Matt Hervey on navigating the legal implications of generative AI

Posted by Mike Walsh

Apr 7, 2024 9:59:34 AM

Matt Hervey 1-1

 

What are the new challenges that generative AI is creating for copyright law? In this episode, I speak with Matt Hervey, the head of AI law at Gowling, to explore the legal intricacies surrounding the creation of content and ideas by large language models. In our discussion, Matt sheds light on the complex landscape of AI ownership, highlighting the differences in legal frameworks across various jurisdictions, such as the UK, EU, and US. 

In Matt’s view, a key issue for leaders to consider in determining the ownership and protectability of AI-generated works, is the degree of human involvement and the level of effort contributed. We also touch upon the controversial issue of training data and the potential liabilities arising from the use of scraped content from the internet.

In this episode, we further explore the transformative potential of AI in industries like life sciences, where AI-powered drug discovery and clinical trials are already making significant strides. Matt discusses the importance of documenting the AI development process to mitigate risks and the need for organizations to develop proprietary models to safeguard their intellectual property.

The 5 Key Takeaways:

1. Understand the legal implications of AI ownership and the varying levels of protection across different jurisdictions to inform strategic decisions and mitigate risks.


2. Assess the potential liabilities associated with training data and implement measures to ensure the ethical and responsible use of AI within the organization.


3. Recognize the transformative potential of AI in industry-specific applications and invest in proprietary models to leverage unique data assets and gain a competitive edge.


4. Foster collaboration between legal, technical, and domain experts to develop a comprehensive understanding of AI's impact and potential within the organization.


5. Prepare for the future of AI-powered organizations by building interdisciplinary teams and upskilling employees to effectively navigate the complexities of AI implementation and governance.

 

 

 

 

Topics: Legal