The rise of artificial intelligence is reshaping the law and legal landscape faster than most policymakers can respond. From intellectual property disputes to algorithmic accountability, businesses now face complex challenges that demand new approaches to governance and compliance. Few experts understand this convergence of technology and regulation better than Lee Tiedrich.
As a Distinguished Faculty Fellow at Duke University and former partner at Covington & Burling LLP, Lee has spent over three decades advising global corporations, governments, and non-profits on emerging technology strategy. Her work with organisations such as the OECD and the Global Partnership on AI has positioned her at the forefront of responsible innovation and digital ethics.
In this exclusive interview, Lee explores the evolving relationship between AI and the law, discussing how intellectual property frameworks, corporate governance, and international regulation must adapt to a world increasingly defined by intelligent machines.
Q: In your view, what major legal challenges should businesses operating with AI and other emerging technologies be preparing for today?
Lee Tiedrich: “AI has evolved so much faster than the laws, and businesses need to know that policymakers are feverishly sprinting to catch up. We’re seeing this play out globally in several ways.
“First, in some jurisdictions such as the EU and the US, we’re seeing new AI legal requirements imposed. Second, there’s been a real uptick in enforcement actions pertaining to AI, ranging from issues such as data scraping, allegations that AI is discriminating against protected people, and consumer protection issues.
“Third, we’re seeing AI policies and laws evolve through procurement practices, through standards, and through other means. So, the bottom line is that businesses need to pay attention to the quickly evolving AI legal landscape, not only to avoid reputational harm and legal liability, but because trusted artificial intelligence products, services, and offerings make good business sense.
“Well, I think it starts with the AI ethics and data governance that I talked about and by design, and I think it really involves building upon the multi-disciplinary team. What I’d add here is that it really requires constant attention throughout the entire life cycle.
“For example, if you’re thinking about deploying AI within your organisation, you want to think about beforehand: what are the risks? What steps can you take to mitigate the risks? What are the benefits you’re trying to capture? Think about that in the initial deployment stage and make sure that’s carried throughout the entire life cycle, through deployment and implementation.
“The same thing goes on the design cycle. When you’re designing the product, you want your technical team and your business team to be thinking upfront — what are the legal issues we need to think about? What are the ethical issues we need to think about? Sustainability, which is a really important part of my work as well, needs to be factored into the design and carried through development, deployment, and the final retirement life cycle.
“It really does take a governance structure, it takes vigilance, but it can be done. I’ve seen it done, and I think it’s worth doing because, like I said, good ethical products sell and it also helps reduce a lot of the legal risk.”
Q: When integrating new technologies into an organisation’s existing products or strategies, what process would you recommend to ensure both innovation and compliance?
Lee Tiedrich: “As I said at the outset, what we’re seeing is that artificial intelligence has evolved so much faster than the law, and intellectual property laws are no exception. First of all, companies want intellectual property often because it’s a big revenue generator. From a business perspective, it’s very important.
“They also want to avoid infringing third-party intellectual property because, if they infringe third-party IP — whether we’re talking about patent portfolios, content, or brands — it could result in big liability, as can the misappropriation of trade secrets.
“Intellectual property has always been important from a business perspective, even before AI became really popular. AI is raising some unique issues when it comes to intellectual property. For example, what we’re seeing a lot these days is that AI is being used to generate new intellectual property — new things of value.
“For example, AI can be used in drug discovery and identify compounds; AI is creating creative content, and our laws have not really caught up to answer the questions of if AI is used to generate new things of value that we would typically associate with intellectual property, is that output entitled to intellectual property protection?”
Q: How are intellectual property issues influencing the deployment of emerging technologies, and what can companies do to navigate the current legal uncertainties?
Lee Tiedrich: “What degree of human interaction is necessary to obtain intellectual property protection? The laws also are not particularly clear, particularly when you have complex value chains, on who has rights to the resulting work if it is entitled to intellectual property protection.
“A lot of my work, stemming back to my 30 years as a corporate lawyer, is looking at what tools we have in our chest today to help provide companies with more certainty around these issues because laws tend to evolve slowly.
“Intellectual property, like many issues, is super complicated — not only are the laws perhaps unsettled within a particular jurisdiction, but when you start looking across jurisdictions, we have lots of different legal regimes.
“A lot of my work through the Global Partnership on AI, building upon my years of practice, is focused on how we can use tools like contracts to help address some of the uncertainty that exists in the marketplace today.
“The focus of my work at the Global Partnership on AI is how we can foster the development of standard contract terms that will make these transactions more predictable and easier, reducing some of the transaction costs.
“Our work has highlighted that these standard contract terms also need to be complemented by business codes of conduct, technical tools, and education — and, of course, supported by good legal frameworks.
“So, bottom line is intellectual property is very important to businesses. Businesses want to protect it; they want to avoid infringing third-party IP. In the meantime, particularly at the intersection of AI and IP, the laws remain unsettled. But I do see contracts as a tool where parties can try to get a little bit more certainty around some of these issues.
“Data scraping is another IP issue as well — it raises a plethora of issues. Companies and AI developers are scraping the internet, third-party websites, and social media properties to get data to train AI algorithms. That’s given rise to a whole host of lawsuits and enforcement actions, raising intellectual property, privacy, and consumer protection issues, and the list goes on.
“One of the questions is how can standard contract terms potentially help address data scraping practices and put it in a way where parties feel it’s fair and legally compliant? The hope is that, by looking at contracts in combination with some of the other tools I mentioned, we can address these issues.
“Bottom line: AI is evolving very quickly, raising a lot of IP issues, and organisations need to be creative about thinking about tools they can use today, in the face of legal uncertainty, to try to address some of these issues.”
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