You, as a Fellow, analyze causal relations, extract latent features, amplify reasonings, derive inferences, formulate knowledge representations, recommend options and choice-sets; create prototypes for digital products, services and functions; embed forecasts, optimizations, allocations and assignments; and build them with machine learning (ML), artificial intelligence (AI), data engineering, physics-inspired statistics and advanced computing technologies. You re-discover your mathematical, analytical and computing skills requiring design innovations and improve quality of human decisions.

Most “brand” elite schools probably would claim the same.

So, here are three good reasons to join the program:

Or, consider this: All our faculty members have either a full-time job in a company, in entrepreneurial venture or on sabbatical from their long-distinguished computing career. They’re all practitioners. And, almost all of them live through the consequences of what they practice, guide and advocate – “data-driven (or evidence-based) decisions”.

And, we don’t have long list of Nobel Laureates or Alan Turing Award winners.

But those aren’t the real reasons you join our program.

When you focus on computing technologies only with the purpose of “serial venture” or an award, you form a very “narrow” and myopic view of the world. When you focus on the design and the scientific study of design, with an honest and authentic intent to collaborate as a team and serve mutual interests, that’s when the creative magic happens. You effect this alchemy. Your “broader” vision that ‘builds up ideas’ – advance humans with more knowledge, productive, a lot more enjoyable experiences and more rewarding.

Giving high potency to an insight, founded in numbers, is an intensely creative act: it requires a massive injection of imagination. As with any other creative act, it also demands an understanding of what is already in the receiver’s mind; and just as importantly, what is not already in the receiver’s mind. That’s when you call on words – provocative, allegorical words – to let in fresh air; to liberate the insight and give it immediate, self-evident potency. They are forged through tens of thousands of decisions, often made by dozens of people in a team.

That contains bold and risky hypotheses. Sometimes we are drawn to a type of analytical work or to an industry that has aspects that repel us.  A car designer, for example, loves the speed and beauty of the machines he or she creates but also struggles with concerns about how auto emissions are affecting the environment. Yet no matter how we rail against the status quo, faced with a choice between our values and our jobs, most of us are reluctant to take action in the workplace. After all, sticking one’s neck out only invites the ax. And, to generate hypotheses you speculate: you need progress from the known to the unknown. But you cannot paint the future in the colors of the past. Other people’s imaginations are engaged, excited, signed on as accomplices. And the choice of the language you use is not arbitrary and inconsequential; for an insight to have real potency, the language in which it is couched is at least as important as the inner truth itself. For an insight to have real potency, literal accuracy is less important than its power to evoke.

This is more true, when you build a digital initiative, automation with machine learning, or designing system with sciences. You have a higher purpose in mind. You learn to challenge conventional wisdom, because there’s no conventional wisdom. Everything and every idea are up for challenge. And, you ensure they are challenged almost regularly.  You build and present your capabilities, capacities and skills to them more conservatively, even those you observe – patterns across nature’s infinite beauties and depth of human experiences. You fail repeatedly in doing so.

Failing gives you the room to experiment and the ability to innovate. And, success forces you to encounter with the devil. You want your customers, large and ventures, to be on the right side of things when your great idea comes along. You use them more often, consciously and deliberately, to cast the same spell on recalcitrant data.

When you design with that mindset, or should we say “digital mindset”, you change how you frame everything that you do. Words get carved in stone – “Knowing is not enough; we must apply. Being willing is not enough; we must do” – become a process of changing how we all think – how we think about collaboration, how we think about computation, and how we think about change. And, you end up not worrying about how humans with digital skills will replace humans without digital skills. Or, will machines replace us; will automation be the end of your career; is career-growth going to be tenure, or seniority, or rank; who has a digital mindset, and who doesn’t.

You view a world full of creative people who are constantly developing new possibilities for themselves and their communities.

Because, Great Minds Lead The Way.