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How might AI enable resilient urban food systems?

Updated: Apr 10, 2024

Exploring strategic intervention points for AI in urban food systems.


Project Goal


Inform businesses and policy-makers on enabling resilience and security in food systems through strategic AI interventions.



Research Question


How might AI accelerate progress towards a circular food system?



Research Process


Literature Review

  • Explore Problem Space (Climate Change & Urban Food Systems)

  • Explore Possible Solutions (AI & Circular Economy)

  • Case Studies

3 Horizons Workshop

  • Identifies systemic barriers to food security and system resilience in the present

  • Generates Collaborative Vision for Future Food Systems

  • Generates Strategic intervention Points for AI to transition to desired future



Participants


Subject Matter Experts

  • Artificial Intelligence

  • Agri-Foods

  • Urban Agriculture

  • Biotechnology

  • Critical Infrastructure Planning

  • Circular Design

Generalists

  • Foresight & Futures Studies

  • Art & Design



3 Horizons Framework


Horizon 1: Status Quo

  • Seeks to understand what issues are plaguing current food systems

  • Drivers of food insecurity and lack of resilience

Horizon 2: Innovation Space

  • Seeks to identify opportunities to build a bridge between the desired future and current reality

  • H+ Opportunities: Disrupts status quo and actively brings about new paradigm that will govern the desired future

  • H- Opportunities: Incremental improvements to the status quo brings us closer to the desired future

Horizon 3: Desired Future

  • Generative Co-visioning of a desired future that accomplishes food security & resilient systems

  • Defines new core values that align actions, incentives, and priorities with desired outcomes





Project Insights


Threats to food security & system resilience

  • Centralization of Food Production

  • Environmental Degradation

  • Interconnected & Long Supply Chains

  • Waste

  • Premiums on sustainably & ethically sourced foods

  • Climate Change – Cascading Impacts


Patterns of behaviours driving threats


Producers

  • Industrialization of Farming

  • Profit-Driven Crop Selection

  • Minimizing Labor Costs

  • Maximizing Selling Windows

  • Expanding Revenue Streams (Seed IP, Processed Foods, Land Leasing)

Retailers

  • Rejecting Cosmetic Defects

  • Just-In-Time Deliveries

  • Expanding Supply Chain

Consumers

  • Purchasing behaviour driven by price

  • Food Waste

Government

  • Lack of transparency in food labelling

  • Policies incentivizing international supply chain

  • Policy influenced by food lobbies



Project Outcomes


Strategic AI interventions

  • Supply chain optimization to minimize food and energy waste

  • Predictive AI forecasting food demand to “right size” production

  • AI as a research accelerant in food science

  • Integrating distributed local production

  • Automating regenerative farming operations

  • Optimizing crop selection for soil health

  • Waste Reduction through resource optimization in communities



LASERRS: Innovation framework derived from co-visioned future food systems

  • Localism, Accessibility, Sustainability, & Ethics as core vales

  • Policy and project incentives to be linked to core values.

  • Measures of success define desired features of future food systems.

  • Measures of success: Regeneration, Food Secure, Resilient






FULL REPORT

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