Background

A new research vector has emerged in the last couple of months.  “New” in the sense that the topic was not mentioned in our 2022 year-end reviews in December or in the  OODA Almanac 2022.

The new research is the “praxis”  (or intersection) of agriculture and cyber risk based on the following nascent driving force and critical uncertainty:  Ukraine is a crucial breadbasket in the global food system. The war is impacting the entire agriculture supply chain and value chain in Ukraine and Russia.  Ukraine not only provides wheat and other grains to Europe but to parts of Asia and Africa.  Broad global food shortages are forecast – and may have a duration of years (not days, weeks, or months):

“By invading Ukraine, Vladimir Putin will destroy the lives of people far from the battlefield—and on a scale, even he may regret. The war is battering a global food system weakened by Covid-19, climate change, and an energy shock. Ukraine’s exports of grain and oilseeds have mostly stopped and Russia’s are threatened. Together, the two countries supply 12% of traded calories. Wheat prices, up 53% since the start of the year, jumped a further 6% on May 16th, after India said it would suspend exports because of an alarming heatwave.

The widely accepted idea of a cost-of-living crisis does not begin to capture the gravity of what may lie ahead. António Guterres, the UN secretary-general, warned on May 18th that the coming months threaten “the spectre of a global food shortage” that could last for years. The high cost of staple foods has already raised the number of people who cannot be sure of getting enough to eat by 440m, to 1.6bn. Nearly 250m are on the brink of famine. If, as is likely, the war drags on and supplies from Russia and Ukraine are limited, hundreds of millions more people could fall into poverty. Political unrest will spread, children will be stunted and people will starve.

“Mr. Putin must not use food as a weapon. Shortages are not the inevitable outcome of the war. World leaders should see hunger as a global problem urgently requiring a global solution.”  (1)

It is unlikely Putin will not use the advantages gained by the crippled global food system.  The brutality of the war speaks to the fact that Putin and the Russians are now devoid of any moral or ethical compass to apply to the failure of the food system.  There is also the fact that the Russians have a full strategic plan in the Artic as landmasses reveal themselves due to the melting of glaciers.

The BBC captures the scale of the issue relative to a recent ransomware incident in the meat industry:  “Even the largest companies aren’t safe from cyber gangs. Some use ransomware: malicious code that can encrypt data and lock systems.  Last year, one of the world’s biggest meat processing company, JBS, paid $11m in ransom to resolve a cyber attack. This month, top US agriculture firm, AGCO, was hit by a ransomware attack that affected production.”

For Putin, all uncertainties, crises, and opportunities are fair game.  Pragmatism and realism are crucial in international relations and geopolitics.  Realpolitik, Machiavelli,  Hobbes, Weber, Sun Tzu – yes, a cynical view of human nature is the central tenet here, but the founding documents of the United States are also informed by Enlightenment-based conclusions about the frailty of man – which the founders structured into the document. A three-branch system emerged as the safeguard.

Global Agriculture and Cyber Risk

“In April, a group of official governmental cyber security authorities including ones from the UK, US, and Australia, warned that Russian state-sponsored hackers could target supply chains as a vital part of Western national infrastructure.  A recent University of Cambridge report said automatic crop sprayers, drones, and robotic harvesters could be hacked.   Smart technology is increasingly being used to make farms more efficient and productive – for example, until now the labour-intensive harvesting of delicate food crops such as asparagus has been beyond the reach of machines.

The brutal irony is that agriculture has been using technology to innovate – but like the proliferation of smartphones and the Internet of Things, innovation has also increased the size of the attack surface.  Further reporting from Claire Marshall & Malcolm Prior at the BBC is illustrative:  “Benjamin Turner, chief operating officer at Agrimetrics, one of four UK government-backed agri-tech centres of agricultural innovation, said: “Hacking into one tractor, you can upset a farmer and maybe damage their profitability for a season.  Hacking into a fleet of tractors, suddenly, you’ve got the power to affect the yield in whole areas of the country.”

“Precision Agriculture”:  The John Doe Tractor Kill Switch Incident In Ukraine

This story was reported by many news outlets.  Author and Futurist Cory Doctorow picked up the story snf offers some analysis and an opinion piece.  More from Cory soon.

First, a summary of the incident:   according to CNN, Russian troops in occupied Melitopol stole $5M worth of equipment from a farm equipment dealership – and shipped it to Chechnya.  Unfortunate for the Russian Army, by the time the equipment arrived in Chechnya, a kill switch had been used to render the equipment useless. (3)  CNN also reported that “over the past few weeks there’s been a growing number of reports of Russian troops stealing farm equipment, grain, and even building materials – beyond widespread looting of residences. But the removal of valuable agricultural equipment from a John Deere dealership in Melitopol speaks to an increasingly organized operation, one that even uses Russian military transport as part of the heist.

CNN has learned that the equipment was removed from an Agrotek dealership in Melitopol, which has been occupied by Russian forces since early March. Altogether it’s valued at nearly $5 million. The combine harvesters alone are worth $300,000 each.”

