Artificial intelligence (AI) has quickly become one of the pillars of the modern economy. According to one widely cited study from 2017, AI could contribute up to $15.7 trillion dollars to the global economy by 2030. That prediction is already coming to fruition. According to a White House report on AI from February 2020, “AI is already having a substantial economic impact, not only for companies whose core business is AI, but also for nearly all other companies as they discover the need to adopt AI technologies to stay globally competitive.” The recognition of the importance of AI is both broad and worldwide. Russia’s Vladimir Putin has gone as far as to state that “whoever becomes the leader in [AI] will become the ruler of the world.”
It is thus no surprise that companies are heavily investing to protect the intellectual property generated from their investments in AI technology. The question becomes how to best protect those investments in this critical space. For example, an autonomous driving company may be looking at its AI training data (i.e. records of previous test drives), the artificial neural network implementations generated from that training data (i.e., the software that helps the car drive itself), and assortments of other source code necessary to operate an autonomous car. For each of these elements, the company must examine what aspects are patentable, subject to trade secret protection—or both. The wrong decision on these topics could result in the company being left with no meaningful intellectual property protection for its most important research and development.
But patenting AI technology today can be difficult. Due to the prohibition on patenting abstract ideas, acquiring meaningful patents on artificial intelligence systems is not straightforward. Thus companies are increasingly turning to trade secret protection to protect their AI-related intellectual property. This article explores the tradeoffs between patents and trade secrets in the AI sector. It then describes how trade secrets have become essential tools for companies to protect their AI-related intellectual property. Finally, it concludes with practical guidance for in-house counsel on how to leverage both patents and trade secrets to best protect valuable intellectual property regarding AI.
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