Doug Gilbert Of Sutherland AI On the Future of Artificial Intelligence

An Interview With David Leichner

While the world is blinded by AI’s aggressive evolution, there is little to no discussion or governance on the impact of AI and automation. While there will be a tremendous amount of good that comes from it, there will also be massive negative consequences, whether they are planned or not.

As a part of our series about the future of Artificial Intelligence, I had the pleasure of interviewing Doug Gilbert.

Doug Gilbert is the Chief Information Officer and Chief Digital Officer at Sutherland, where he has been at the helm of all technology functions, digital platforms, IT services, product development, and technology partnerships. As a seasoned leader in digital transformation, Doug plays a pivotal role in client relationship management and solution architecture, leveraging his extensive expertise to drive innovation and deliver measurable business outcomes.

Thank you so much for joining us in this interview series! Can you share with us the ‘backstory” of how you decided to pursue this career path in AI?

My career began as a developer, with a focus on developing systems & security software that automatically blocks nefarious threats for large companies and banks. This foundational experience instilled in me a deep appreciation for the power of automation and the role of machines in enhancing human capabilities.

Throughout my career, I always sought ways to automate processes and assist humans using machines. The shift to AI was simply a natural progression of this journey.

What lessons can others learn from your story?

AI is simply the latest significant evolution in technology. In some of my discussions with younger individuals who aspire to a career in technology, they have a common fear: because technology moves so quickly, they are afraid of focusing on the wrong area and being left behind.

The most successful and interesting people I have met in my career have had numerous roles and focuses along their career journey. What binds them is that they always fall back on the fundamental understanding of technology and then apply that understanding when learning new / emerging technologies.

Can you tell our readers about the most interesting projects you are working on now?

I love and am extremely passionate about the interactions between AI and humans, specifically augmenting human capabilities. I think this is the big grey area that many companies miss.

Many organizations primarily focus on driving savings through automation, but a massive amount of value can be unlocked when AI and humans work together to solve a complex challenge. Just like Tony Stark had Jarvis within his helmet to assist him with every task, AI can be a powerful tool to assist the everyday person, whether that’s through real-time translations, sentiment, and behavior insights or even helping them solve complex problems or everyday challenges.

We are already witnessing this coming to fruition more and more every day. For example, how AI is aiding doctors in detecting cancer cells in radiology images using computer vision or how real-time language translations are enabling seamless communications across languages.

At Sutherland, we are pushing the boundaries further by not only focusing on AI augmentation but also leveraging the power of Human-in-the-Loop (HiTL) approach to improve these models. This approach dramatically improves the learning of both humans and AI simultaneously.

To understand this, it’s essential to understand the concept of Neural Learning in machine learning. When a single node learns something, that “knowledge” is immediately shared across every node on that network. Unfortunately, humans do not learn the same way. If Human A learns something, it doesn’t mean that Human B has also learned it.

Imagine a scenario where whenever someone learns something new, you immediately learn it as well. This was the underlying intent of knowledge bases: to store as much knowledge as possible in a central repository and attempt to make it readily available to everyone else. But this method is clunky and requires manual maintenance of that knowledge.

The current method of training humans and AI is also fragmented and inefficient. However, by implementing a HiTL model, we can create a very elegant and seamless continuous training model for both humans and AI. Here is how…

Let’s imagine that you have a very complex business problem that the AI does not know how to solve. That problem would then NOT be handled at the automation layer but would be routed to a human to solve. AI is always working alongside humans. As humans solve problems, AI will begin to learn the answers to these problems.

We won’t be able to automate a similar problem the next time it comes in, but the AI will provide the FIRST human with a suggested answer. Something along the lines of “Another colleague of yours solved this problem yesterday, and here was their answer.” This new person can review that answer, agree or disagree, and if they disagree, they can provide yet another answer.

When humans agree with an answer, they validate it as a correct answer, and we give that answer a positive confidence score. If they disagree with that answer, it will get a negative confidence score. Over time, we will get very high confidence scores on answers we know are accurate for that particular problem, and we can eliminate “bad” answers. And because AI is actively working across EVERY problem across EVERY human, we learn at a “neural speed.” Therefore, by providing suggested answers, AI disseminates accurate information in real-time, improving human performance.

