Agriculture Big Data Legal Issues and Protections: Part 5 - Legal Concerns Regarding the Freedom of Information Act

Written by M. Sean High – Staff Attorney

Some in the agricultural community have expressed concern that depending on where the agricultural Big Data is stored, this private information could be subject to public exposure under the Freedom of Information Act (FOIA).

Under FOIA, citizens have the right to access information from the federal government.  It is important to note, however, that FOIA only applies to government information and not private information. 

A citizen’s FOIA right to information includes “‘agency records’ maintained by ‘agencies’ within the executive branch of the federal government, including government corporations, government controlled corporations, and independent regulatory agencies.” While FOIA does not provide a definition for “‘agency records,’ in United States Dep’t of Justice v. Tax Analysts, 492 U.S. 136, the Supreme Court set forth a two-part test to determine what constitutes agency records pursuant to FOIA: (1) records that are either created or maintained by an agency, and (2) under agency control at the time the FOIA request is made.”

Recently, in the case American Farm BureauFederation v. United States Environmental Protection Agency, Civil No. 13–1751 ADM/TNL (2015), District Judge Ann D. Montgomery ruled that EPA (responding to a FOIA request submitted by environmental groups) could disclose agency records regarding the names, addresses, and GPS locations of certain farms keeping animals in close confinement.  As a result, farmers are now fearful that if at some point federal law requires that a federal agency maintain records for aggregated agricultural Big Data information, this currently private information will become susceptible to FOIA.

FOIA, however, does offer specific protections that exempt the disclosure of information that is a trade secret, commercial, or financial.  While FOIA does not provide a definition of the term “trade secret,” federal courts have generally regarded information to be “commercial or financial” if that information relates to business or trade.”

Agriculture Big Data Legal Issues and Protections: Part 4 - Legal Concerns Regarding the Use of Big Agricultural Data

Written by M. Sean High – Staff Attorney

Though agricultural Big Data offers the prospect of higher yields and greater profitability, many farmers are fearful of the potential consequences that could follow after their individual information has been submitted for aggregation and analysis.

Concerns regarding data ownership

Contracts between farmers and agricultural Big Data companies “are generally a license agreement whereby the farmer retains ownership of the information, [however,] most also give the companies free rein to conduct studies and use the data tocreate highly profitable products.” As a result, once a farmer’s individual agricultural information is transmitted to the agricultural Big Data companies and aggregated, the aggregated information is most likely owned by the agricultural Big Data companies.

Today, many large seed companies, “such as…Monsanto and DuPont are now as much data-technology companies as they are makers of…seeds.” As a result, farmers have raised conflict of interest concerns due to the seed companies’ financial incentive to encourage the planting of more their product.  In response, many agricultural Big Data companies have included farmer protections in their policy documents regarding the ownership and privacy of agricultural information.  These policy statements, however, are not legally binding agreements and may be subject to future revision.

Concerns regarding Wall Street

Farmers have also indicated concern that their agricultural data could fall into the hands of Wall Street commodities traders who would then use the information to make bets on futures contracts.  The concern is that the overall effect of these bets would lower futures-contract prices early in the growing season; thereby deny farmers the opportunity to make a profit through selling futures-contracts that lock-in higher crop prices.  

Concerns regarding other farmers

Finally, farmers have expressed fear that their information could be used by other farmers competing to rent the same farmland.  The concern is that through the use of information relating to crop yields, rival farmers will see untapped potential in rented farmland.  Farmers fear that this knowledge will cause competition for the rented farmland and ultimately result in higher land rents. 

Agriculture Big Data Legal Issues and Protections: Part 3 - What are the Benefits of Agricultural Big Data?

Written by M. Sean High – Staff Attorney

To create agricultural Big Data, relevant crop information is collected from individual farms and aggregated with similar information from other farms.  The aggregated information is then combined with “highly detailed records of historic weather patterns, topography and crop performance,” to create models and simulations that attempt to predict future conditions and help farmers make decisions that will improve yields and productivity.  As a result, instead of merely blanketing fields with arbitrary amounts of seed, water, and fertilizer, farmers are able to selectively apply these inputs to specifically targeted portions of the land.

Some agricultural Big Data companies have asserted that farmers utilizing agricultural Big Data can eventually increase their average corn harvest by an additional 40 bushels per acre.  While the majority of farmers currently employing agricultural Big Data have only seen corn yields increase by 5-10 bushels per acre, agricultural Big Data companies maintain that the higher yields will eventually be realized once additional information is gathered from more farmers and pooled.

