The relationship between population growth and scarcity of resources is much disputed. Thomas Malthus, in his Essay on the Principle of Population, argued that the world’s population grows by geometric progression (1, 2, 4, 8, etc) while the supply of food grows in an arithmetic progression (1, 2, 3, 4, etc). This means that even though the supply of food is increasing, it will not do so at a pace at which it can meet the needs of the population.
His idea has drawn criticism from all sides, but the central conceit that there is a substantial discrepancy between population size and consumption is indisputable. As the population grows, access to nutrition for the poorest section of society gets increasingly difficult, and it is not likely that this will improve. According to UN projections, the global population will reach 8.5 billion by 2030 and 9.7 billion by 2050. As a society, we cannot feed the 7.3 billion people we currently have, with roughly 795 million people in the world lacking sufficient food to lead a healthy active life. The Food and Agriculture Organization of the United Nations (FAO) estimates that food production will have to grow 70% if it we are to feed this dramatic growth. At the moment, it is hard to see how this could be achieved.
One of the principle arguments against Malthusian theory - or at least his arithmetic for the scale of the gap - is that he failed to take into account technological advances for means of production. In the 19th century, leaps in agricultural technology and crop fertilization helped to cater for the population explosion that occurred. Such a boost is needed now if that 70% deficit is going to be filled.
In the first quarter of 2016, CB Insights data found there were over 140 deals with startups focused on Artificial Intelligence (AI) - the most in any quarter ever. To date in 2016, more than 200 AI-focused companies have collectively raised almost $1.5 billion in funding. The momentum around AI is building, and it appears that, although it may still be some way from reaching its full potential quite yet, it is at least on its way.
And it is going to need to if we are to produce the amount of food needed. In agriculture, many companies are already working on utilizing AI for food production. The applications are many. It can use image recognition to identify weeds, assess plant help, predict weather patterns… essentially predict any issues that impact agriculture better than humans can so solutions can be applied for farmers to optimize their resources and increase their yields.
There has already been significant investment in the sector. Switzerland-based agricultural tech firm Gamaya, for one, recently announced that it had raised $3.2 million in funding for its AI project. Gamaya has equipped drones with hyperspectral cameras that capture changes in water and fertilizer use, crop yields, and pests, which it then analyzes using AI algorithms so it can bring potential issues to farmers’ attention, as well as predicting patterns that it can use to predict outcomes farmers can use to invest in and apply appropriate resources.
This is a smaller scale example of AI being used. For governments and charities looking to provide help to producers, allocating resources correctly is imperative. Harvesting, another startup, is currently using machine learning to analyze satellite data of the Earth’s surface on a scale that humans are unable to deal with. They are looking to identify areas that require investment in the water and tools needed for farming to help institutions distribute money more efficiently. Harvesting CEO Ruchit Garg noted that, ‘Our hope is that in using this technology we would be able to segregate such farmers and villages and have banks or governments move dollars to the right set of people.’
There is significant room for agricultural productivity to improve, with traditional farming practices still shockingly outdated in many parts of the world. Waste is also a huge problem. A study by Britain’s Institution of Mechanical Engineers estimated that 550 billion liters are wasted annually in crop production. If solved, it could raise food production by 60% or more, and AI may be able to provide this. AI is still in its infancy, and there is still much to come that could provide a solution to future food shortages. The problem, as it always has been with agricultural technology, is whether it will reach the areas that need it most.