Legal Strategies to Protect Advances in Artificial Intelligence.
The Kansas City Augmented Intelligence Laboratory is a synergistic collaboration of individuals with extensive experience and advanced training in machine learning (ML) and artificial intelligence (AI) that have formed a cooperative entity to provide training to those with the drive and determination to develop their understanding of this rapidly advancing technology. This dynamic team of experts has pooled their intellectual prowess to develop a no-cost program to train this region’s future experts in ML and AI.
This pool of talent will unquestionably be drawn upon by employers at an accelerating rate in the coming years. This collaborative effort is intended as one measure to keep Kansas City and potentially the entire Midwest relevant when it comes to advancing the practical application of these technologies — technologies critical to our national security and also to the development of our broader economy. Government is not focused on this challenge of training and retraining of workers in this advancing technology, and business is not doing enough to meet it. Moreover, an education system built around a four-year degree may not be a good fit for a world requiring continuous retraining in new skills. The primary goal of the Kansas City Augmented Intelligence Laboratory is to lend support to the proposition that the United States must remain the global leader in further development of this cutting edge technology.
Artificial Intelligence (AI) has already produced many things in use today, including web search, object recognition in photos or videos, prediction models, self-driving cars, and automated robotics. The legal implications for AI are complex and constantly evolving, and they often seen as less of a concern than the pressing business demands of bringing innovative technologies to market. It is important for businesses today to implement a proactive and comprehensive strategy to protect their intellectual property (IP) rights in AI. Such strategy should consider not only patent coverage but also copyright and trade secret protection, particularly for aspects of the IP that may not be patent eligible.
Patent Protection
Patents can be a powerful form of protection for AI-related IP, particularly because independent creation is not a defense to patent infringement. Since patent rights are based on first to file, getting an early filing date is essential. The filing date is applicable worldwide and it is critical for startups to file as early as possible, which is often when money is at its tightest.
Nonetheless, AI is extremely challenging from a patentability perspective because patent law progresses linearly, while advances in AI move far more quickly creating a gap and the ability of the law to address them is getting wider. Three to five years is the typical timeline from filing a patent application to obtaining allowable subject matter. This is an eternity in the AI world and at any time in that process, an applicant for a patent could be infringing someone else’s intellectual property. It is important to recognize that patents do not protect data compilations, such as AI training sets, a programmer’s particular expression of source code, or other types of proprietary information that may be competitively advantageous and constitute a trade secret.
The patent system in the United States also presents uncertainties regarding patentability as it pertains to certain aspects of AI, such as software. Since the Supreme Court’s decision in Alice, many software patents have been attacked and invalidated as patent ineligible. Under this ruling, the decision to seek a patent may have adverse consequences. If a patent is sought but not granted or granted and then invalidated, the subject matter may have become public, rendering not only patent protection but also trade secret protection unavailable. Patents have a limited term of protection (20 years from the earliest filing date), after which the subject matter becomes dedicated to the public. A copyright term is much longer (the author’s life plus 70 years), and trade secret protection can theoretically last forever, as long as secrecy is maintained and the information is not publicly known. Trade secret and copyright protection should be taken into account when developing an effective AI protection strategy.
Trade Secret Protection
Federal and state trade secret laws protect economically valuable secrets. Protectable information includes formulae, compilations, programs, methods, techniques, processes, designs, and codes. Unlike a patent, no application or registration is required to obtain trade secret protection. Trade secret protection arises automatically provided that the trade secret owner can demonstrate that the information creates a competitive advantage by virtue of its secrecy and that reasonable measures have been taken to maintain its secrecy. Many AI system elements are well-suited for trade secret protection, such as: neural networks, including modular network structure and individual modules; training sets, data output, and other data; software including underlying AI code and AI-generated code; and learning, backpropagation, and other algorithms.
The methodology to maintain the secrecy of a trade secret may vary depending on a company’s size and resources, but they must include physical and technical solutions to limit and monitor access to trade secret information. Physical solutions include locked cabinets and server rooms, whereas technical solutions may involve multi-factor authentication, mobile device management, and data loss prevention software. Written policies should dictate trade secret management, and employees who have access to trade secrets should be limited in number and contractually required to protect company confidential and trade secret information from improper disclosure. When sharing trade secrets with business partners, nondisclosure agreements should have secrecy obligations, audit rights, and provisions for post-relationship control. Object code given to customers should include digital rights management and robust licensing terms containing anti-reverse engineering provisions.
The mission of the Kansas City Augmented Intelligence Laboratory is to become a regional leader in the delivery of hands on, no cost, training for individuals who seek to become not only knowledgeable, but proficient, in AI and ML. If you have an interest in learning more about the Kansas City Augmented Intelligence Laboratory reach out to counsel for the Laboratory, Bob Lambrechts at blambrechts@lathropgage.com or at (913) 451–5126.
Bob Lambrechts is a partner in the Overland Park office of Lathrop Gage LLP where he practices as an Intellectual Property lawyer.
