technology might change people's life within next 5-10 years. Our team were interested in design opportunities and innovation in the food industry.
How will technology elevate the food consumption experience within the next five years?
Given this is such a broad topic, we did secondary research to find areas we want to focus on working. We identified the tension between emotion, social and function in food experience
Flavor is the distinct impression of food or drink that is perceived through our senses of smell and taste. It refers to the smell , the texture as well as the taste of food.
Think back to some holidays. There is always a common theme that accompanies any celebration: food. Even in our fast pace culture, people still set aside time to enjoy eating together.
Eat safely is a challenge for a considerable amount of people in US
Bring the pleasure of eating and the delight of food discovery back to people who have multiple allergies and dietary restrictions.
Joybite is a portable smart utensils and a companion app to help you detect food components and allergens, and discover new flavors and food you like.
Joybite is composed of two components: a smart portable utensil and a companion app. Data is the key to tie the software and hardware together.
To better understand how Joybite works in the real context, let's meet Julia and walk through her story together.
Julia is a recent graduate who is about to start a new remotely-based job at a big tech company. Her job has no home base, so she’s excited to move away from the Seattle area to her dream city: Paris!
Julia has multiple food allergies. She loves to explore the local and new cuisine but she is concerned about whether the food will be safe for her to eat or will she like it.
Luckily, Julia found JoyBite online and decided to bring it with her to Paris.
She received and unboxed JoyBite. The utensil has swappable heads and an embedded spectrometer that can detect the composition of the food.
She downloads the companion JoyBite app. In the onboarding process, Julia got an overall sense of how the product detects bites, learns bites, and find bites for her. She loves it and signs up for a new account.
After creating her account, she is prompted to fill out her flavor preferences, allergies info, and set the level of data captured by JoyBite.
After setting up JoyBite on the app, Julia decides to take the utensil to the restaurant to give it a try.
She orders a Pad Thai. Before she starts eating, the app optionally recommends her to take a photo of Pad Thai. It also prompts her to use the JoyBite utensil to detect her meal to check for unwanted ingredients.
It's all clear!
Julia starts enjoying her Pad Thai. JoyBite continues to scan as Julia eating to get more data on the dish's flavor profile.
After eating, JoyBite generates a rating of how much it thinks Julia enjoyed the dish based on her previous choices and comments. It also gives her a chance to add simple feedback and comparisons to other meals.
One day, Julia is searching for a place to have dinner using JoyBite. She decides to try a restaurant that has a high flavor matching rate and many dishes that are safe for her to eat.
Julia goes to the restaurant and shows her flavor profile QR code to the waiters, after scanning the QR code the restaurant knows about her food allergens and flavor preferences.
That way, they know how to customize dishes that are safe and delicious for her to eat. Julia gets to enjoy new restaurants and meals while staying safe.
From then, going out to eat is a fun time of discovery for Julia!
So this is JoyBite, an innovative idea using AI to advance people's food tasting experience. While with bold and novel ideas, we are creating something that can impact the entire landscape and interactions in society. As designers, we need to think ahead of how we ensure AI-based products are not used as harmful factors to society.
Treat all stakeholders equitably and prevent undesirable stereotypes and biases
Create systems and outputs that understandable to relevant stakeholders
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Build systems to perform safely even in the worst-case scenario
Protect data from misuse and unintentional access to ensure privacy rights.
Empower everyone, regardless of ability and engaging people by providing channels for feedback.
Take responsibility for how systems operate and their impact on society.
The value tension map sheds lights on where the areas that users might have their most concerns on our product. From there, we conducted usability test and were able to propose actionable solutions to mitigate the tension.
Our initial concept is that JoyBite Utensil will passively record users’ sounds while they are having meals so that the AI could know whether they enjoy the meal or not. However, participants in our user test are uncomfortable about being recorded what they say while they are having meals.
I wouldn’t be 100% comfortable with this option. Enjoying food seems like a private thing. - P4
We realized that the initial idea is efficient, but not necessarily effective and responsible. We reconsider the purpose of the audio data and realized that our end goal is to recommend food that is matched with the users flavor profiles. It led us to think about an alternative data-collection approach to get this data from the users. What we end up is to add a quick and low-effort poll after users have a meal.
Users show their interests in our concept and are willing to have Joybite leverage their data to help them discover food. However, they are still very concerned about data not being well protected and used by other parties.
There's no confirmation saying all the data will be extremely securely protected and how it will be protected. - P4
In this case, change we made here is to bring up a clear consent mechanism at the very beginning. We provide a clear explanation of how the data will be used at the first place and give users chances to opt out from sharing data with third party
In our initial concept, the smart utensil will send blink lighting signals while it detected food allergens. However, later we realized using a smart utensil in a public area discloses another layer of privacy concern. Participants were concerned about stereotypes reinforcement because of the lights while they have a meal with other people.
I will feel embarrassed if my utensil started blinking while I'm having a meal with friends. - P3
To address this harm, we switched the noticeable lighting signal to a subtle and haptic vibration feedback on the utensil. So that users don’t have to worry about being noticed by others when they find things they can’t eat in the food.
To set up the initial database, our original design intent to ask users to link with third-party accounts and share their data with us. However, users are unsure about what types of data we are using from the external accounts and are skeptical about linking them with Joybite.
I'm not quite comfortable with linking my Yelp. I mean, I don't really know what data you will pull from it. - P5
We recognized the benefits of linking with third-party accounts could rapidly bring us an abundant amount of data to build the database at the beginning. However, the tradeoff was not being able to earn trust from users. Thus we decided to give users the option to finish a short quiz on their food preferences or show them what data we will pull out if they choose to link with third-party apps
Thanks for reading
