An Interview With Chad Silverstein
Find the most trusted AI vendor possible. Once you’ve found it, validate that they will be investing in your market for at least the next three to five years and have a robust set of resources invested in AI. AI technologies are advancing too quickly and with too many providers in many fields. Picking the right partner with staying power is crucial.
In today’s tech-driven world, artificial intelligence has become a key enabler of business success. But the question remains — how can businesses effectively harness AI to address their unique challenges while staying true to ethical principles? To explore this topic further, we are interviewing Shandon Quinn.
Shandon Quinn is Vice President of Patent Intelligence, Search, and Analytics at Clarivate. In this role, he leads the division that provides leading software, people-based services, and unique data for over 5,000 companies and law firms worldwide to support their critical IP, innovation, and R&D decisions. These offerings include Derwent Innovation, Innography, Incopat, Derwent SequenceBase, the Derwent World Patents Index, GENESEQ, the Chemical Patents Index, and several new product innovations in development. Shandon has nearly twenty years of experience in the information, data, and analytics industry. He is a graduate of Princeton University with a degree in chemical engineering.
Thank you so much for joining us in this interview series. Before we dive into our discussion, our readers would love to “get to know you” a bit better. Can you share with us the backstory about what brought you to your specific career path in AI?
At Clarivate, I lead teams building AI solutions for intellectual property (IP) professionals who want to protect and monetize their inventions.
My journey began with cheesy cornmeal snacks and the scientific journal, “Powder Technology”. When I was a food scientist doing research early in my career, IP and innovation monetization were introduced into my life when I learned about patenting a new cornmeal snack technology I was researching. Having my other early research published in “Powder Technology” led to the beginning of my career in the publishing, information, and data services industry. Throughout that career, I observed how high-quality content and data became the lifeblood of machine learning and AI.
Now, those two themes have come together as I build AI for IP. Clarivate is the perfect place to pursue this passion because our solutions sit at the intersection of data and technology and serve multiple parts of the innovation cycle. We have the honor of supporting thousands of organizations by integrating technology with our extensive content, thereby aiding the entire IP industry.
Can you share the most interesting story that happened to you since you started working with artificial intelligence?
I was once part of a team that fine-tuned an AI model using what we believed was a really good set of data, but it actually made our model worse! That experience forced us to review our AI development protocols and examine the training data more carefully. We found some issues with both that led to the unexpected outcome.
This story reminded me that developing AI is like raising children. They need sustained and iterative care, feeding, training, re-training, and scrutiny to evolve and grow. And it’s normal to have setbacks every now and then. At Clarivate, we have structured our AI developments and investments to be continuous and sustainable to overcome stories like these.
You are a successful leader in the AI space. Which three character traits do you think were most instrumental to your success? Can you please share a story or example for each?
#1: Problem-scoping. Defining the exact scope of the problem your AI solution is meant to solve is crucial to focusing the experimentation, development, and go-to-market messaging. In one AI project, we had the option to develop AI at either a very niche use-case level or an entire solution category. Choosing to develop the niche AI solution helped us launch it quickly in that case.
#2: Perseverance. I mentioned the story earlier about an AI solution that got worse when we fine-tuned it. You need perseverance as a product and project leader to iterate continuously on AI through setbacks. My team has an AI model in its ninth version for a solution that has only been on the market for nine months.
#3: Commercial Sense. Fitting an AI solution to address the right problem for the right user through the right scaled channel to market is more crucial than ever. Developing AI requires significant investment; therefore, the return on that investment must be sustainable. For a different AI project my teams have worked on, we carefully analyzed both the costs of different AI models we could have used, and the expected commercial benefit via our product suite to confirm we could sustain them.
Let’s jump to the primary focus of our interview. Can you share a specific example of how you or your organization used AI to solve a major business challenge? What was the problem, and how did AI help address it?
Many organizations developing new inventions and technologies often have to determine whether they can get a patent by searching for prior art. This is a challenge because the volume of patents has increased dramatically in the last couple of decades. It can usually take many hours to craft and conduct the search properly and determine an invention’s patentability.
Clarivate recently solved this by developing an AI patentability search solution. Our new AI Search in Derwent Innovation uses a language transformer model trained on our proprietary database of 66m+ invention summaries (the Derwent World Patents Index) to understand the context of an inputted invention description, and return highly relevant results for patent prior art searching. The solution can find the most relevant prior art hits in a matter of seconds, a game-changing enhancement compared to the hours it would have taken in the past.
