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WORK > 2024 > MVP X FFF

Minimum Viable Protein [MVP] x Food Forest Flavours [FFF] prototypes a dual-circulation food system that connects two complementary (but differently optimized) farming typologies.

MVP x FFF is a pop-up food stall and AI-assisted food computer for thinking & tinkering with the culinary (& nutritional) possibilities of Food Forest Flavours (ingredients grown and harvested from food forests (FFFs)) and Alternative Proteins (Commercially available, non-animal derived, high-protein food products (MVPs)).

We explore if and how digital tools and AI can aid in the creation of viable and desirable recipes from novel ingredient combinations. In spring 2024, we will cook recipes generated by the digital tool and serve them in public via a pop-up food cart, creating an forum to reflect on and evaluate the textual and edible results of the food computer, considering both the accuracy, applicability and process by which this knowledge was created, as well as what forms of culinary knowledge are included or excluded using LLM (large language model) tools. 

As we confront the challenges of climate change, shifting our dietary patterns towards consuming less meat and looking to alternative sources of protein seems imperative in order to align with environmental goals such as freeing up valuable land resources, reducing water consumption, and mitigating CO2 emissions. This has sparked various innovative farming approaches ranging from controlled environment agriculture alternative protein projects to agroforestry projects that heal the land and attempt to mimic the ecosystems and patterns found in nature.

The MVP x FFF Food Computer is a digital tool for harmonizing the rhythms and culinary possibilities for alternative proteins and food forest ingredients. Select a date and location, then add your criteria and preferences, the MVP x FFF Food Computer will do the rest! The computer assembles ingredient data sets, textual prompts and evaluative criteria for thinking through and tinkering with the new culinary possibilities afforded by emerging forms of food production. In addition to evaluating the resulting recipes and tastable dishes, we prompt the user to reflect on the limitations or inaccuracies in AI-generated recipes, as well as how the knowledge was produced.  

This project is developed as part of the Hungry EcoCities S+T+ARTS Residency which has received funding from the European Union’s Horizon Europe research and innovation programme under grant agreement 101069990.