Agriculture technology is a significant startup industry that is rapidly expanding. Royse Law is a partner of the annual SV Agtech conference (hosted by Royse AgTech) and is a veteran of both the startup and agtech industry. This presentation will overview current developments in Agtech law. (12/2016)

1. Roger Royse
Founder, Royse Law Firm
rroyse@rroyselaw.com
twitter: @rroyse00
Royse Law Firm, PC
www.rroyselaw.com
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Current Developments in AgTech Law
Licensing Executive Society
Tuesday, 12/13/2016

2. Royse Law AgTech
royseagtech.com

3. Recent Activity in AgTech Financings
• 307 deals with 425
unique investors
totaling $1.8 billion in
the first half of 2016
• $4.6 billion 2015 total
funding

4. • Global Farm Economy Slump
• Family farms are thriving.
• Farm Labor Shortage.
• Consumers are reconnecting
with food production.
• Local
How Has Farming Changed?

5. • A Platform of Hardware and Software Technologies
• Optimize efficiencies
• Increase production
• access new markets,
• capture useful data,
• reduce agricultural inputs Data and privacy
standards
• Highly specific and automated applications
• “push every acre to its maximum potential”
What is Precision Agriculture

6. • Farm data
• Data and privacy standards
• Use of drones
• Benefits/problems
• Legality
• Regulatory issues
• Market Issues
Overview Issues

7. • Farm Data
• Site specific data
• Seeding rates, Soil nutrients, Fertilizer, Pesticides, Water,
Yield data
• Meta Data
• Number of Acres, Inputs applied, Crops
• Big Data: aggregated farm data from numerous
operations
• ATP: Agricultural Technology Provider
Defined Terms

8. • AgTech Licenses: tech startups using standard EULA
• SaaS, Terms of Services, Browser and Click Wrap
• Issues
Is Digital Data Property, and who owns it?
• Who has rights to possess, use, enjoy, exclude, transfer, and
consume?
• What are the rights and responsibilities of the parties?
How can growers access the data?
• Export all of their imported, generated, and recommended data
from a company’s software program
Is the data accurate and presented in a useful way?
Trade secret protection (UTSA)
• Information
• Independent economic value from not being known
• Reasonable efforts to maintain secrecy
AgData: Ownership, Access, and Use

9. Farmers want to retain ownership of their data
• Can they take the data with them if they discontinue use of the service?
Do all the parties have the appropriate rights to use the data?
Farmers are concerned about who ends up with the data
• Wall Street traders could manipulate market prices
• EPA could look for potential regulatory violations
• Retailers could use the information to sell new parts when an existing part needs replacing
or to set prices
Ownership, Use, and Disclosure of Data

10. Ownership, Access, and Control of Data are major issues
• 2013 EPA CAFO Data Incident
– Earth Justice, the Natural Resources Defense Council and the Pew Charitable Trust made a FOIA
request
– They were given information on roughly 80,000 farmers and ranchers including personal data that
the EPA did initial protect, but later redacted after it was made publicly available
• Smart Farming May Increase Cyber Targeting Against US Food and Agriculture Sector, Joint Private
Industry Notification of USDA and FBI Cyber Division, March 31, 2016
Issues in AgTech Data

11. • What is aggregated or “blind” data?
– Data combined from two or more sources
– Typically stated as “anonymized”
•But is it truly anonymized?
– Is all personal data removed?
– Are there sufficiently numerous sources to ensure anonymization, especially for a
small startup?
– Can the aggregated data be reverse engineered in order to find out where the
data originated?
•Again, aggregated data is required for the software companies,but precautions
should be taken to ensure it’s truly anonymized.
Blind Data

12. • Farmers are becoming increasingly aware of the need to protect their data and
enforce their ownership rights through stakeholders
– Government
– Input Providers
– Trade Groups
– Startups
• Stakeholders are trying to implement a common set of data and privacy
standards to guide Agriculture Technology Farmers (ATPs), farmers, and other
contracting parties on what are appropriate contract terms
AgTech Data and Privacy Objectives

