As I sit enjoying the light but steady Spring rainfall that is transforming my backyard into what feels to me like a Garden of Eden, a world away in northern India, dozens of debt-stricken farmers have taken their lives in response to devastating crop losses wrought by unseasonal rain, hailstorms and high winds, while hospitals seek to help many more struggling with deep depression in the face of insurmountable debt.
As Vinod Kumar, an Uttar Pradesh farmer, laments in Biswajeet Banerjee’s AP article, “Normally this time of the year, we are a happy lot. Our granary is full and we clear all our dues by selling our produce. This year we lost everything. We are left with nothing. Neither food for us nor fodder for animals.”
I came across the article by chance while doing some research on The Climate Corporation. The company has always struck me as something of a poster child for empowering ordinary people to take advantage of data science to address to big challenges.
The initial challenge Climate Corporation tackled was the potentially disastrous impact of increasingly frequent extreme weather events on businesses, coming to focus over time on farmers exclusively.
They developed a platform to crunch through trillions of weather simulation data points across hundreds of terabytes of data to develop crop insurance products that would provide farmers with greater protection against losses due to extreme weather. Essentially, the policies serve as sort of ‘gap’ insurance for losses not covered by government crop insurance, with payments sent automatically when specified weather conditions occur: a marked contrast to the painfully long waits for payments tied to government inspections and damage assessments.
This is the kind of buffer of that could have made a difference in the lives of northern Indian farmers like Vinod Kumar, and Mohammad Sabir of Wazirpur village in Uttar Pradesh, who was so decimated by the sudden loss of his entire wheat crop that he hanged himself from a mango tree on his farm earlier this month.
However, one can’t help but wonder whether there are any changes to our complex systems of public and private finance that could obviate the need for farmers like Kumar and Sabir to enmesh themselves in cycles of extreme debt to bring food to our tables and theirs each season. Or whether there are any changes to modern agricultural practices that could ameliorate the cycle of debt as well. Even broader, are there any economic or agricultural practices that are actually contributing to the escalation in extreme weather events that wreak such havoc in the first place?
Such questions are beyond the scope of The Climate Corporation, as CEO David Friedberg states. As he tells msnbc.com’s John Roach, his company’s job is to “identify trends in climate data and use them to help us predict what is going to happen in the future.” On broader subjects like whether the increase in weather volatility is due to human-caused climate change (much less what role economic or agricultural systems might play in that change), he says the company doesn’t have an opinion.
Fair enough I say.
But now the company has expanded beyond insurance to deliver analytic software for farmers designed to “deliver field-level insights powered by data science.” This software crosses the line from predictive analytics to prescriptive analytics, in other words, not just telling farmers what is likely to happen, but recommending what they should do in response. For instance, the Nitrogen Advisor feature in the Climate Pro app uses predictive models that factor in nitrogen applications to date, crop stage and weather data to recommend how much nitrogen a farmer should apply, and when, to achieve target yields.
In short, the app helps farmers – at least those following modern industrial practices – do as they have always done, but with a new level of precision.
I can’t argue with Mike Stern, the Monsanto executive who was named President and COO of The Climate Corporation following Monsanto’s acquisition of The Climate Corporation, when he states in his blog post “Data Science: The Next Revolution in Sustainable Agriculture,” that the people at The Climate Corporation believe that “data and the application of data science can help farmers make more informed decisions about their operations that can increase crop yields and help them use resources more efficiently.”
I can’t argue either with the stark facts in the infographic featured in the post: more people + fixed amount of arable land = a need to do more with less, with a potentially valuable role for data science in meeting this need.
But as I looked at the graphic, I was reminded of a postage stamp-sized patch of land I saw behind a chateau on the outskirts of Paris. It was teeming with a crazy variety of fruits and vegetables all huddled together on peculiar little mounds but thriving marvelously, producing enough food for the inhabitants of the chateau and all who pass through it, without chemical fertifilzers or herbicides or genetically engineered seeds (permaculture they called it).
I think about that tiny plot, and farmers like Kumar and Subir, and I wonder whether sometimes data science might be best applied to not just helping us do what we’re already doing more efficiently, but doing things differently, even if that ‘differently’ is decidedly low-tech, or even no-tech.