What are some of the common misconceptions you’ve encountered about using AI in business? How do you address those misconceptions?
One of the biggest misconceptions is that organizations can easily develop their own custom AI solutions. The appeal of a bespoke system trained solely on your company’s private data is strong. But I have heard from many clients who encounter major hurdles: managing infrastructure costs, cleaning and curating large datasets for training or fine-tuning, hiring and keeping data science talent, and maintaining the code.
Oftentimes, the best choice for these clients is to outsource these risks to a trusted service provider who understands their problems and data and can demonstrate sustained investment into AI on their behalf. Clarivate has invested in machine learning and AI for more than 15 years and has served the industry for more than 60 years. We are a trusted service provider to many of the world’s top innovators.
In your opinion, what is the most significant way AI can make a positive impact on businesses today?
The most significant way that AI can make a positive impact today is by re-igniting and revisiting past ideas that a business previously found to be impossible. AI might be the technological key to finally unlocking many customer problems. For example, four years ago my business attempted to solve a distinct patent licensing problem that had emerged across the telecoms industry. We failed, because at the time, the algorithmic and deterministic models we developed then weren’t good enough. Fast forward to now: we are developing a new language-based probabilistic model for the same problem, and it is already demonstrating successful matches to support patent licensing.
In the IP space, AI will enhance multiple such parts of IP creation, maintenance, and protection, but without altering them beyond recognition. We are now at a stage where AI can handle tasks on our behalf, such as repetitive, boring, and labor-intensive workflow steps. Think of tasks like finding patents, reading patents, docketing, and sorting patents. Two years ago, when we asked our Derwent Innovation community of thousands of users about which feature they most wanted on our roadmap, an AI patent search feature was their top choice, with over half showing interest.
AI has shown it can help increase the productivity of patent searching, patent classification, patent application editing and drafting, office action responses, and docketing and administration. As a result, smart, experienced IP team members can do less of the “doing” tasks and more of the “thinking” tasks, becoming more strategic in a complex and fast-paced environment.
Ok, let’s dive deeper. Based on your experience and research, can you please share “5 Ways AI Can Solve Complex Business Problems”? These can be strategies, insights, or tools that companies can use to make the most of AI in addressing their challenges. If possible, please share examples or stories for each.
It’s no surprise that all of my solutions relate to intellectual property, innovation and R&D. Here they are:
1. Legal patenting decisions — The complex determination of whether a business’s new technology or invention is novel enough to merit a patent, and useful enough as it relates to products that could be developed, can be solved with AI. Clarivate has developed Derwent AI Search to make first-pass patentability searching easy. It will only get easier.
2. Patent business decisions — Many organizations can unlock new commercial opportunities for their patent portfolios with the help of AI. For example, Clarivate has developed an AI solution in its Innography platform that can classify all the patents of a third-party company against a company’s own products and technologies. When done well, that classification can confirm whether that third party is a potential target for licensing technology and generating new revenue.
3. Patent drafting and prosecution — The process of applying for a patent with a national patent office requires domain expertise as well as legal craftsmanship. AI can automate the more tedious tasks within this workflow, from converting the invention features into patent claims to generating illustrations or responding to patent office communications. Rowan Patents from Clarivate supports all of these tasks and has helped convert many patent application workflows from human-generated to human-reviewed, faster experiences.
4. Competitive intelligence — An organization’s patents are a window into its technology and product strategies, and analyzing patent trends can be extremely revealing for competitive intelligence. AI capabilities are being developed that can create landscapes of technological movement based on patents. As a result, they can identify barriers and white spaces.
5. Simulating IP scenarios — IP can be very event-driven, with licensing agreements and infringement lawsuits generating significant risk and opportunity. AI can turn simulation exercises into more regular practices. Clarivate is exploring simulation solutions for patent portfolio management to help clients manage their riskiest decisions.
How can smaller businesses or startups, with limited budgets, begin to integrate AI into their operations effectively?
Find the most trusted AI vendor possible. Once you’ve found it, validate that they will be investing in your market for at least the next three to five years and have a robust set of resources invested in AI. AI technologies are advancing too quickly and with too many providers in many fields. Picking the right partner with staying power is crucial.