13. •Open Ag Data Alliance (OADA)
– Open data sharing standards (API’s) and open source software libraries, March 2014
•American Farm Bureau Federation (AFBF) Privacy and Security Principles of Farm Data
– Affirmed by 39 Ag entities as of April 1, 2016
– Originally known as the 2014 Farm Data Principles Agriculture Data Coalition
•Agriculture Data Coalition (ADC)
– Partnership of agriculture stakeholders focused on building a “farmer-centric data repository
where farmers can securely store and control the information collected every day in the fields by their
tractors, harvesters, aerial imaging and other devices.” (March 2016)
•Farmobile, Inc. -- Ag Data Collection Startup
– Farm Data MarketPlace where Farmobile collects offers from companies that want to use the
farmer’s data, whole transaction is governed by Farmobile’s legal agreements
•“Guiding Principles” Independently Developed by Ag Companies
– Ex. Climate Corp, Farmer’s Business Network, John Deere
Current AgTech Data Standards

14. AFBF Principles include the following key provisions that should be incorporated
into contracts:
•Easy to understand language
•Farmers should own information generated through their farming activities and any use of
that data by the ATP is only with the explicit and affirmative consent of the farmer
•ATPs shall notify farmers how their data is to be used, with whom it will be shared, and for
what purpose
•Farmers should be able to retrieve their data for use with other systems
•ATPs shall not sell or disclose a farmer’s data to other parties without notifying the farmer
and without that other party agreeing to the same terms as the farmer
•ATPs shall use reasonable security safeguards to protect against risk of loss or theft of data
AFBF Privacy and Security Principles

15. The standards provide strong protections for farmers, but may not be
workable
•Many farmers are not able to negotiate terms and may feel like they are in a “take it or
leave it” position.
•The business model of some ATPs is the collection and presentation of data and a
subscription model is common
– The ATP will not want to let farmers take this data with them once they are no longer paying
for the service.
•The contract terms are necessarily complicated because of the multiple agreements in
place
– Not easy to reduce the terms down into something easily digestible.
Workable Standards?

16. Current Industry “M.O.”: Agriculture is a handshake industry
•Agriculture is driven by personal interactions, not formal agreements.
•Farmers tend to prefer to “kick the tires” for on-farm products.
•Pre-revenue transactions, like field trials (including university trials) are done without agreements.
Issue: Without a contract, different laws are implicated that these parties never
anticipated.
•Intellectual Property: Trade secret disclosure, ownership of IP (patents, data, “results and
recommendations”).
•Contract Law: Implied contract principles.
•Torts: “Negligence” damages for startups who are providing services.
Solution: Education and information on importance of formal agreement.
Problem: Lack of Formal Agreement

17. Scenario #1: VineLabs, Inc. and GrapeGrower, Co.
Facts:
– VineLabs created a software program (“Program”) that: (1) gathers data during the growing
season; (2) overlays the collected data with other third party data; (3) generates a yield prediction
from the aggregated data.
– GrapeGrower wants to test the Program, but does not want its data to be used for “precision
agriculture” that could benefit its competitors.
Party Objectives:
– VineLabs: gather, aggregate, and use GrapeGrower’s data and generated data to improve
software program.
– GrapeGrower: all ownership and control rights to its data, including data generated by the
Program → freeze out competition or push low acquisition price of VineLabs.
Negotiating Data Clauses

18. Resolution Objectives:
In General:
– Ensure VineLabs has the necessary licenses and permissions to use and aggregate the data.
– Draft clear and conspicuous protocols regarding the use of GrapeGrower’s data and how it will be
used.
– Prevent overbroad definition of GrapeGrower’s data.
Specific:
– Clearly define and describe rights to data:
• Data Defined: “Any and all data, information, or materials provided by GrapeGrower or
collected through the Program in connection with GrapeGrower’s use thereof or any services provided
by VineLabs.”
• VineLabs Data Rights: Blind data and any and all recommendations and/or improvements
to the underlying algorithms resulting from data collected or “Feedback” provided by GrapeGrower
– Include a broad license for VineLabs to use blind or anonymized data in (1) any manner (preferable)
or (2) solely in order to improve the Program and related services (less preferable) or (3) solely as necessary
to provide services to GrapeGrower (least preferable).
– Include a broad license for VineLabs to use and incorporate Feedback
Negotiating Data Clauses

