'I see huge potential for AI as an amplifier': Vishal Sikka

Vishal Sikka

Two years after his surprise exit as Infosys CEO, Vishal Sikka launched his new venture on artificial intelligence (AI), Vianai, this September. In the last two years, he held courses on AI—in which he has a PhD from Stanford University—in the US and China. In an email interview with Forbes India, Sikka, 52, explains the philosophy and focus of his new company, and the positives and negatives of AI. Edited excerpts:

Q. What have you been doing since leaving Infosys?
I had just turned 50 after I left Infosys in August 2017. I was thinking about the next 25 years and looked back at the past 25 (1992-1993). Google wasn’t around then, Facebook didn’t exist and neither did Uber, Tesla and Airbnb. Steve Jobs wasn’t at Apple. Amazon wasn’t there either or had barely started. I thought the new things that will define the next 25 years aren’t around now.

I have always been passionate about the idea of technology being a human amplifier, something that improves our ability and makes us see more, do more, and be more. At a time when you hear so much about technology’s negative effects and unprecedented ability to scale, and to propagate things in a negative way, why can’t we build technology that improves us? It was time to go back to the drawing board. [American theoretical physicist] Richard Feynman used to say that the best way to learn is to teach; so I taught two classes last year, one in California and one in China. I also identified issues, did some prototypes, got funding and recently launched Vianai using powerful techniques to build a new platform and bring it to life.

Q. Is there a story behind the name Vianai?
In Bali, the firstborn child carries the name Vian. The word Vian—the proper name Vivian comes from it—also means full of life. It is a beautiful word for us which means full of life and intelligence.

Q. When did you officially found Vianai?
We founded the company earlier this year and launched officially on September 12. We have an incredible team of over 30 people, including employees, consultants, contractors and advisors. 

Q. Where is AI adoption at among the kind of large enterprises that would be your customers or potential clients?
While there have been some impressive recent advancements in AI, they have been pretty narrow in their focus. There are still many issues and questions that are yet to be resolved. The hype around the field is high, but we believe it is still in its infancy, and even more so in the enterprise context. There is a huge market need related to end-to-end design, development and delivery of solutions in enterprise AI, and an opportunity for many companies, especially for startups like ours, which have deep experience and expertise in AI, enterprise technologies, design, engineering and technology services in general, to make a mark in this space.

Q. AI brings with it the concern of job losses. Is it justified? What are the consequences of large-scale AI adoption?
I see a huge potential for AI as an amplifier, as something that augments human capability, not something that replaces people. People who are amplified in their capability by advanced technology can solve some of the world’s greatest challenges, from climate change to cancer. Perhaps, it is a good thing to let machines do some of the most tedious, hazardous, mundane and automatable tasks, and free people to do tasks that require higher levels of thinking, innovation and collaboration: Tasks requiring advanced reasoning, imagination and creativity.

Q. What are the kind of problems that Vianai is working on?
We’ve worked with one of the world’s largest banks on identifying failures in certain transactions—which have values of tens of billions of dollars a day—that go through their systems. If you are a manufacturing company, even if you make-to-order, the issue of working capital is fundamental to your operational and financial efficiency. In companies with large numbers of physical assets, this directly impacts their bottom line and stock price. So, working capital management using AI is one of the areas we are working on.

As one of our client executives said, “AI and machine learning (ML) aren’t magic… they’re complex and sophisticated math on data.” That’s where Vianai was able to do the problem finding, and then ‘do the math’ with AI’s help.

Q. Who are your investors?
We have raised a seed round of $50 million. We are not disclosing the names of our investors yet.

Q. Elon Musk has said AI is “a fundamental existential risk for human civilisation”. Peter Thiel and you believe it will amplify human creativity. What concerns Musk, according to you, and why aren’t you worried?

I believe these statements or positions are contradictory; what is missing from them is our ability to influence the outcome. It depends on how we, as individuals and as a collective, choose to proceed, to build AI systems that are transparent, easy to understand, built using tools that can be learnt by anyone.

I am an optimist when it comes to technology and humanity. I take the optimist’s view that, ultimately, we will take this field with amazing progressive (and also destructive) potential, and find a way to overcome the negative impact, and amplify the positive impact.

Q. Where is AI at today? How far away are we from it?
AI means a lot of things to a lot of people. My former professor at Stanford and father of AI, John McCarthy, defined it as “the science of making machines do those things that would be considered intelligent if they were done by people”, which to this day is a sound and solid definition.

