C-Suite Perspectives On AI: Nikhil Vadgama Of DLT Science Foundation On Where to Use AI and Where to Rely Only on Humans
An Interview With Kieran Powell
Does the task require specialist knowledge? If so, use AI as a supporting tool and not do the work for you, as it’s not going to do a great job!
As artificial intelligence (AI) continues to advance and integrate into various aspects of business, decision-makers at the highest levels face the complex task of determining where AI can be most effectively utilized and where the human touch remains irreplaceable. This series seeks to explore the nuanced decisions made by C-Suite executives regarding the implementation of AI in their operations. As part of this series, we had the pleasure of interviewing Nikhil Vadgama.
Nikhil Vadgama is a distinguished expert in web3 and emerging technologies, specialising in artificial intelligence and blockchain. He is a co-founder and director of the DLT Science Foundation and deputy director of the UCL Centre for Blockchain Technologies. He is also an associate professor, programme director, and esteemed lecturer for several of University College London (UCL)’s world-class programmes, including financial technology, emerging digital technologies, and others. He also represents UCL on the Hedera Governing Council.
Nikhil has pioneered many new emerging digital technology education initiatives, including executive education, online education, accredited education, and education standards. He also has extensive industry experience in financial services, having launched a challenger bank in multiple countries, and previously working for large global investment banks.
Thank you so much for your time! I know that you are a very busy person. Our readers would love to “get to know you” a bit better. Can you tell us a bit about your ‘backstory’ and how you got started?
I started out with a degree in physics, which laid the groundwork for a methodical and analytical way of thinking. From there, I transitioned into the fast-paced world of investment banking, both in the UK and Asia. This experience gave me a deep understanding of global finance and business practices. While in Asia, I started learning Mandarin and immersing myself in Chinese culture. This opened the door to participate in the booming education businesses that were rapidly developing in China at the time. However, due to unforeseen circumstances, I found myself in the wrong place at the wrong time and decided to move back to the UK.
Back in the UK, I pivoted my focus towards fintech, specifically AI in real estate. This eventually led me into academia, where I started working at University College London. At UCL, I progressed to become an Associate Professor running Financial Technology programmes. I’ve had the opportunity to launch a challenger bank in the UK, Europe, and the US. Most recently, I’ve been involved with DSF (DLT Science Foundation), continuing my journey in the industry. So that’s a bit about my backstory.
It has been said that our mistakes can be our greatest teachers. Can you share a story about the funniest mistake you made when you were first starting? Can you tell us what lesson you learned from that?
A good lesson I learnt early on is to always have two of everything in business, particularly with bank accounts, critical infrastructure, systems and people in roles. Too many times early on in my career, I’ve had a system go down, leaving me and perhaps the organisation in panic — if you have redundant systems, then you don’t have to worry!
Are you working on any exciting new projects now? How do you think that will help people?
Yes, we are launching some exciting new projects at DSF, including a venture fund to invest in blockchain and new emerging technologies — particularly looking at technology convergence. The venture fund will help to provide much needed capital for new entrepreneurs in Web3.
Thank you for that. Let’s now shift to the central focus of our discussion. In your experience, what have been the most challenging aspects of integrating AI into your business operations, and how have you balanced these with the need to preserve human-centric roles?
One problem we have at the moment is LLM (large language model) fatigue — too many people use AI LLMs in an extremely lazy way. This means that the quality of their work deteriorates. In fact, in these very tasks, it would be better to go with a human-centric approach first and then to correct, or ideate with an LLM and do the work. Too many times, people try and use AI LLMs simply to do their work, and it ends up missing the mark entirely.
Can you share a specific instance where AI initially seemed like the optimal solution but ultimately proved less effective than human intervention? What did this experience teach you about the limitations of AI in your field?
When AI tools initially came out, they seemed like an amazing breakthrough and opportunity to surcharge one’s efficiency, but you must be careful. Too many times, I come up against the limitations of using AI. For instance, the tone and writing can be poor. Similarly, AI LLMS still find it difficult to interrupt and help with seemingly easy tasks, such as processing tables or outputting them. Let me give you an example. In my organisation, we run many events where we produce transcripts of what went on and what was said — but if you ask AI LLMs to produce a white paper or good summary, it shows that they are incapable in specialist areas. This means these types of documents can be written by LLMs, but they require a lot of editing afterwards. Sometimes, it can be faster to just write it from scratch yourself.
