Legal Outlook podcast 5

Legal Outlook podcast 5: transcript

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Nina Fitzgerald:
Hello, and welcome to episode five of Ashurst Legal Outlook series on all things AI. My name is Nina Fitzgerald, IP and media partner at Ashurst. And today I'm joined by Julie Cheeseman, counsel at Ashurst in the IP media team, where she specializes in media, IT and IP disputes. So far throughout this series, we've introduced AI and ethical considerations. We've also examined AI from a copyright and patents perspective.

In this episode, we consider the use of trade secrets to protect AI and the unique challenges of protecting AI using trade secrets. Join Julie and myself as we consider these laws and whether they are the best means for protecting AI systems. You are listening to Ashurst Legal Outlook.

Hi Julie. Today, we're going to talk about AI and trade secrets, and I thought a great place to start would be for you to talk a little bit about what a trade secret is.

Julie Cheeseman:
Thanks, Nina. That's a great starting point.

A trade secret is a category of information that has the quality of intrinsic confidentiality, the secrecy of which is maintained by its owner. So think of the recipe for Coca-Cola, KFC's 11 secret herbs and spices, and Google search algorithm. These are all trade secrets, which have been strongly guarded by the company to rely on them.

Nina Fitzgerald:
Okay. So, how are trade secrets protected under Australian law?

Julie Cheeseman:
Good question. In Australia, there's no common law or statutory cause of action directed specifically to the protection of trade secrets. Instead in Australia, we give trade secrets legal protection through the equitable doctrine of breach of confidence and where there's an appropriate clause breach of contract.

Nina Fitzgerald:
What do you need to do to satisfy a breach of confidence action? What do you need to make out in order to get a remedy?

Julie Cheeseman:
Sure. It's essentially three elements that you'll need to make up for a successful breach of confidence action. First, the information you are trying to protect needs to be confidential. Next, that information needs to have been imparted or communicated in circumstances importing an obligation of confidence. And finally, there needs to have been an unauthorized use of the confidential information to the detriment of that person who imparted or communicated it.

Nina Fitzgerald:
When you say detriment, I'm guessing you mean damage there. We need to be able to prove that there has been some financial loss. Is that right?

Julie Cheeseman:
Correct. Detriment is basically damage as you've identified there.

Nina Fitzgerald:
And so what about breach of contract?

Julie Cheeseman:
Yeah, the equitable action is quite different from the breach of contract. So, a breach of contract is where you have a confidentiality clause in your contract. And that includes an obligation to keep information, which is expressly identified in the contract confidential. Similar to an action to breach of confidence, a confidentiality clause will not typically extend to information which has been made public other than through a breach of the relevant clause.

However, unlike an action for breach of confidence, and this is an important difference, while the recipient must be aware of the obligation, for example, by the express wording in the relevant clause, there is no requirement for detrimental damage.

Nina Fitzgerald:
Interesting. So when you were giving examples of trade secrets before, you mentioned KFC's secret herbs and spices and the Coca-Cola recipe, which is perhaps less relevant in the context of AI. More relevant is Google's algorithm. So does that mean that AI systems or algorithms are typically protected in this manner?

Julie Cheeseman:
That's a really good question. And I think I need to break that down into two parts to answer. To the first aspect Nina, is whether AI systems can be protected by the law of trade secrets. So the answer to that part of the question is yes. So whether by breach of confidence or a contractual provision, trade secret protection is afforded to a broad range of subject matter, including both technical and non-technical information. In Australia, trade secret protection has been afforded to confidential information contained within software. So with that type of protection, the owner of the software may enjoin a third party from copying or using the source code to create new software or to use the information as a springboard for development.

I guess it follows that the same protection would also be available to other elements of AI. For example, the source code, the training data, and the learning algorithms, provided that all of those things have been kept confidential and cannot be reversed engineered. Some of the benefits of trade sacred protection as opposed to patent protection, for example, include that there's no originality, distinctiveness, novelty or inventiveness requirement, there's no application or registration fees. And finally, trade secret protection can last forever, provided that the secrecy is maintained and the information is not publicly disclosed. Additionally, there are other elements of AI that may be particularly well suited to trade secret protection, given the rapid rate of product development and improvement in the technology industry.

Now, going back to your question and addressing the second aspect, which was, our trade secret's typically used to protect AI. The answer actually varies depending on the jurisdiction. So in Australia, for example, breach of confidence litigation to protect trade secrets is really rare. However, in the US, trade secret litigation is on the rise following the commencement of The Defend Trade Secrets Act of 2016. That particular act created a specific course of action, the trade secret misappropriation. And a recent case held that the legislation applies to acts conducted outside of the US, so long as there is a requisite nexus to the US.

