Food for Thought: Can Deep AI-D Prevent the Next World Hunger?

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In 1798 Malthus published his famous essay “On the Principle of Population” including his grim observation that “the power of population is so superior to the power of the earth to produce subsistence for man, that premature death must in some shape or other visit the human race”. Malthus articulated the discrepancy between the potential of populations for rapid growth and the slower growth rates of food production needed to support the population. This discrepancy can lead to a ‘Malthusian Catastrophe’ in the form of famine, epidemics and wars over food supply. Malthus, which was pessimistic regarding increasing food supply, advocated for policy measures to restrict the growth of the population to avoid a catastrophe.      


Figure 1: Waves of innovation propel free economies, the Kondratiev-Schumpeter model.

Jumping forward to 1925, Russian economist Kondratiev proposed that free markets develop in nonlinear waves (aka k-waves, long cycles or super cycles) of technological innovation and market adoptions (Figure 1). This notion was further developed and popularized later by Joseph Schumpeter. Adopting the Kondratiev-Schumpeter theory to the agri-food sector, waves of technological innovations enabled a dramatic boost of food production by replacing wood tools with iron tools (1st wave), replacing iron tools with steel tools (2nd wave), replacing human and animal labour with machines (2nd and 3rd wave), introducing synthetic fertilizers and pesticides (3rd and 4th waves), and introducing genetically modified crop variants (5th wave).  In the 200 years since Malthus made his grim predictions at the dawn of the industrial revolution, agricultural production has increased dramatically due to these waves of innovation that supported the growth of human populations to current levels and a Malthusian catastrophe was so far avoided. 

A recent illustration of the matching trends in global food production and population growth can be seen in Figure 2:


Figure 2: Global food production and population growth (2000-2018)

Alarmingly, there are now growing concerns that a Malthusian food crisis may be inevitable somewhere between 2030 and 2050, when population size is predicted to surpass global food production capacity. Particularly concerning are global warming forecasts of two to four degrees warmer global climate. Global warming is likely to increase weather instability, including droughts, severe storms, and floods which will reduce the food production capacity of the earth and may lead to a food crisis.     

The Kondratiev-Schumpeter framework of innovation waves can inspire a solution for the next world hunger by market adoption of technological innovations. In the current wave of innovation (the 6th wave), artificial intelligence and deep learning enable machines to interact with the natural world in an unprecedented way.  AI can boost productivity in the agri-food sector similarly to the predicted effects of AI in the transportation, telecommunications, advertisement, finance, and healthcare sectors.

Farming in North-America is transitioning from a low-tech and labour-intensive occupation into a high-tech, mechanized, and data-intensive profession. The increasing availability of GPS technology, digital harvest monitors, computer vision and remote sensing technology generates reams of granular  agriculture data. This digital transformation in agriculture provides robust foundations for a wave of AI solutions and companies that aim to generate insightful actionable predictions in: optimizing fertilization (FarmersEdge, Canada), optimizing seed selection (FarmerBusinessNetwork, USA), and pest detection (Taranis, Israel) to name a few prominent examples.               

Dr. Tzvi Aviv is the founder and CEO of AgriLogicAI Inc., an agri-fin-tech venture supported by Next Canada and the Creative-Destruction Lab, developing geospatial intelligence platform aiming to enhance farm productivity, profitability, and sustainability. We apply deep learning and machine learning to satellite images and other data to automatically appraise farms, predict crop yields, and evaluate food production risks. Dr. Aviv designed machine learning solution for optimizing seed selection in farms that won first place in an AI challenge run by the AI for Good Foundation and Syngenta, a global seed producer (presented in the 2017 Knowledge Discovery and Data Mining conference in Halifax NS).

    

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