जैसा कि हम जानते हैं, AI दुनिया को बदल रहा है - और वह भी अविश्वसनीय गति से। और भविष्य को आकार देने में कौन मदद कर रहा है? बेशक एग्लोनियन।

If it feels like the future of Artificial Intelligence (AI) is a rapidly changing landscape, that’s because the present innovations in the field of artificial intelligence are accelerating at such a blazing-fast pace that it’s tough to keep up. It seems likely that AI is going to (continue to) change the world.” Even in the 12 months since tech journalist Michael Thomas wrote these words, the pace of change has got quicker still, with governments starting to take the risk of AI seriously and chatbots going viral. And, of course, where there are significant developments, there are Aiglonians.

“Back in the 2000s, Stephen B Johnson’s book Interface Culture made the point that artisans of that decade would be software engineers and product designers,” says Narain Jashanmal (Alpina, 1997), now Vice-President of Product at streaming service MUBI. “I think he was spot on. What you can do with code or product design is as creative as what you can do with a camera, pen or paintbrush.”

Narain should know: he’s been at the cutting edge of social media since he joined Facebook, now Meta, back in 2014, progressing to become Director of Social Commerce at Reality Labs where he pioneered new shopping experiences in virtual and augmented reality (AR/VR). AI, he points out, is nothing new: its theories have been with us since the 1950s. But the rise of the internet and social media meant that, suddenly, datasets were so large that humans could no longer process them.

New tools were needed, and AI kicked into gear. But up until last year, AI and machine learning tended to stay behind the scenes – driving searches, or recommendations, or what appears at the top of your Instagram feed. But now generative AI products such as OpenAI’s ChatGPT are allowing consumers to interact directly.

How will this new-found ability affect our world in the future? Narain points out that AI is good at helping with things that humans aren’t great at. “It’s incredibly hard for a human to come up with 100 different data-informed scenarios,” he says.

“And it’s very easy for a machine to do it. But while that machine can interpret that data, it can’t interpret the outcome of that data. That’s up to us – as is how we choose to distribute the rewards of these new technologies.”

Dariane Hunt (Exeter, 1986) is Director of User Experience for Digital AI at the bank Wells Fargo, and she too is excited about the potential of AI to create better experiences. She was not interested in computers in college, she says, because she didn’t think the language she needed to learn to communicate with them was intuitive. “The biggest thing I’m excited about with AI is that we can now talk to computers using our own language. At Wells Fargo we have a big customer base and we are always trying to create designs that are optimised for the biggest number of people. But people have different ways of processing information. AI will allow us to create personalised experiences – liquid UI – that will adapt and adjust to every individual according to their needs, instead of us having to adapt to the technology.”

Dariane started her career as a digital designer, learning on the job in the 1990s, when broadband and interactive TV were going to be the next big things. After a detour to work in a rehabilitation sanctuary for rescued orangutans in Borneo – “I’d always wanted to work with great apes, and it was something I just had to do before I settled down!” she says – she took a deep dive into tech with a Master’s in Interactive Telecommunications at New York University. She found herself in what was then a completely new field: user experience and information architecture.

She first encountered AI at Bank of America, when asked to develop an Alexa skill for the bank. In the end, the difficulties around data security were limiting and they realised the bank had the resources and capabilities to develop it in house. “We started leveraging AI, specifically natural language processing, to create a multi-modal experience in our mobile app. Essentially, it’s allowing computers to understand what people are asking in their own words, whether through voice or text.” Erica, one of the first AI-powered banking assistants, was launched in 2018. Since then, it has helped more than 37 million clients in more than 1.5 billion interactions, allowing customers to gain insights into their spending habits. Hunt is now working on a similar tool at Wells Fargo.

So, what does the future hold for those who want to work in this field? As a Senior Software Engineer in the Vision Products Group at Apple, Noah Gamboa (La Baita, 2014) is well placed to know. His love of technology started in his computer science class at Aiglon, and grew at Stanford University, where he gained a Bachelor of Science and a Master of Science in Electrical Engineering. At Stanford, he became interested in AI, working with lung cancer researchers aiming to build AI models that can analyse a patient’s CT scan and predict their survival prognosis.

After graduation, he interned at Apple, working on Siri, later joining the company in his current role. “I’m so excited about spatial computing, because you get to see the world for what it could be, not like it is,” he says. “I’m currently using Apple Vision Pro and it’s just seamless, allowing me to use spatial computing in an entirely new way.”

Noah believes that the best way to think about building a career in this space is to just start tinkering. “If you see something that you find interesting, and you think it could do this other thing, try and make it do that other thing. Or if you’ve got a puzzle that you’re not sure how to solve, but you like going in and fixing it, that’s a good sign that new technology – whether it’s AI, AR, VR or something else on the cutting edge – is something for you. There’s never a day where the problem is the same.”

Dariane says we will always need people who think creatively and strategically and can synthesise all that information into something that’s cohesive. Generative AI, she points out, doesn’t think. “It’s a predictive technology; a smart algorithm that can assess the most likely response to a question. But it’s not really understanding. You are always going to need humans who can think critically and who can synthesise and solve problems in ways that are much more intuitive than any type of machine algorithm.”

And Narain agrees that this kind of adaptability and ingenuity will be hugely valuable as we enter an AI-powered future. “It’s easy to say that you’re intimidated by a piece of technology, especially as the technology you’re using is more abstract,” he says. “But trying to understand doesn’t mean you have to become an expert in machine learning. It’s about curiosity, asking questions, listening, getting to the heart of something. Curiosity is the first thing that I would look to. Not just pure intellectual curiosity, but a curiosity about how things work. And leaning into the things that make us uniquely human.”