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Using "the da Vinci Method" in Scientific Discovery

Leonardo da Vinci, the original Renaissance man, has something to teach researchers about innovation, says author Michael Gelb.

Cover of the How to Think Like Leonardo da Vinci book and the Mona Lisa

This month organizers celebrated a new data repository for lung scans, a triumph of collaboration among many partners, including CSL Behring. The resource launched by the Open Source Imaging Consortium (OSIC) aims to combine big data with artificial intelligence in a way that will improve care for  patients who have rare lung diseases.

So it was a little surprising to hear Leonardo da Vinci’s name come up at an OSIC meeting. Born in 1452, the Italian artist painted the “Mona Lisa,” imagined airplanes 400 years before they flew and made intricate anatomical drawings of the human body to understand how it worked.

In describing the data repository, OSIC’s Executive Director Elizabeth Estes said this: “It’s going to look at the data from different perspectives: pulmonary, radiology and artificial intelligence. Three perspectives, like the da Vinci effect.”

That’s accurate, says Michael Gelb, author of the best-selling book, “How to Think Like Leonardo da Vinci.” Da Vinci did look at his subjects from multiple perspectives as he figured out how to paint realistic scenes and people, puzzled over the physics of flight and diagrammed the mechanics of the body, including even the inner workings of heart. He crossed disciplines and blended his interests in art, map making and engineering.

“His art was in service to his science. They weren’t separate,” said Gelb, who pored over da Vinci’s notebooks to extract principles for modern-day living, creating and innovating.

Gelb’s seven da Vincian principles – appropriately expressed in Italian – are:

Curiosità – A thirst for learning

Dimonstratzione – A commitment to testing knowledge through experience and making mistakes

Sensazione – A continual refinement of the senses

Sfumato – A willingness to embrace ambiguity

Arte/Scienza – Balancing art and science in “whole brain thinking”

Corporalità – Pursuing grace, fitness and poise

Connessione – “A recognition and appreciation for the interconnectedness of all things and phenomena. Systems thinking.”

Since the book’s launch in 1998, Gelb has been counseling business leaders and research scientists about how to apply these principles to their lives and careers. Balancing art and science is an essential da Vincian principle. Nobel-Prize winning scientists, Gelb says, are three times more likely than average to have artistic interests in addition to their research pursuits.

To work the whole brain, he encourages deep dives into comparative art, surveys of musical genres and, true to da Vinci’s Italian roots, wine tasting. But even with all these sensorial prompts, rigorously trained doctors, engineers and scientists often have difficulty tapping into creativity. It’s easy to understand why. Physicians, for instance, must protect a patient’s health and make the right calls. There’s no time for playful thoughts.

Gelb combats this by offering low-risk opportunities to be creative. For instance, he once taught 1,000 computer company employees to juggle and invited a team of scientists to write anonymous poems. These exercises teach risk-averse professionals to toggle between their creative selves, when conditions allow, and their necessarily precise, analytical selves, he said. The point is to become more aware of which situation you’re in and when to enjoy the wide freedom of creative thought.

Perhaps it’s “connessione” – the interconnectedness of things – that’s most relevant to scientists who are pursuing breakthroughs in their fields. What will happen if you combine the disciplines of pulmonology, radiology and artificial intelligence?

“This is what geniuses do that no one else does. They make connections that other people don’t see,” Gelb said.

Even artificial intelligence – with all its 21st Century potential – has a thread of connection to da Vinci, his relentless pursuit of knowledge and his stalwart belief that he could figure almost anything out.

“Everything connects to everything else,” Gelb said. “AI is just a reflection of NI – natural intelligence.”