Will You Eat Me, Dutch Design Weekend, Eindhoven, October 2024.
The frameworks that inform the innovation and development of deep learning AI applications are embedded with layers of bias in the status quo. Kate Crawford in Atlas of AI, argues the far-reaching harms of biased technological systems. These algorithms, in practice, not only perpetuate the bias they are built on but also amplify the existing systems of discrimination.
MESIF - Marker of Emotional Stability, Intelligence, and Functionality
has become a universalised scoring system that demarcates the function of an individual in society. This system is an aggregate score of five AI-driven sub-scoring systems - Happiness Meter, Smile Scale, Resting Factor, Labour Rate and Social Life Expectancy. These sub-systems are based on the AI research and experiments of 2024 - Mental-Health Biomarkers, Computer Vision, Movement Analysis, Office Monitoring, and Social Media AI tools, respectively.
Methodologies
Thinking through Making | Narrative Building | Participatory Design | Research through VR | Speculative Fictions
Collaborators
Team Members
(Collective Research + Narrative Building + Execution)
Unity Designer - Yashika Goel
(Collective Research + Narrative Building + Execution)
Unity Designer - Yashika Goel
3D Maker - Emerald Chen
Tools and Mediums
Virtual Reality > Immersive Experience >
Unity for VR Development
< E x p e r i e n c e >
What do you eat in VR ?
Will You Eat Me? is an interactive speculative storytelling experience wherein the audience is invited to create their own cheesburgers using speculative digital food ingredients, while listening to the narration encapsulating the journey of food from today to tomorrow.
a l s >
Why speculate VR Food Futures ?
As climate change fundamentally alters our food production capabilities, there's an urgent need to reimagine our relationship with food consumption. While this future might seem distant, the decisions we make today directly shape tomorrow's dining table.
"Will You Eat Me?" emerged as a response to this critical juncture, using virtual reality not just as a technological tool, but as a medium for embodied storytelling that bridges the gap between current food practices and potential future realities. The project deliberately employs familiar actions - like building a burger - to make abstract concepts about food sustainability tangible and personally relevant. By contrasting comfortable food memories with unfamiliar future alternatives, the experience creates a space for meaningful discourse about food sustainability while remaining accessible to diverse audiences.
Signal - Softbank and their Emotion AI
1. Emotion Cancelling AI that is built for better customer srvice by altering emotional states of the employees through changing tones of customer speech, and AI triggered video montage to calm and relax the employee.
Refer here.
Signal - Bumble AI Assistant?
2. Bumble co-founder suggesting an AI Concierge that would date other people’s AI concierge so you don’t have to talk to anyone and everyone.
Refer here.
Signal - AI Therapists
3. Masses increasingly seeking AI advice for their mental health concerns through AI chatbots and AI therapist bots, disregarding harm enacted through computational bias.
Refer here and here.
< M e t h o d
o l o g i e s +
P r o c e s s >
o l o g i e s +
P r o c e s s >
How does the Machine Learn?
Chapter Four
Feedback Reflections
Feedback Reflections
Citations
One
<G a t h e r i n g
D a t a >
Datasets are active participants in defining the function of machine learning models. Data is primarily human. So,
How might we ethically collect data to programme equitable AI models and systems?
Extractivist Data Methodologies
Ethical + Feminist Data Methodologies
Dubious or Hidden or False Consent and Permission
Informed Consent
Hidden use of Data -
The Function of Data Sharing is not Defined or Shared
The Function of Data Sharing is not Defined or Shared
Transparency about Outcomes Generated
from Use of Shared Data
from Use of Shared Data
Reproduction of Biases
through Inappropriate or Biased Labelling
through Inappropriate or Biased Labelling
Diverse and Communal Collection
Allows for Dilution of Biases
Allows for Dilution of Biases
Adopting, learning and practicing with human first data methods, I designed a 3 part workshop focusing on
co-creating narratives, sharing, and collecting.
Below is a fundamental flow for each part, and you can access the blueprint for each workshop here.
co-creating narratives, sharing, and collecting.
Below is a fundamental flow for each part, and you can access the blueprint for each workshop here.
Two
< (Un)P r o g r a m m i n g
Y e a r n i n g >
This was my first AI coding project, so post my call for collaboration was answered in the form of a brilliant math & coding whiz, Anushka Aggarwal, we began with what would be
weeks of back and forth developing each iteration, each time optimising to achieve our evolving purpose.
weeks of back and forth developing each iteration, each time optimising to achieve our evolving purpose.
I t e r a t i o n #1
I t e r a t i o n #2
I t e r a t i o n #3
I t e r a t i o n #4
Three
< D e s i g n i n g
t h e
E x p e r i e n c e >
Interacting with the custom yearning AI could have been a 3D visualised digital character embodying the voices of yearning but my primary enquiry was -
How might we utilise the feeling of awe as a transformative tool for cultivating critical reflection among the masses who make and use AI?
How might we utilise the feeling of awe as a transformative tool for cultivating critical reflection among the masses who make and use AI?
Yearning voiced from fibreplastic belly.
A cultural vessel housing stories.
Bottled-up emotions.
The talking well.
An artefact in time; a future artefact.
The echoing cave.
and more.
1.
What are the possible forms that the custom AI could embody?