Developers of a new AI agriculture tool should consider the following
- An intellectual property (IP) strategy that layers IP rights to protect different aspects of the innovation.
- Contributors to the technology should be identified and tracked.
- Ownership and confidentiality should clearly be set out in a written agreement.
- Companies should have policies for developers incorporating third-party IP, even if inadvertently, as it may impact ownership of the technology and freedom to operate.
- Employees or a contracted developer, for example, may incorporate third-party source code without authorization, which may impact ownership and could create inadvertent liability of infringement of other’s IP rights.
- Contractual terms with end users and third parties should clearly specify permitted use and ownership for collected data.
Copyright is an important IP asset for AI as it protects any new original works which can cover computer program code, application programming interfaces, compilations of data and graphics. This protects the technology product (code) from unauthorized use and reproduction. Digital locks on products and services can protect the code and data. Circumvention of digital locks is an offence in some jurisdictions.
AI systems can also generate new works protectable by copyright, such as creating new artwork or music. However, most copyright statutes do not yet clearly define who owns machine-generated works. It is currently a point of contention in respect of some such works whether the work is generated by a machine, and or the role played by the humans in creation of the work. To this end, agreements should attempt to clarify ownership when possible. Further, an AI system may act or operate autonomously in a manner that infringes third-party IP rights. If existing laws do not extend liability to a machine, then a related stakeholder (such as the owner, developer, operator or another supply chain participant) may be responsible.
A trade mark may consist of a combination of letters, words, sounds or designs that distinguishes one company’s goods or services from those of others in the marketplace. A strong brand helps companies differentiate AI products and services from competitors and establish a strong reputation in the market. Algorithmic accuracy can help a company develop goodwill for its brand. AI companies are often stewards of important data assets and documentation should consider these as valuable assets and document and register marks when possible. A reputable brand may be of paramount importance to customers.
An AI tool can be a “black box” device embedded within a finished product offered by a third party. This can make it difficult for the end customer to recognize the brand of the company supplying the “black box”. A co‑branding agreement can provide for use of the mark associated with the “black box” on the finished product offered by the third party. This can help the “black box” provider become recognizable by the end consumer.
Patents provide an exclusive right to make, use and sell his or her invention, which may help companies, obtain or maintain market share, and protect research and development investments. In contrast with trade secrets, granted patents may be enforced against third parties that make, use or sell the claimed invention, despite independent development. Patents may also be used defensively as a negotiation tool and patent publications can be cited against subsequently filed applications to prevent grant which can protect freedom to operate.
AI involves software which is increasingly difficult to patent and there is no clear delineation of what is patentable and what is not patentable. Highlighting salient technical features such as technical advantages and practical implementation details can increase the likelihood of success during patent examination. The description should highlight physical form factors and discernible effects generated by the AI innovation, such as moving a physical machine to pick up an object. Given the quickly evolving AI market, obtaining early priority dates is important in view of the“first to file” nature of the patent system.
A company making, using or selling AI tools should also consider its freedom to operate to avoid encroaching on existing IP. A landscape assessment and competitor monitoring are helpful to mitigate risk. In the AI context, the legislative protection has not yet advanced as quickly as the technology, which makes early and ongoing IP portfolio management of particular importance. A company may then better control the use of its IP rights, including permitted use under licensing and collaborative arrangements.