Understanding Farm Data

Precision agricultural and the use of sensor technology and hi-tech systems in agriculture has resulted in large quantities of data regarding farm conditions, operations, and yields in the possession of agricultural technology providers. Agricultural technology providers or ATPs are constantly developing new software algorithms to organize and analyze farm data collected from different farmers to create meaningful information that farmers canthen apply to, and improve, their farming practices. The organization and analyses of large data sets to produce meaningful information, commonly referred to as “big data analytics,” has made it possible for farmers to adjust fertilizer and seed types and quantities for different portions of the same field to optimize yields. By combining and analyzing machine data from different farmers using its combines along with land area and usage data, John Deere has been able to forecast farmers’ demands for spare parts of the combines. Big data analytics has even been used to predict and identify sick cattle more accurately than a cattle operator’s evaluation of physical signs of sickness in cattle. Indeed, the American Farm Bureau Federation, while acknowledging the potential impact of big data analytics in agriculture, has said that big data can do for agriculture what the Green Revolution and biotechnology did for agriculture.

While big data analytics has resulted in improvements in farming, some farmers are concerned that, unless restrictions are imposed on the ATP’suse and disclosure of farm data, ATPs might share farm data, including farm research and specialist practices, of one farmer with competing farmers or with third parties, such as environmental and animal welfare lobbies, in a manner disadvantageous to farmers. The American Farm Bureau Organization has voiced concerns on behalf of farmers that ATPs might use farm data to manipulate markets, since ATPs have real-time data on much grain is being harvested from tens of thousands of fields. There is also concern that ATPs might sell farm data to third parties in connection with marketing such third parties’ own products and services without compensating farmers for the revenue generated by the ATP from the sale of their farm data. As a first step towards dealing with these concerns, a coalition of certain farm organizations, including the American Farm Bureau Organization, and certain ATPs, have agreed to a set of non-binding “Privacy and Security Principles for Farm Data” that they hope will be adopted by other ATPs.

The complete text of the Privacy and Security Principles for Farm Data is available here on the American Farm Bureau Organization’s website. It reads very much like privacy and security principles for personally identifiable information, including that the ATP must provide farmers with notice that farm data is being collected and about how the farm data will be disclosed and used, about the types of third parties to which the ATP will disclose such data, and about the choices the ATP offers the farmer for limiting its use and disclosure. Among other things, it requires that an ATP’s collection, access and use of farm data should be granted only with the affirmative and explicit consent of the farmer and that the ATP will not change the customer’s contract without his or her agreement.

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While on the face of it, adopting the Privacy and Security Principles for Farm Data seem non-controversial and good business practice for ATPs to help build customer trust, their application, without an understanding of the legal landscape and the difficulties in practical business implementation, is ill-advised. For instance, the different types of “farm data,” which may include agronomic data, machine usage data, land data, personal data, and even associated weather data, are not created equal from a legal perspective in terms of assigning legal ownership to each type of farm data, or in their designation and treatment as business confidential information or as a trade secret, or in their designation and treatment as personally identifiable information (which is subject to the higher standard of privacy reserved for such information). ATPs should consult with legal counsel familiar with technology and data related contracts, to assist them with drafting an appropriate definition for “farm data” and appropriate contract clauses that help build customer trust but also do not create contractual representations of the ATP that would exceed a customer’s rights granted by applicable law. Furthermore, ATPs adopting these principles should also consult with legal counsel about the frequency and nature of contract modifications that is necessitated by the rapidly evolving nature of technology and the workflow process of complying with a contractual obligation to obtain customers’ consent to contract modifications.

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Satya Narayan

Satya Narayan focuses her practice on intellectual property protection, licensing and commercial transactions. Ms. Narayan represents clients ranging from start-ups to established public companies and multinational companies. Her clients include software, e-commerce, cloud, digital media and content, semiconductor, solar, and medical device companies.
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