19. Scenario #2: FreshFruit, LLC and MegaDistribution, Inc. (MegaD)
Facts:
– FreshFruit created a software program (“Program”) that: (1) gathers image data taken of
produce and provides “fresh-vision”; (2) overlays the collected data with data regarding source of
produce (i.e. grower, distributor, # of days/weeks since harvested); (3) generates data base of
relationships of source v. freshness parameters.
– MegaD wants to test the Program, but is protective of proprietary data, namely, produce
grower and delivery information.
Party Objectives:
– FreshFruit: Gather, aggregate, and use MegaD’s data and generated data to improve software
program.
– MegaD: All ownership and control rights to its data, including data generated by the Program.
Negotiating Data Clauses

20. Resolution Objectives:
In General:
– Ensure FreshFruit has the necessary licenses and permissions to use and aggregate the data.
– Draft clear and conspicuous protocols regarding the use of MegaD’s data and how it will be
used.
– Prevent overbroad definition of data → exclusions for Blind Data.
Specific:
– Clearly define data:
• “all data, information, or materials provided by MegaD or collected through the
Program in connection with MegaD’s use of the Program and any services provided by FreshFruit
in connection therewith.”
– Exclude Blind Data from definition of Confidential Information.
– Include a broad license for FreshFruit to use Blind Data in (1) any manner (preferable) or (2)
solely in order to improve the Program and related services (less preferable).
– Include reasonable confidentiality obligations for FreshFruit.
Negotiating Data Clauses

21. Scenario #3: AerialAg, Inc. and HiddenFarms, Co.
Facts:
– AerialAg collects farm data through sensors and drones then provides recommendations and
results through its online software platform (collectively, the “Services”).
– HiddenFarms wants AerialAg to provide the Services, but is hesitant of the use and
inadvertent disclosure of proprietary farm data.
Party Objectives:
– AerialAg: Gather, aggregate, and use HiddenFarms’ data and generated data to improve its
Services, in particular, to improve recommendation algorithms.
– Hiddenfarms: Protect against disclosure or use of HiddenFarms’ Confidential Information
(which may include, geolocation information, soil composites, and growth/harvesting processes).
Negotiating Data Clauses

22. Resolution Objectives:
In General:
– Ensure AerialAg has the necessary licenses and permissions to use and aggregate the data.
– Draft clear and conspicuous protocols regarding the use of HiddenFarms’ data and how it will
be used.
Specific:
– Clearly define Confidential Information (negotiate to exclude “geolocation” and other
necessary data to enable Services to optimize precision agriculture practices.
– Exclude Blind Data from definition of Confidential Information.
– Include a broad and perpetual license for AerialAg to use Blind Data in (1) any manner
(preferable) or (2) solely in order to improve the Services (less preferable).
Negotiating Data Clauses

23. • General right to maintain software
• Digital Millennium Copyright Act (DMCA) of 1998
• Criminalizes acts of circumventing “digital locks”.
• DRM rules were originally designed to prevent someone
from copying a video game or jailbreaking a game console
to play unlicensed games.
• JOHN DEERE: “ownership of equipment does not
include the right to copy, modify or distribute
software that is embedded in that equipment.”
• Exemption of Automotive Software
• Available on October 28, 2016.
• When circumvention is "a necessary step . . . to allow the
diagnosis, repair or lawful modification of a vehicle
function”.
• Only available to "authorized owner" of the vehicle.
• Expire on October 28, 2018.
DMCA and Copyright Exemptions

24. • The global market for agricultural drones, currently
estimated at $494 million is anticipated to reach $3.69
billion by 2022.
Agriculture Drones