This is exactly how self-driving cars also work. For example, if you and your neighbor both have a Tesla and you happen to get into an accident, that accident is analyzed, and all other self-driving cars learn from it, helping your neighbor avoid a similar accident.

At Sutherland, we built an innovative customer experience solution based on the AI HiTL model for one of our global clients. Our client was investing more than $3B to launch a new global streaming entertainment service. The client wanted a scalable modern infrastructure that could match their rapid growth and AI-powered customer service capabilities to ensure they could deliver exceptional and differentiated global experiences to the end customers. We deployed Sutherland Connect®, our proprietary cloud-based customer engagement platform, to deliver end-to-end transformation for the client. On day 1 of go-live, we managed 1.7 Mn interactions and further generated 1000% capacity expansion within the first four weeks to meet the demand.

In a HiTL model, AI constantly learns from humans, and this knowledge is instantly shared back with humans, aiding them in their tasks. In turn, humans are not only assisted by AI but also continuously training it.

Moreover, HiTL models build a “governance gateway” for AI-generated responses. One of the key concerns around Generative AI is the risk of hallucinations, jailbreaking, and undesirable responses. With humans validating and scoring these responses, we maintain better control over acceptable outputs.

This is exactly the fundamental approach at Sutherland to solving all kinds of client problems. We bring together human expertise and artificial intelligence. In short, we do digital chemistry.

None of us are able to achieve success without some help along the way. Is there a particular person who you are grateful towards who helped get you to where you are? Can you share a story about that?

I have had many mentors, all extremely important to me. One thing I feel I have done well is to ask people I respected throughout my career for their guidance, advice, and mentorship.

Steve Jobs was quoted as saying that he had never picked up the phone to ask for help and was told no. This has been my experience as well. Whenever I reached out to someone for mentorship, I was met with openness and support. Without these mentorships, I do not feel I would have succeeded as well as I was able to through their involvement.

What are the 5 things that most excite you about the AI industry? Why?

Rather than focusing on five individual aspects, I am excited about the collective improvements across many dimensions of AI, which dramatically increase its applicability to solve numerous challenges in everyday scenarios.

For instance, everyone talks about Generative AI as if it is new. The reality is that an AI model named Eliza was generating text responses in the 1960s. In the 1970s, another AI model, AARON, was creating paintings. With the improvements in neural networks, GANS networks, transformers, and other technologies, we are obviously light years from where we were with ChatGPT generating human-like text and DALL-E creating stunning pictures.

Soon, quantum computing will lead to a new era of AI / Machine Learning.

The future promises even more groundbreaking advancements with the advent of quantum computing, heralding a new era for AI and machine learning. Therefore, it’s the broad applicability of AI that excites me, rather than any single area. Here are some examples:

• Use of computer vision to improve the detection of potential cancerous cells.
• New AI-led prediction models successfully predicted 14 earthquakes.
• Causal inference, AI is being used to understand the linkage between underlying health conditions and likely health outcomes, significantly improving preventative care measures.
• Self-driving cars autonomously preventing accidents.

These examples illustrate how AI is being integrated into various aspects of our lives, improving daily experiences and outcomes. The potential for AI to continue enhancing our world in ways we have yet to fully imagine is what excites me the most.

What are the 5 things that concern you about the AI industry? Why?

Rather than listing five individual concerns, I would like to highlight a broader issue that encompasses multiple dimensions of concern.

While the world is blinded by AI’s aggressive evolution, there is little to no discussion or governance on the impact of AI and automation. While there will be a tremendous amount of good that comes from it, there will also be massive negative consequences, whether they are planned or not.

As you know, there is an ongoing debate between prominent scientists, (personified as a debate between Elon Musk and Mark Zuckerberg,) about whether advanced AI poses an existential danger to humanity. What is your position about this?

I am not a proponent of unsupervised learning, and there are many examples of this, such as some very public self-learning chatbots that began to respond in less-than-desirable ways, so they ultimately had to be removed after much embarrassment to the company.

While the idea of a sentient AI posing an existential threat is a compelling topic for debate, my primary concern lies elsewhere. I worry more about the displacement of humans due to AI and how that will evolve. The reality is that we are seeing massive improvements in the number of areas we can automate effectively, which removes people, and there is no adequate balance to this equation.

This massive disruption to our labor force is already underway. It will have dramatic effects long before any sentient AI comes to fruition.

