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Ecological Intelligence
In Collaboration with:
Morning Glory Farm,
West Bethel, Maine
Coach:
Ayush Gandhi
Location
Studio Overview
Climate change is reshaping ecosystems, food systems, and the ways communities relate to land. At the same time, artificial intelligence is becoming a powerful tool that can help us observe, analyze, and respond to environmental challenges. But AI is never neutral — every dataset, every model, and every decision reflects values. This studio explores how we can design AI tools that are technically functional, ecologically grounded, and ethically responsible.
Ecologically Grounded
Ethically Responsible
AI Tool
Technically Functional
Studio Client: Morning Glory Farm, West Bethel, Maine
In partnership with Morning Glory Farm, an independent CSA organic farm in West Bethel, Maine, students will investigate real ecological challenges faced by small farms: soil health, pest detection, water management, crop monitoring, biodiversity, and energy use. They will design AI-assisted tools that support sustainable and regenerative farm practices while honoring ecological wisdom and systems-thinking.
Studio Overview Continued
Students will collect their own datasets (images, sensor readings, audio clips) or use open environmental datasets, build simple machine learning models using beginner-friendly tools (Teachable Machine, Google Colab, Micro:bit/Arduino sensors), and prototype ecological monitoring or decision-support systems that could be used on our client farm.
Collect Data
Train a Machine Learning Model
Prototype Ecological Monitoring/ Decision Support Systems
Studio Overview Continued
Throughout the studio, we explore ecological intelligence — the ability to recognize interdependence, act with ecological humility, and design technologies aligned with the wellbeing of land, people, and nonhuman communities.The final outcome is a working prototype with an ecological systems-impact map and an ethical/philosophical reflection. In alignment with NuVu’s design process, students will iterate on ideas, test models, analyze failures, and critically reflect on the consequences (intended and unintended) of using AI in real ecological contexts.
Ethically...
Working Prototype
Systems Map
Ethical/Philosophical Reflection
Monday
Tuesday
Wednesday
Thursday
Friday
8.30-10
10.15-11.30
12.30-1.30
Studio Introduction
G4G
Dec 1
Dec 2
Dec 3
Dec 4
Dec 5
L U N C H
Client Meet
Teachable Machine
Ecosophy + Client Introduction
Systems Map
Data Analysis
Find your Partner
Farm Data Sources
Project Brainstorming
Client Interview Questionnaire
Desk Critics
Research
Monday
Tuesday
Wednesday
Thursday
Friday
8.30-10
10.15-11.30
12.30-1.30
Mid Review Presentations
G4G
Dec 8
Dec 9
Dec 10
Dec 11
Dec 12
L U N C H
Project Proposals
Monday
Tuesday
Wednesday
Thursday
Friday
8.30-10
10.15-11.30
12.30-1.30
Studio Introduction
G4G
Dec 15
Dec 16
Dec 17
Dec 18
Dec 19
L U N C H
Monday
Tuesday
Wednesday
Thursday
Friday
8.30-10
10.15-11.30
12.30-1.30
Final Presenttations
Jan 5
Jan 6
Jan 7
Jan 8
Jan 9
L U N C H
Community Agreement
Do's:
From students:
- During Community Circle time, everyone in class should be part of the circle (in center of the room)
- Laptops to be used only on desks kept towards the walls
From coach:
- Give clear instructions, and support students whenever necessary
- Bring snacks to class sometime.
Ethically...
Dont's:
From students:
- Using phones during class time
- Disturbing others
- Invading someone else's personal space
From coach: