With just a week to go until the Dublin IP and R&D Summit 4.0, our star-studded lineup is ready to make a lasting impact on the intellectual property landscape. This promises to be our most exciting edition yet!
We’re thrilled to feature Sergey Kinchin, In-House Counsel at ICON PLC, in this exclusive interview. Sergey has been admitted to practice law since 2010 and has worked across a wide range of industries and businesses, ranging from startups to multinationals. Sergey manages ICON’s global IP portfolio and provides legal support to ICON’s AI and IT R&D teams. This includes products such as OneSearch and Cassandra, as well as integration of third party products such as Microsoft Co-Pilot. Sergey provides advice on all aspects of product development, ranging from data acquisition, to patenting the underlying technologies, to governance of output use cases.
Sergey will join the Day Two panel, “AI as a Threat” at the Dublin IP and R&D Summit next week - but until then, you can read his his exclusive interview below.
What do you see as the most significant global trends and challenges currently impacting the IP landscape, and how should IP professionals prepare to address these issues?
I would like to highlight two issues. First, acceleration in AI-driven outputs seems to be both a problem and a solution, challenging our ability to effectively evaluate the landscape and protect new ideas. We need to review how we can sort the wheat from the chaff in the face of the surge of AI-assisted creations.
Second, AI has shone a light on the fragmentation of regulatory approaches to IP protection globally, both in terms of what is protectable and how it is protected. It raises questions about whether we need to re-evaluate where IP is generated and how to adapt global R&D strategies. As an illustration, one of the pivotal issues in the UK Getty Images vs Stable Diffusion litigation was the location the servers that were used to train the LLM were located.
In what ways are emerging technologies, such as artificial intelligence, influencing the IP field, and how should IP Professionals adapt to these technological advancements?
The technologies are influencing what IP we are protecting as well as how we are protecting it. Large language models are likely to be more adept at working with IP than we realise. For example, in the NYT case vs OpenAI, Google Patents was listed as the single largest source of tokens in the Common Crawl database used for training ChatGPT. So, out of the gate, LLMs are likely to be powerful at recognising patterns in patents.
To adapt to the changes IP professionals will need to understand both how the technology works and how to use it in their work. To understand the nature of IP, it will be important to pry open the machine and examine how it generated what it did, including the extent of human involvement. On the professional side, we could see increased volumes of work, but fortunately, the technology promise to offer solutions to coping with this. Thus, an understanding of the emerging technologies is critical in understanding both what we are dealing with and how we can deal with it most effectively.
What are the ethical considerations and potential legal challenges associated when using AI tools internally?
The commentary on AI, for example from Ethan Mollick, suggests that in many cases the approach to internal use of AI tools is yet to mature. A key challenge is transparency. Ethan refers to a lot of ‘hidden’ use of AI, where staff might fail to disclose their use of AI.
This lack of trust and transparency can feed into other issues. It can bring into question the integrity of the work and the ability to rely on it, for example, if copyright is challenged. Further, it can raise questions about competency or the value of certain competencies, ‘why do we need you, if AI did it’. These are rough ethical challenges to balance.
What are the most effective strategies for enforcing IP rights on a global scale, particularly in combating issues like counterfeiting, piracy, and infringement?
From my perspective, it is taking a risk-based approach that is proportionate to what is at stake. The benefit of this approach is that it remains valid and current even in the context of fast-paced technological and regulatory developments, since failure to keep up is a risk that needs to be balanced.
A critical aspect in developing an effective strategy is finding the right balance in terms of the investment made into enforcing IP rights, versus the value protected or generated by the process. A risk based approach takes into account the point I highlight in the next section: what if things that we value today are valued differently tomorrow? What do we need to do now to be ready for that tomorrow.
What do you predict for the future of IP management and protection over the next decade, and what innovations or changes do you believe will be most transformative for the industry?
We could see a rebalancing of the value of the underlying assets in IP. AI could lead to depreciation of a lot of assets that in the past were labour intensive or required rare, but replicable skills. At the same time, there might be a spike in the value of technologies that cause such change. It would be interesting to see if such value can hold long-term.
A critical input into the long term future of IP management might be how the regulatory fragmentation will play out in the short to medium term. After all, IP management in a world in which AI generated content cannot be patented or copyrighted would be very different from the one where it can be.
How do you balance the need for innovation with the protection of intellectual property rights within a company?
While there is some tension, the need for innovation does not necessarily conflict with property rights. Rather, they should be seen as mutually reinforcing processes that help deliver sustained progress, akin to a ratchet.
The tension is there because innovation is a developmental and forward-looking process, while protection is to an extent, reactive – there is an element of consolidating what was already invented. I use the ratchet analogy because protection of IP helps to secure the gains. This can then help evaluate and consolidate the progress, forming a springboard for the next round of innovation.
Join Sergey on Day Two at the Dublin IP and R&D Summit 4.0!
He’ll be part of the highly-anticipated panel, “AI as a Threat,” where industry experts from Vinted, Wesco, and more will explore the potential IP infringement risks posed by AI and machine learning - and how to mitigate them.
Don’t miss this exclusive opportunity to meet Sergey and learn directly from this expert himself!
Secure your spot today:
Comments