What can be done to prevent such concerns from materializing? And what can be done to assure the public that there is nothing to be concerned about?

There is no definitive answer for now. Companies and research organizations are focused almost exclusively on aggressively progressing AI developments, with little attention given to how we will support people impacted by AI and automation, the potential consequences of AI, or how to govern it effectively.

While many companies have implemented responsible AI practices, these often center around accurately training AI models rather than addressing potential downstream impacts.

As you know, there are not that many women in your industry. Can you advise what is needed to engage more women into the AI industry?

While there has been a small increase in women participating in STEM courses, there is still much work to be done to engage more women in the AI industry. Encouragingly, we are seeing more women attending STEM-based courses, which will contribute to advancements in AI and related fields over time.

One notable trend in AI is the emergence of more human-centric applications, such as ChatGPT or AI systems capable of creating songs and art. This shift highlights the intersection of technology and creativity, making the field more appealing to a broader range of individuals, including women.

To engage more women in the AI industry, several steps can be taken:

• Encouraging girls to pursue STEM subjects from an early age is crucial.
• Showcasing successful women in AI can inspire and motivate others to follow in their footsteps.
• Financial support in the form of scholarships and grants specifically targeted at women in STEM can help reduce barriers to entry and encourage more women to pursue careers in AI.
• AI increasingly intersects with various fields, including the arts and humanities. Promoting interdisciplinary approaches can attract a more diverse group of individuals to the AI industry, including those with interests in creativity and human-centric applications.
• Building a supportive and inclusive culture within organizations is essential.

As the way we interact with and train AI continues to evolve, I believe we will see a more balanced representation of women in the industry. By taking these proactive steps, we can create a more inclusive and diverse AI community, ultimately leading to richer and more innovative advancements.

What is your favorite “Life Lesson Quote”? Can you share a story of how that had relevance to your own life?

I don’t know if I can synthesize a critical life lesson into a single elegant point, but I learned early on that failure is just practice for success. I learned this by playing sports all my life, and I think Michael Jordan put it best: “I’ve failed over and over and over again in my life, and that is why I succeed.”

This quote resonates deeply with me because it captures the essence of resilience and the importance of perseverance. I find a common thread among people like Michael Jordan and others who achieve great feats: They never fear failure and never fear asking for help. Embracing failure as a stepping stone to success and seeking support when needed has been instrumental in my journey. It’s a lesson I carry with me and one that continues to shape my approach to challenges and opportunities.

How have you used your success to bring goodness to the world? Can you share a story?

When I was in the 4th grade, I saw my first computer program and was immediately fascinated. From that point forward, I learned everything I could about computers. I attended every computer course available and even attended the parent’s job fair, not with my father, but with his friend who was a computer programmer for Wang Computers.

This early exposure and opportunity to learn about computers shaped my passion and career in technology.

At Sutherland, I am proud to be part of a global initiative that aims to share this same opportunity with others. We have a program that provides free computer skills training courses to anyone looking to improve their digital literacy. To date, we have trained over 85,000 people across 30 countries. This initiative empowers individuals by equipping them with essential digital skills, opening doors to new opportunities and enhancing their ability to participate in the digital economy.

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. :-)

While it’s still in the early stages, at Sutherland, we are working on citizen predictive health AI solutions in partnership with several large health consortiums. This initiative aims to improve the predictability of potential health conditions and emphasize preventative health. Our goal is to shift away from the predominantly reactive healthcare system that exists today.

As we progress with this initiative, we hope to share our work and findings more broadly.

How can our readers further follow your work online?

Follow me on LinkedIn here.

To Follow Sutherland’s work, visit our website here.

This was very inspiring. Thank you so much for joining us!

About The Interviewer: David Leichner is a veteran of the Israeli high-tech industry with significant experience in the areas of cyber and security, enterprise software and communications. At Cybellum, a leading provider of Product Security Lifecycle Management, David is responsible for creating and executing the marketing strategy and managing the global marketing team that forms the foundation for Cybellum’s product and market penetration. Prior to Cybellum, David was CMO at SQream and VP Sales and Marketing at endpoint protection vendor, Cynet. David is the Chairman of the Friends of Israel and Member of the Board of Trustees of the Jerusalem Technology College. He holds a BA in Information Systems Management and an MBA in International Business from the City University of New York.