Though the interest in agricultural Big Data is a relatively recent phenomenon, much of the agricultural information currently being utilized was available to farmers in the mid-1990s.  Lack of development of this agricultural information was primarily a result of underpowered computer processors and high data storage costs.  Today, however, the average smartphone has considerably more processing power than the top-of-the-line computers in the mid-1990s, and fees associated with most types of data storage are relatively low.  

By utilizing the availability of modern computer processing and data storage, researchers are now able to aggregate and analyze agricultural information to now find previously hidden patterns and signal—“those needles in the haystack.”  Importantly, because agricultural Big Data enables researchers to create predictive models that are based on actual farming results, as greater numbers of farmers permit their agricultural information to be collected and aggregated, researchers will be able to uncover additional needles in the haystack and provide increasingly more accurate predictions.

Agriculture Big Data Legal Issues and Protections: Part 2 - What is Agricultural Big Data?

Written by M. Sean High - Staff Attorney

The term agricultural Big Data generally refers to the collection, aggregation, and analysis of incredibly large amounts of agricultural information.  This available agricultural information is so vast that it is difficult to work with and therefore cannot be processed according to traditional methods.  As a result, agricultural Big Data requires advanced computer software and innovative analysis techniques.  The ultimate goal of this collection and analysis is to provide farmers with a tool to increase production through a precise and efficient use of resources.

The first step in the agricultural Big Data process is the collection of agricultural information from individual farms. 

Recent developments in farming practices have served to provide an incredible wealth of agricultural information.  Today, it is common practice for farmers to employ Global Positioning System (GPS) satellites to guide their tractors and combines.  Farmers that utilize this technology simply sit in the equipment cabs and monitor the progress of the machinery from computer tablets.  As a result, many farmers have been freed form the tedious task of steering and are now able to plant significantly straighter rows.  

Significantly, the same machinery currently used to guide farm equipment also has the potential to collect soil and crop information.  These highly developed tractors and combines are able to display in real time, on the same computer tablets utilized for steering, detailed planting and harvesting information regarding  where every seed is placed and what the current yields are.  Importantly, this information can also be recorded and collected for later analysis and use.   

In addition to information collected from tractors and combines, information may also be gathered through the use of sensors placed in fields that measure the temperature and humidity of the soil and surrounding air.  Furthermore, crop maturity may be monitored from images acquired through the use of satellite imagery.

An area that offers significant potential for crop monitoring and information collection is through the use of drones.  Drones are flying devices that do not have an “onboard pilot, use global positioning satellites (GPS) for guidance, and establish a microwave (“wifi”) data link to a control station on the ground.” These unmanned aircrafts are able to effectively cover large areas and collect vast amounts of agricultural information through the use of mounted cameras (one of which usually has infrared detection).” Relatedly, as a result of the ever increasing use of drones, in December 2015, the Federal Aviation Administration established new regulations regarding drone registration. 

Agriculture Big Data Legal Issues and Protections: Part 1 - Background

Written by M. Sean High - Staff Attorney

In recent years, the term “Big Data” has been used with increased frequency.  In general, Big Data refers to the modern practice of collecting and using computers to process incredibly large amounts of information for a designed purpose.  A common example of this would be when online companies collect information, based on social media activities, in order to present likely consumers with targeted advertisements.

By processing the collected information, Big Data promises businesses the potential to increase profits through a more efficient use of their limited resources.  In the example of online advertisement, recording social media activities and habits allow businesses to present consumers with products they are inclined to purchase and not with those they are unlikely to buy.  By employing this approach, advertising dollars are concentrated where they are likely to have the greatest affect.  While the monitoring of social media activities may offer businesses a significant marketing tool, it also raises questions regarding control of the collected data and the personal privacy of those being observed.

Recently, Big Data has become widely associated with agricultural production.  Proponents of agricultural Big Data assert that better understanding of agricultural information (such as that related to crop production) will allow farmers, like other businesses, to more efficiently use their limited resources (such as land, water, seed, and fertilizer).  Others in the agricultural community have been reluctant to embrace agricultural Big Data because of concerns over control of the information collected and loss of personal privacy; the same apprehensions associated with the monitoring of social media activities.

While most farmers have heard of the term agricultural Big Data, large numbers of them do not fully understand how agricultural Big Data affects (or potentially affects) their own agricultural operations.  Nevertheless, farmers are now being approached by companies offering to sell their agricultural Big Data services.  Because these farmers are being asked to decide on whether or not to utilize agricultural Big Data, it is now necessary that they understanding the meaning of the term agricultural Big Data; that they comprehend the key legal issues regarding agricultural Big Data; and that they become aware of the potential legal protections available to those who decide to utilize agricultural Big Data.