How do you navigate the ethical implications of implementing AI in your company, especially concerning potential job displacement and ensuring ethical AI usage?
AI is predominantly employed by organizations for use cases that do not typically give rise to ethical implications. Yes, if you are talking about bias in models for credit scoring or facial recognition — sure, there are plenty of ethical implications. But for the vast majority of use cases at many companies, we are talking about AI optimising processes and improving decision-making and efficiency. Here, ethical implications don’t really come into the equation. With regards to job displacement, as I said before, it’s still some time away, and when it really does begin to affect the workforce, who knows what the dynamics will be then. Certainly, it will be robotics and AI combined that will be the great differentiator.
Could you describe a successful instance in your company where AI and human skills were synergistically combined to achieve a result that neither could have accomplished alone?
As a tool for editing, writing, and ideating, AI LLMs are fantastic. Particularly for helping you think through different permutations or giving you different perspectives for particular tasks, these models are very good. Many of the higher-level tasks we do, have some input from AI to help refine thinking. Certainly, it is not good enough on its own, but it helps to give you an added dimension of intelligence.
Based on your experience and success, what are the “5 Things To Keep in Mind When Deciding Where to Use AI and Where to Rely Only on Humans, and Why?” How have these 5 things impacted your work or your career?
- Does the task require specialist knowledge? If so, use AI as a supporting tool and not do the work for you, as it’s not going to do a great job!
- Is it the AI, or is it your prompt? Sometimes, when you are using AI, you might not get a great response from it, but it may be because of the prompt you are using. Think about using different prompts or breaking your prompts down into smaller steps.
- Are you seeking fresh ideas, need to be creative, or need to see something from a new perspective? If so, AI can help you ideate and see things in a new way.
- Is your task something that makes you accountable and needs to be reliable? Use AI as an assistant, but don’t rely on it fully in case of hallucinations.
- Are you faced with a complex, unpredictable challenge? Keep in mind that humans are better at handling these types of problems than AI is.
Looking towards the future, in which areas of your business do you foresee AI making the most significant impact, and conversely, in which areas do you believe a human touch will remain indispensable?
AI is going to have the biggest impact in helping lower-skilled employees rather than displacing more advanced knowledge workers. It is unlikely that AI will rapidly reduce job opportunities, but instead will be utilized to enhance the productivity of workers with lower skills. A human touch will still remain crucial in most areas — it is just something that we as humans need. The big change for this will come with robotics — but we are still a long way from that. For example, Tesla has developed a robot that can fold clothes, but this technology is only functional in a highly controlled environment. The combination of AI and robotics will potentially have the most significant impact of all the applications of AI.
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, what would that be? You never know what your idea can trigger. 🙂
I think AI is going to really surcharge education, particularly for people from the developing world. This is something that I’m passionate about, and as AI LLM models develop further, they will be great personal learning tools for the global youth to get education at levels that people in more developed countries enjoy.
How can our readers further follow your work online?
You can connect with me via LinkedIn, and also follow the DSF profile! Be on the lookout for new books, and academic papers on Google Scholar.
This was very inspiring. Thank you so much for joining us!
About The Interviewer: Kieran Powell is the EVP of Channel V Media a New York City Public Relations agency with a global network of agency partners in over 30 countries. Kieran has advised more than 150 companies in the Technology, B2B, Retail and Financial sectors. Prior to taking over business operations at Channel V Media, Kieran held roles at Merrill Lynch, PwC and Ernst & Young. Get in touch with Kieran to discuss how marketing and public relations can be leveraged to achieve concrete business goals.
C-Suite Perspectives On AI: Nikhil Vadgama Of DLT Science Foundation On Where to Use AI and Where… was originally published in Authority Magazine on Medium, where people are continuing the conversation by highlighting and responding to this story.