25. • Use of drones for agriculture
• Monitor land for weeds and weather damage
• Collect data on land
• Concerns/problems with the use of drones
• Privacy issues: Not a huge concern with farmland,
• Safety issues: Collisions and Crashes
• Use problems
• Cost of entry: hardware is cheap, software is not.
• Battery life
• Connectivity
• Presentation of data
Agriculture Drones

26. Agriculture Drones
• Drones could revolutionize farming through:
• Mass data collection
• Surveying land and planting seeds
• Surgical precision in the use of pesticides, fertilizer, and
water
• Brazil and Japan already use drones in agriculture. In
US, FAA issued new rules to regulate commercial use
of drones in 2016
• Safety and privacy concerns that affect urban areas
may not apply to farms
• However, farmers are concerned that drones will be used
by environmental groups to spy on and monitor their
operations

27. FAA Rules for Commercial Drones (Part 107)
Daylight-only operations; or Civil twilight with
appropriate anti-collision light (30 mins before
sunrise to 30 mins after sunset).
Visual line-of-sight only
• Max Weight: 55 lbs
• Max Speed: 100 mph
• Max Altitude: 400 ft.
Operator requirements:
• At least 16 years old
• Demonstrate aeronautical
knowledge
• Obtain operating certificate
• Vetted by TSA

28. • GEC is the new unregulated GMO
Gene Edited Crops
Bacteria Use
Use in
Higher
Organisms
 Who Invented CRISPR? Any Overlap?
 Final resolution may not come until 2018 or 2019.
UC Berkeley vs. Broad Institute of MIT and Harvard
Filed First Approved First
• No more foreign DNA or transgenic gene delivery
• Cut DNA at targeted location in the genome and insert desired genes in that
place
• Cheaper and quicker than GMO technology
• CRISPR Cas-9 technique: Enables geneticists to edit parts of the genome by
removing, adding or altering sections of the DNA sequence

29. • Legality: There is none!!!
• Zero regulatory oversight for GECS.
• Coordinated Framework for Regulation of Biotechnology only
regulates GMO technology.
• April 2016: USDA confirmed twice it cannot regulate GECs
but the GM regulatory framework was written to only handle
GM modified products.
• The EU is also still considering whether to class gene-edited
plants as genetically modified.
• Hope that new regulations will be science-based and more
flexible to evolve with new technologies rather than piece
meal technology based legislation.
Gene Edited Crops

30. • May be anti-trust issues with ATPs that collect and share data
on prices of products or inputs
Section 1 of the Sherman Act
• Collusion: “unreasonably restrain competition”.
• agreement to fix price; agreement to allocate markets; agreements to
boycott particular customers, suppliers or competitors, etc.
• Knowledge of prices could reduce competition in the market and
stabilize prices which is often seen as bad for consumers
Section 2 of the Sherman Act
• Monopolization or Attempt to Monopolize
• Although it is not easy to find Monopolization
Clayton Act
• Anticompetitive Mergers
• Bayer-Monsanto Merger: Shareholders of Monsanto approved on 12/12/16
• ChemChina-Syngenta Merger
• Dow Chemical-DuPont Merger
Anti-Trust

31. • Contracts
• ATPs must balance complex contracts with the need to
provide farmers with straightforward information
• Lots of inherent complexity, especially when the ATP sells
combined hardware and software
• For example, there could be software on the hardware, separate
software sold to the farmer for use on a personal computer, and
a SAAS subscription all as part of one service
• All the software will have different terms of use
• Farmers often work with dealers
• Dealers sometimes collect and input the data
• Who has the relationship with the dealer? The farmer or the
ATP?
• Need to ensure all the parties have the correct licenses
• ATPs should consider using FAQs on their website to
answer questions from farmers
• Need to ensure answers to FAQs are consistent with privacy
policies, end user agreements, etc.
IP Issues

32. • Monetization
• Sale of software and add-ons
• Patents
• Hardware and software
• Big Data
• Reports
• Aggregated data
• Must have rights to use the data in this way
• Subscription services
IP Issues

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