Nina Fitzgerald:
So that seems like the US has a better statutory regime in order to encourage trade secret litigation. What are the challenges to protecting AI systems using trade secrets in Australia?

Julie Cheeseman:
There are definitely some challenges, Nina. As I mentioned earlier, in the technology industry, we see really rapid rates of product development, and that's particularly true of where AI is created. Developers regularly rely on open source software to program fundamental components of their technology. While it is possible to keep the company's proprietary source code confidential while also using open code software, a company must be careful to adhere to the license terms, some of which require the company to release their proprietary code to the public under the same or equivalent terms, thereby destroying the confidentiality of the proprietary code.

Another challenge is the risk of reverse engineering when technology is placed on the market. While at present, it may be difficult to reverse engineer complex AI systems, this may not necessarily be the case in the future. And if an AI system can be reverse engineered, treating it as a trade sacred becomes redundant.

A third challenge is behind mobility and atypical employment relationships, which are commonly seen in the technology sector. Ex-employees or consultants may steal trade secrets; however, proving such claims in court can be really tricky as there is often a fine line between an ex-employee's unauthorized use of confidential information and their own skill or know-how. Similarly, where independent contractors who have created AI or software but tailored it for the benefit of their employer, both parties may have ownership claims to different parts of the software. Although not in the trade secrets context, these types of challenges have played out in the courts. For example, in the litigation between the University of Western Australia and Professor Bruce Gray. Now, in terms of the facts of that case, Professor Gray was a full-time professor at the university and had signed a standard university employment contract. During his employment, Professor Gray undertook extensive research into liver and bowel cancer, developed technologies for their treatment and filed several patents in his and others' names relating to those treatment technologies.

After his employment with the university ceased, Professor Gray assigned various property rights to a company which had been set up to commercialize and market the treatment technologies he had developed. This company later went public and by then Professor Gray was the director with a significant shareholding in the company. Not surprisingly, the university was not at all pleased with this development and brought proceedings against the professor, arguing that he had, among other things, breached his employment contract by failing to comply with an implied term, which provided that the university owned the various inventions developed during his employment. The full federal court determined that there was no such implied term and that Professor Gray's employment contract did not provide he was under a duty to provide the university with the benefit of his inventions.

Rather, the full court found that Professor Gray was free to choose the subject matter and direction of his research, that it was not under an obligation of secrecy and that he was free to publish. The university actually sought special leave to appeal to the high court, but that application was refused. I think this case really illustrates that employers should be regularly monitoring the contracts they have with their employees and independent contractors in order to ensure that express terms are included which deal with the question of who owns the rights to inventions made during the term of the contract.

Nina Fitzgerald:

So to sum up, AI may be well suited to trade secret protection, but there are some challenges with this course as well. So on a closing note, with all things considered, how do you decide exactly what mechanisms you'll use to protect your AI system?

Julie Cheeseman:
Look, I think that companies developing AI should consider a holistic approach to their IP protection. They should take into account factors, such as the likely lifespan of the technology, the value of the AI to their business and its importance to their business. Utilizing a range of strategies, including patents, copyright, and trade secrets to protect different aspects of AI is likely to be your most effective strategy.

Finally, a note of thanks, Nina. I've really enjoyed having a chat with you about this topic today. Thanks very much for having me along.

Nina Fitzgerald:
Absolutely. Thank you, Julie.

So I think, based on what you've just said, there are three really practical steps that we should give our listeners. The first is that it's best to have contractual arrangements with employees, contractors, and others working with your business, which clearly set out who owned the relevant products of the arrangement and what information must be kept confidential. This should provide the most straightforward cause of action in the event of any breach.

And secondly, you should put special procedures and policies in place to maintain the confidentiality of any information, which is valuable to your company in the event that you do need to ultimately rely on a breach of confidence action.

And finally, it's important to seek advice ahead of time when determining how your AI system might be protected, such that you can strategically use the various IP regimes as effectively as possible.

Thank you for listening. To hear more Ashurst podcasts, including our dedicated channel on all things ESG, please visit To ensure you don't miss future episodes, subscribe now on Apple Podcasts, Spotify, or your favorite podcast platform. While you're there, please feel free to keep the conversation going and leave us a rating or a review. Thanks again for listening, and goodbye for now.

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