On May 8th, Doctorow in his About those kill-switched Ukrainian tractors | by Cory Doctorow on Medium – offers the following perspective:

“Why are John Deere tractors kill-switched in the first place?

Here’s a hint: the technology was not invented to thwart Russian looters.

No, it was invented to thwart American farmers.

For most of John Deere’s history, it partnered with farmers on its technological development. I mean that literally: John Deere used to send engineers on the road to visit farms and learn how farmers had adapted their equipment, and then it would integrate those improvements into new models of its tractors.

Farmers have been making, fixing, and adapting their technology for millennia (literally)— farms have workshops and forges because when you’re at the end of a lonely country road and the storm is coming and you need to bring the crops in, you can’t go into town (or call the Deere dealership) to get a key piece of equipment repaired.

But as John Deere went from just one of many ag-tech companies to a monopolist, its relationship with farmers was transformed. Deere perceived many opportunities to extract new sources of revenue from farmers.  For example, they fitted out their tractors with clusters of new sensors: torque sensors on the wheels that measured soil density, humidity sensors on the undercarriages that measured soil moisture, and location sensors on the roof that plotted density and moisture on a centimeter-accurate grid.  This information is very useful! Farmers can use it to practice “precision agriculture,” broadcasting their seed according to these maps to maximize yield.

But Deere farmers couldn’t get that data — at least, not on its own. Deere originally bundled that data with an app that came with seed from Monsanto (now Bayer), its preferred seed vendor. The farmers generated the data by plowing their fields with their tractors, but Deere took the position that the farmers weren’t the owners of that data —Deere was.

Tech monopolists love kill-switches, and they exhibit heart-warming confidence in their own ability to prevent their abuse.

That confidence is terribly misplaced. These can and will go wrong, with terrible consequences. It’s important not to get swept up in the industry’s self-serving cheerleading about these kill-switches working in ways we like, because of all the ways they can go wrong.”

Overall Climate for Innovation

In our recent Opportunities for Advantage: A Real-Time, Precise, Accurate, Interoperable OS for Autonomous Systems,   we noted that the burden of “fatal accidents as a feedback loop” cannot be distributed out to the consumer during an iterative production cycle.   Small scale success (short and long-haul trucking, for example) will have to be scaled up once the fatal risk is close to 100% mitigated.  Or will the market sustain a 95% to 99% accuracy rate, with the unintended consequences and the inevitable autonomous systems accidents that most assuredly entail?”

Like the trucking fleet, farming and tractors are also a really promising fleet for phase one development of autonomous capabilities.

John Deere is announcing the acquisition of a state-of-the-art algorithm package from artificial intelligence startup Light.  No, you won’t be seeing green tractors rolling themselves down city streets anytime soon. But the timeline for fully autonomous farming is being massively accelerated. Today’s purchase is all about John Deere’s need for speed — and accuracy, but first let’s talk about rapid development.  In essence, Light’s algorithms will allow Deere’s equipment to use industry-standard cameras (read: regular old off-the-shelf vision systems) to achieve virtually unparalleled depth perception.  This is similar to the approach that Tesla takes for its ‘Full Self-Driving’ (FSD) system.

Light, the company Deere’s partnering with for the asset purchase, is a major player in the autonomous vehicle field. It uses a computer-vision approach to self-driving that allows the AI system controlling a vehicle to ‘see’ the world similarly to the way biological systems do.  We’ve criticized vision-only approaches in the past here at Neural, but this is different. Passenger vehicles have to travel on busy thoroughfares where the slightest mistake can result in the loss of human life.  On a farm, the stakes are much different. Tractors and other agricultural equipment need to be able to identify crops and obstructions in order to ultimately achieve the goal of optimizing food output.

The current industry-standard solution for autonomy (usually) involves using a combination of LiDAR and computer vision. This allows developers to achieve the resolution and depth necessary to, for example, teach an AI system to ‘see’ a pedestrian walking across the street in a snowstorm.  But that’s not necessarily the best way to go about things in the agricultural space. Deere’s vehicles, for example, often need to be able to see individual weeds in real-time as the vehicle is moving across bumpy terrain.” (4)

What Next?

The Ukrainian Kill Switch Incident Is Just the Beginning:  Agriculture and Cyber Risk are now high on the list of critical infrastructures which will continue to experience large-scale cyber attacks.

A Large Attack Surface – and Value Created by Innovation:  As new systems come online, new vulnerabilities are created.  The attack surface expands.  All the while, certain innovations will fuel new business models, create new value proposition designs, generate revenue, and eliminate and create jobs.

Agricultural Fleets Show Great Promise as the First Operational Autonomous Vehicle Fleet:  There are inherent risks is an aggressive, accelerated transition to autonomous vehicles in agriculture.  The problem is that new vulnerabilities and cyber-attack incidents will be a constant risk. It is to be seen if these incidents are bespoke and unique to the early development of the autonomous market – or if a high percentage of incidents will inform broad safety and systemic innovation which accelerate the autonomous future.

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