Today, we aren’t anywhere close to that definition, but we are making progress, and also learning from AI failures (and there are plenty). I believe that artificial general intelligence is a long way off—decades or more—and the approach that many people are taking to attain it, including some of the most prominent and well-funded, is fundamentally flawed.

Q. You said in a recent interview that “there was a tremendous weakness in the current state of AI”. What is the weakness and what can be done better?
There are just as many stories of the failures of AI as there are of impressive achievements. Take for example the fatal accidents attributed to autonomous vehicles, the use of AI-based voice processing agents to perpetrate fraud, the ability to deliberately confuse AI and influence results by introducing small distortions into inputs.

The existence of these weaknesses and their inherent nature, have been known and written about for decades. They were just being ignored in the mad rush to build larger and larger networks, throw more and more data, build increasingly opaque architectures… the massive marketing push on AutoML (which is the wrong direction to take), etc.

The situation in the enterprise AI market is even dire, since it is compounded by fragmentation, asymmetry and a tremendous gap in required skills and talent.

We can do better, and we are doing better. We are looking at bringing to the market an approach that results in a better end-to-end design and development experience, which is built ground up to support exploration and explainability, and is augmented with access to the best learning and education resources. It has the ability to transform the state of enterprise AI, and also bring the opportunities created by this new field to millions of people who would otherwise be denied the benefits.

Q. What do you mean when you talk about building systems that are easily explorable and transparent? How will AI make a difference here?
We believe in an approach that combines AI technology with the practice of design thinking. What this means is that “problem finding” is just as important as “problem solving”.

Exploration refers to the ability of individuals, teams and organisations to learn by doing. By reducing the cost (both time and money) of trial-and-error experimentation, you can fundamentally alter the way in which people use technology. Think of how much the field of photography has changed from the era of film rolls and chemical processing. By reducing the time of cost of exploration and experimentation, the purpose of photography has gone from one of archiving memories to supporting everyday communication. This is similar to what will happen when you have explorable AI.

Transparency or explainability refers to the ability of AI to explain the reasons for its results or predictions. Most people (and businesses) are not satisfied with open-ended marching orders. They ask ‘why’—why should we buy more raw material, why should we stop this transaction, why should we hire this person, why should we issue this warning, etc. If an AI-based system cannot answer these questions (with something better than “because the AI Gods say so…”), it becomes worthless in many business scenarios. There may also be statutory or regulatory limits to using AI which are not explainable.

Q. At one of Infosys’s conferences you spoke about the importance of problem finding. What bearing does this have on Vianai?
An emphasis on good problem finding (as opposed to just jumping into problem solving without asking “why” this is a good problem to solve) is a fundamental tenet of design thinking. At Vianai, we bring design thinking principles and behaviours into every single project that we do. We are always thinking of desirability (how does this solution benefit the end-user, why will they adopt it?), feasibility (can this solution be delivered using the state-of-the-art in technology, or is the technology itself subject to limits), and viability (what is the business or commercial value of solving this problem?). We bring empathy, research, data synthesis, design, iteration and experimentation into everything. It is just the way we work—it is part of our DNA. We apply it equally for tackling issues internally or for our customers.

Q. What are your goals/targets for the next two years?
Beyond financial success for the company, we want to make sure that we measure the impact that we have, both in terms of the number of people whose lives we impact by the work that we do and by working on important problems of our time. Personally, I am interested in making a difference on this front in India, the country of my birth, where AI can either be a vast disruptor or an equally vast opportunity, over the next few decades.

Q. In 10-15 years, where would you like to see Vianai?
I don’t believe in forecasting that far ahead; the world changes more quickly than we realise, and nobody can know what the priorities will be even 3-5 years from now, let alone 10-15 years hence. But my hope for the company is that it will always be at the forefront of technology and business, it will champion a culture of inclusivity, progressiveness and compassion, and remain relevant and focussed on making a difference to the lives of millions, probably billions, of people.

Q. Anything that stands out about Vianai’s work and AI in particular?
There is a mystique associated with AI. The reality is that these are techniques, techniques that we can learn and use to improve things around us, and also to improve ourselves. I would love to see tens of millions of people be able to build intelligent systems, and billions be able to bring basic intelligence into anything that they do. That is not hard. We can do that.