Digital twins of organs can help us solve big challenges: TCS futurist

What exactly are digital bio-twins?

If we can digitally mimic organs such as the heart, colon, skin, and nose, and allow for simulation and some level of predictability, we will be able to solve big challenges for health and wellness sector. Digital bio-twins can complement wearables, and the data flowing through them can help us better understand how the body reacts and responds to activities like running as in Linden’s case.

How are digital twins used across sectors?

A digital twin can help us become better prepared for disasters, whether a pandemic or hurricane or any other extreme event. There are people even working on a digital twin of the Earth (to simulate, among other things, the atmosphere, ocean, ice and land, and provide forecasts of floods, droughts, and fires). A digital twin in the education sector could help doctors train more efficiently for surgeries without the risks associated with surgeries. Children can be simulated through a digital twin from early childhood to the point where that digital twin knows a lot about that individual and helps nurture them through their formative years. To become more energy-efficient, we can simulate buildings, and cars, among others.

Are we seeing the convergence of digital twins with AI, and the Metaverse?

Yes. These building blocks, as I like to call them, are accelerating the pace of innovation because they can converge in many ways. Here’s an example: I showed a video of a mother being reacquainted with her dead 8- year-old daughter virtually. The simulation is very real and emotional. Virtual reality combined with AI was leveraged to simulate her daughter, and haptic gloves allowed her (the mother) to touch her daughter in some sense. I asked the audience: If you could reconnect with a dead relative or friend, will you? Many people will say ‘No’, but it’s this convergence of these building blocks that is enabling societal changes. Over the next 10 years, I expect to more such scenarios emerging.

In this context, how is generative AI changing the face of AI?

Generative AI is an application of the broader AI field. Anybody who explored ChatGPT or other large language models (LLMs) would be fascinated by their potential. LLMs, for instance, could be a broker of standards across health and wellness industry by converting any one standard to another, creating a common language at some level in an industry with various different standards and languages —just think about the possibility of a (generative AI) model that may reduce administrative burden by filling out a claim as opposed to an individual doing so. Many such applications will play out in various industries over the next couple of years.

What are the challenges in using generative AI models?

In most environments, you’re dealing with data siloed and spread across business (units), and must be pulled together, and later merged with third-party and other kinds of data. Training data requires a lot of compute capacity, which is a challenge. You also have issues like a (short) supply of AI chips.

Will advances in quantum computing speed up the pace of generative AI adoption?

We need a new compute paradigm to realize the broader innovations enabled by things like AI. The combination of quantum computing and AI, if it comes to pass, will be world altering for several reasons. Quantum computing is being used today, but there are reliability and scalability issues. It’s just a function of when we resolve the things, but it’s hard to put a timeline to it. We’re seeing breakthroughs every day on a scale no one would have imagined even five years ago.

What about the debate around AGI becoming a reality, and outsmarting and overpowering humans?

There are references to existential threats of AI and talks of AI becoming a conscious entity, but it doesn’t help the conversation a whole lot. The reason is even with the narrow AI we have today, you can solve major challenges for society. If you look at it just from a positive lens, AI has the potential to solve grand challenges like climate change, cancer at some level, Alzheimer’s, Parkinson’s, etc., if society manages it well.

I understand the premise of the open letter (‘Why Generative AI is a divided house’) that was released when ChatGPT got launched. But I don’t believe that it’s in society’s best interest to slow this process down. Instead, it’s in our best interest to manage it. It’s always been the case where we’ve had technologies like this, such as nuclear weapons.

But AI experts also argue that while nuclear weapons cannot replicate themselves, AGI models will have the potential to weaponise themselves if they become sentient, especially those built with self-supervised algorithms…

This is a great point which comes up a lot. My comparison wasn’t really about AI and nuclear weapons. It was comparing the need to manage general purpose technology like AI. I’ve talked about the positive potential we have as a society to advance human development with AI. The pessimist in me looks at the global will to manage three big things that converge to change the world – AI, quantum computing, and synthetic biology.

So, let’s talk more about the global will to control synthetic biology. What does it entail?

Synthetic biology will give us the ability to manipulate and create life. At the molecular level, synthetic biology and genetics are allowing us to modify foods, modify animals, and eventually people. Again, it’s a dual path. It gives us the ability to deal with a genetic deformity early, and even before it happens. What parent would not want to do that if they knew that their child might be born with some kind of genetic defect? Of course, there always a chaotic conversation around the benefits and the downside of those kinds of things.

Such as the controversy around designer babies…

Yes.

As AI becomes more powerful, we are also seeing humans embedding AI chips and using bionics to become stronger and smarter. What are your thoughts on this subject?

I find history very instructive when exploring the future. Consider what it means to be human. We’ve changed twice from being hunter gatherers to the agricultural era, and then from agriculture to industrial. The third change in terms of what it means to be human could be, as you pointed out, the actual merging of machines with humans. Ultimately, at some point, we will have bionic limbs or embedded chips or other forms of machines that we merge with – all of which will fundamentally alter what it means to be human, and that’s an open question. There’s a lot of polarized debate on the topic right now. But it is a potential path, and we must acknowledge that possibility and prepare for it.

As a futurist, what do you advise thought leaders and CXOs who are trying to come to terms with the accelerated pace of technological progress?

My advice goes back to my favourite quote from Alvin Toffler: “The illiterate of the twenty-first century will not be those who can’t read and write, but those who cannot learn, relearn, and unlearn." ‘Unlearn’ is the biggest point of that quote. So, my key advice is to tell them to let go of some of their core beliefs and think differently about how this era is emerging and how they might manage in the current era that looks very different.