What advice would you give to business leaders who are hesitant to adopt AI because of fear, misconceptions, or lack of understanding?
Evaluate, evaluate, evaluate.
This constant evaluation is essential for three reasons.
First, it will familiarize your team with AI, its concepts, and its evolutions. If you aren’t going to be building models yourself or learning how to prompt models properly, then at least become familiar with the tools that can be trained on for specific jobs and challenges.
Second, continuous evaluation is truly the only way to know what the best-performing AI tools are for your needs. In a highly confidential space like patents, there are few true benchmarks and gold tests that can be shared among organizations to know what is best. So be ready to make that determination yourself with a set of test cases that are unique to your business.
Finally, AI is moving too fast to assume that you can make a decision that will serve you well for multiple years. Unless you have a trusted partner who you know is going to be investing continuously in the sustainable future of their AI-enabled solutions in the right way, you should assume the AI technology will be obsolete, or at least stale, a year later. Be ready to do your diligence in asking how dedicated a vendor is, how much they are continuously investing in their AI models, where they get their training data from, and how they are managing significant AI development and maintenance costs.
In your opinion, how will AI continue to shape the business world over the next 5–10 years? Are there any trends or emerging innovations you’re particularly excited about?
The most exciting AI innovations for me will be laser-focused B2B solutions leveraging sector-specific and proprietary data. While LLMs are paving the way generally for all professionals and individuals to find productivity enhancements for day-to-day tasks, these B2B AI solutions are what enable businesses to shift teams towards higher-value problems. The commitment from Clarivate to support the IP space is a great example of this. I think we will see a step-change in IP and B2B knowledge worker productivity that we’ve never seen before.
As mentioned earlier, at the moment, we’re in a phase of accepting AI to do things on our behalf. This is the phase we’re in now and for the next five years. The second phase is accepting AI to think things on our behalf. In the IP space, this includes tasks like interpreting a patent claim, drafting a claim, correlating with standards and products, and taking monetization decisions like abandoning, licensing, and asserting. This phase will require more AI technology development and harder discussions about the inflection of professions before we see mass adoption.
How do you think the use of AI to solve business problems influences relationships with customers, employees, and the broader community?
In the IP space, the job of an IP professional is getting harder, but the same translates to many other sectors. Patent volumes continue to grow. More jurisdictions, markets and products face uncertainty. Corporate and law firm IP budgets are tightening while competitors are emerging faster from more places. Technologies advance at record paces, and portfolios are more complex. At the same time, IP professionals are being asked to prove more value to the business amidst all of that. Against this daunting backdrop, there’s never been a better time for AI to help IP professionals do more with less.
At the same time, the biggest question in the AI movement will be who captures the value from the benefits AI provides. For example, if an IP law firm attorney bills by the hour, which is the current standard, but becomes twice as productive by using AI, will they still charge their client the same amount as if they hadn’t used AI? Will the client demand to pay less? The answer to these questions has profound implications for the IP legal industry and communities. We will see this same tension created across all industry value chains.
You are a person of great influence. If you could start a movement that would bring the most amount of good to the most amount of people through AI, what would that be? You never know what your idea can trigger. 🙂
Patents underpin most of the major innovations that have shaped our society for the past 250 years. If we, as an industry, truly can deploy AI to enhance the rate at which inventors develop new inventions and increase the quality of those inventions, then I can’t see how all of society wins. AI for IP can revolutionize the world.
How can our readers further follow you online?
At Clarivate, our Clarivate for Intellectual Property LinkedIn and my personal Linkedin.
This was great. Thank you so much for the time you spent sharing with us.
About the Interviewer: Chad Silverstein is a seasoned entrepreneur with 25+ years of experience as a Founder and CEO. While attending Ohio State University, he launched his first company, Choice Recovery, Inc., a nationally recognized healthcare collection agency — twice ranked the #1 workplace in Ohio. In 2013, he founded [re]start, helping thousands of people find meaningful career opportunities. After selling both companies, Chad shifted his focus to his true passion — leadership. Today, he coaches founders and CEOs at Built to Lead, advises Authority Magazine’s Thought Leader Incubator.
Shandon Quinn of Clarivate On How Artificial Intelligence Can Solve Business Problems was originally published in Authority Magazine on Medium, where people are continuing the conversation by highlighting and responding to this story.