FieldScripts: a tale of prescriptive planting, digital disruption and sub-optimal trust

You can beg all you like: it's all but impossible
to repair a sub-optimal level of trust ...

All too often, we in the IP world forget about the centrality of trust in the successful exploitation of even world-class innovation. However cutting-edge the technology, and no matter how effective is the larger ecosystem at successfully commercializing these developments, a sub-optimal level of trust between the parties can lead to the result where the opportunities for win-win are significantly lessened. This is particularly so when trade secrets and confidential information are involved. An instructive example with an interesting potential twist was recounted several months ago by The Economist in connection with so-called “prescriptive planting” (“Digital disruption on the farm: Managers in the most traditional of industries distrust a promising new technology”, here).

First: the technology. In 2006, a Silicon Valley start-up, the Climate Corporation, here, was set up by two ex-Google employees. The company in effect mapped all 25 million agricultural fields in the U.S. and superimposed on that mapping data climate information. As a result, by 2010 the company database contained 150 billion soil observations and 10 trillion (!) weather-simulation points. The original purpose of gathering this data was to offer better crop insurance. But in October 2013, Monsanto paid over one billion dollars for what is, effectively, a niche (though a huge one) purveyor of big data. Monsanto added to these data its own so-called library of hundreds of thousands of seeds and terabytes of data on the yields of these seeds. By combining all of this information, Monsanto developed a map which sets out which seeds do best in what field and under circumstances.

What ensued is Monsanto’s “prescriptive planting” system, called FieldScripts, here, which takes these data and in effect operates a planting device (itself the product of another company—Precision Planting, here—also purchased by Monsanto). Using this system, the Monsanto “can plant a field with different varieties at different depths and spacing, varying all in accordance with the weather.” First indications point to increased yields of approximately 5%, a significant improvement. It is no surprise, therefore, that other companies are seeking to get into the prescriptive planting game. So far so good—innovation based on integrating several advances in gathering and exploiting big data promises to dramatically improve the yields of US farmers.

So what is the problem? In a word—“farmers distrust the companies peddling this new method.” The overarching concern is that the information received by the companies from the farmers about their harvests, which the farmers view as proprietary information, may be misused by the companies. Potential sources of distrust are several:

(1) this confidential information might be sold;
(2) even if not sold, such confidential information could still “leak” to third party farmers;
(3) the companies might make use of this harvest information to identify underperforming farms and seek to operate them in a more efficient manner, in competition with the farmers;
(4) the companies might make use of this information to trade on commodities markets in ways that are not aligned with the interests of the farmers; and
(5) the information may not be portable (shades of data portability for information stored in the cloud), should the farmer wish to move to another company offering prescriptive farming services.

Several attempts have made to lessen these potential sources of distrust. First, the American Farm Bureau is preparing a code of conduct that provides generally that the farmers “own” (whatever that means in this context) their data; no use can be made of such data except for the specific purpose for which it was given by the farmer to the company; or these data cannot sold or otherwise transferred to third parties. It appears that sometimes these provisions are embodied in the agreement between the farmer and the companies while other times they are not included in the contract between the parties. Moreover, the efficacy of these principles might be limited, especially after these data have been “anonymized” by the company after receipt from the farmer. Stated otherwise, the extent to which any such agreement can serve as a contractual replacement for the lack of trust between the parties may well be limited. As so often happens when confidential information is concerned, it would seem, there is no silver bullet to make up for a lack of trust.

That said, one wonders whether the situation is a bit more nuanced than that. The article concludes by saying that

“[i]f users think they are taking a disproportionate share of the risks while firms are getting an excessive chunk of the benefits, trust will remain in short supply.” 

This observation suggests that what is really at issue is not the absence of trust per se, but the feeling by the farmer that he is being short-changed in the relationship. Couched in this manner, this Kat wonders whether there is some way that the companies can make their relationship with the farmers with respect to prescriptive farming more commercially attractive (especially given the difficulties and limitations in enforcing contractual restrictions regarding confidential information and the apparent inability to rely on the goodwill of the company to honour the code of conduct, even in the absence of an agreement). Stated otherwise, perhaps there is a better way to quantify and thereby bargain this lack of trust between the farmer and the company. Or has this Kat been struck down by a serious case of naiveté in a field where the relationship between the companies and farmers has long been a charged one?