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Korean Scientists Find a Way to Calculate Creativity
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Korean Scientists Find a Way to Calculate Creativity
Based on their calculations, Beethoven is the most influential composer in the history of classical music
PHOTOGRAPH: Unsplash
PHOTOGRAPH: Unsplash

By Jenny Lee WIRED Korea

Science, as one explains, is like wandering through a jungle that is uncharted, unexplored. It is all about explaining how nature works and why it is the way it is by drawing on past knowledge, present observations and future expectations. And the answers science brought to light thus far have not only resulted in a greater understanding of life but also led to medical innovations, putting men on the moon and pushing technology forward.

Uncovering underlying truths has been the aspiration of many, if not all, scientists including Park Juyong and his team at Korea Advanced Institute of Science and Technology (KAIST). A theoretical physicist, Park has a keen interest in making intangible and impalpable things understandable.

“Abstractions are real,” says the professor at KAIST’s Graduate School of Culture Technology. “For example, we know that human emotions exist though they are hidden from human perception.”

While manifesting abstract concepts in something that is concrete, observable and testable is no easy feat, Park says three years of their effort have culminated in the development of a methodology of mathematically expressing and precisely calculating creativity.

To try and quantify qualities of creative works, large-scale data and a mathematical framework were tapped by the team, which managed to analyze about 900 classical piano works by 19 composers from the common practice period spanning the Baroque (1700–1750), Classical (1750–1820), Classical-to-Romantic Transition (1800–1820), and Romantic (1820–1910) periods.

Each composition was segmented by a computer model into “codewords,” which are composed of simultaneously played notes as well as their octaves. Sequences of codewords were then compared between musical pieces.

Park says creativity can be broken into two componential factors, ‘novelty’ and ‘influence’. Therefore, how different these works were from past works and from the known characteristics of music at a given point in history were first examined, which was followed by the assessment of their influence on future creations or how much they had been referenced in the future.

Park’s team also contemplated on other important questions: How do the novelty and influence change over time? Does novelty lead to influence and later recognition? How do these characterize the evolution patterns of a creative field?

A number of interesting findings emerged from his research. Of the 19 composers, Handel was most influential during the Baroque period, Haydn and Mozart during the Classical period and Beethoven during the Romantic period. No composer trumped Beethoven, who died in 1827, on the influence scale up until 1900, the endpoint of the data set.

Perhaps the most fascinating is this: the composer whose works had the most novelty was Rachmaninoff.

“When I published this study in January, a few professors reached out to me to rebut this finding that Rachmaninoff was the most innovative composer, claiming his works (produced in the late Romantic period) had many shades of early romantic music,” Park says. “But based on our calculations, Rachmaninoff used a combination of notes that had not been used before and created a classic feel.”

“Our model in a sense opens up new opportunities to re-assess creative works whose assessment many think was completed a long time ago,” Park adds.

With creativity emerging as a marketable professional skill across many industries, the importance of quantifying creativity has been growing. Many attempts have been made to bring forth dependable instruments to measure it, but many of them, if not all, did not fare well due to limitations derived from the ambiguity surrounding the definition of creativity. They were considered “limited in scope,” failing to wholly encompass what is meant by creativity.

Park’s approach seems to suffer from the same shortcoming, as creativity may include a whole lot more than just novelty and influence – like the level of technical skill displayed, the pleasure afforded to audiences by the creative product and the level of emotion conveyed.

Also, his model does not yet take into account other aspects of music such as structure, tempo, instrumentation, something that Park’s team admitted in the paper published in the open access journal EPJ Data Science.

“Our research marks an advancement in that it went beyond the level of collecting statistics and surveys,” Park says. “We have developed a framework based on scientific methodologies.”

Park believes the ability to quantify the idea of creativity in music can yield benefits, potentially help musicians to produce something of the sort of soaring quality, of greater value.

“Knowing what is more creative, what is more innovative, and what is more influential will help artists produce better works,” Park says.

But it is not certain whether his computer model can measure creativity in other forms of art or even activity not associated with art. Park and his team have so far made no such attempt.
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