AgCast: AI is a Human Complement in Agriculture

Artificial intelligence (AI) is one of the biggest topics for discussion — and a lot of disagreement — in the technology world today. The idea of AI leading to self-awareness among machines conjures imagery of the Terminator running amok and taking over humankind. But, the reality is the machines aren’t nearly that complex today, and the data feeding those machines isn’t broad enough to enable them to act in the sort of “human-like” ways, sinister or not. Yet.


But, it’s inevitable that AI’s evolution will continue and reach much more sophisticated levels. The companies and marketers who are best suited for the arrival of AI as an agricultural mainstay will be those who are most adaptable and willing to embrace that evolution and the industry-wide change it will create.


Whether you believe in the future dominance of AI and machine learning (ML), the application of AI in machines and mechanisms that can carry out tasks without human intervention, depends on who you ask in the tech sector. There are some who feel the technology still falls well short, but others believe AI and ML are on the cusp of changing industry forever, for better or worse.


Erik Brynjolfsson falls somewhere near the middle — the Director of the MIT Initiative on the Digital Economy and MIT Sloan School professor knows AI and ML will one day have major roles in our lives, but knows there is work to be done before that happens. He’s called AI the “most important general-purpose technology of our era,” but acknowledges that may not happen the way many think it will.


“The impact of these innovations on business and the economy will be reflected not only in their direct contributions but also in their ability to enable and inspire complementary innovations,” he wrote recently in the Harvard Business Review (his article is brilliant and describes the technology way better than I could ever hope to). So, the fact of the matter, Brynjolfsson says, is AI might not be the end itself, but the means to an end that will still require human intervention to create.


Growing AI Momentum in Agriculture


Though there has been a lot of back-and-forth about how soon AI will become a part of modern crop production in the past, it’s the subject of a lot of activity lately. Just a couple of years ago, some ag company leaders were questioning AI’s ability to function effectively in environments like a corn field, for example. But today, initiatives like the Syngenta AI Challenge are actively seeking ways to apply the technology more immediately to the farm. Though it’s already there in some minor regards (think how Facebook has the magical presence of mind to recommend you “like” things you seemingly were just thinking about), AI is going to be part of farming in the future.


But, what will it look like? If Brynjolfsson is indeed right, and AI will become more of a complement to the human element, here are a few ways that it could help human beings get some key jobs done on the farm.

  • Grain marketing
  • Crop protection
  • Fleet management


What’s your risk tolerance or aversion? What crops do you raise? Where are you located? These may be the only questions you have to answer in creating your grain marketing plan. Everything else could become part of a system that applies AI to an algorithm that accounts for all other variables and ultimately leads to you being paid what you want for the grain you produce. In this way, AI would follow Brynjolfsson’s assertion that it’s a complement to the human decision-making process, not a replacement for it.


“The most effective rule for the new division of labor is rarely, if ever, ‘give all tasks to the machine,’” he says.“ Instead, if the successful completion of a process requires 10 steps, one or two of them may become automated while the rest become more valuable for humans to do.”


Heat signatures, vegetative indices and satellite map color gradients are all ways that current mapping programs can detect the presence of many common crop weed, disease and insect pests. Today, once those types of maps indicate an issue, it’s then typically confirmed by a field scout or crop consultant before being treated by the farmer, an employee or custom applicator.


Now, imagine an AI system that views satellite maps on its own, identifies the visual characteristics of a specific disease or pest and confirms its presence in the field. Then, an order is automatically placed for an application, which may be carried out by a human operator. Though the treatment itself happens by human hand, all other steps in the crop protection process happen via an AI machine.


This is an increasingly important topic in agriculture, especially in ag technology. Self-driving vehicles today already utilize AI. It’s easy to see this technology can be extrapolated to farm machinery in the not-so-distant future, especially considering big ag companies have been talking about self-driving tractors and combines for almost two decades now. Artificial Intelligence could help machines control themselves rather than today’s guidance systems that still require a human driver.


This could be of particularly high value during key times of the year, like planting and harvest. An AI system taking agronomic variables into account at these times could send self-driving machinery and equipment to the right fields at the right times to hit the optimal planting window in the spring, for example. It could help both eliminate the guesswork of how to best manage planting and harvest and automate the movement of machinery to free up labor during the busiest times of year on most crop farms.


Implications for Marketers


Exactly how AI will become integrated into agriculture remains a big question mark. But, what is clear is how it will change what constitutes success once the technology does become mainstream, especially as it continues to rapidly evolve.


“Although it is hard to predict exactly which companies will dominate in the new environment, a general principle is clear: The most nimble and adaptable companies and executives will thrive. Organizations that can rapidly sense and respond to opportunities will seize the advantage in the AI-enabled landscape,” Brynjolfsson says. “So the successful strategy is to be willing to experiment and learn quickly. If managers aren’t ramping up experiments in the area of machine learning, they aren’t doing their job. Over the next decade, AI won’t replace managers, but managers who use AI will replace those who don’t.”


When it comes to marketing, that’s going to require a nimble, responsive approach to not only the AI technology itself, but how farmers and consumers use it. Viewing it as a complement to the human capital required to successfully operate a farm instead of a wholesale replacement of that human capital will be an important part of developing an understanding of the technology, how it can be used and how ag companies can position themselves to become part of those processes through their own education and awareness of this growing sector.


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