Creative Intelligence

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Synopsis

Rethinking the creative process.

Albert Camus once said that “true art is characterized by an irresistible urge in the creative artist.”  Henry Ward Beecher similarly wrote that “Every artist dips his brush in his own soul, and paints his own nature into his pictures.”

You don’t have to look far to find quotes like these, because art is something we consider intensely human. Art and the artist are so thoroughly intertwined that we can’t bear to think of one without the other.

For better or worse, we’re going to have to rethink this comfortable little notion.  Machine intelligence is advancing to the point where algorithms have begun to invade the world of culture and the aesthetic.  From recommendations to evaluation to the production of art itself, computers are becoming a force to be reckoned with in the creative realm.

The Search for Creative Assets

When you make a TV ad in Ukraine (as I have), you generally do it on a tight budget. You certainly don’t have the money to buy the rights to the latest hit by a big pop star or a vintage Beatles classic.  There are some local musicians who can create something for you, but thats a pretty involved effort and, to be frank, the quality isn’t worth it.

I found a good solution with DeWolfe Music, which is an online database that gives you access to thousands of songs from unknown composers and performers.  You can search by music genre, keyword (e.g. an artist that you’re trying to emulate) and tempo, quickly find what you need and license the music for a small fee.

Newer services, such as Pandora and Spotify, deploy a similar idea in order to build custom radio stations.  Rather than a human programming director choosing your music, you can just give the software some clues about what you might want to listen to and it designs a selection from a nearly infinite database to cater to your mood and preference.

This is all done through the use of complex mathematical techniques, such as Bayesian classifiers and Gaussian copulas, that recognize similarities between data sets.  So just like a sommelier might ask you what wine you typically like and offer you something similar,recommendation algorithms can do the same with music, films and even art.

Cultivating Creativity

Being able to search and find elements of art and culture is one thing, but can computers appreciate quality?

Mike McCready has shown that they can.  His company, Music X-Ray, offers a service where composers can upload their music to evaluate its hit potential and it has been shown, in many cases, to outperform professional music executives (reportedly predicting the success of Norah Jones when many industry experts were skeptical).

As crazy as the idea sounds, you’ve probably recently listened to many songs identified by the service.  Every major label now uses some version of it and they’re not alone.  Movie studios employ a similar service, called Epagogix to tell them which scripts are likely to become box office hits.

And it doesn’t stop there.  Music scholar and composer David Cope has built algorithms which create music that has drawn critical acclaim.  In fact, even music experts can’t tell the difference.  When Cope’s computer generated music was played along with a Bach piece and another original composition, they couldn’t correctly identify which was which.

What is Creativity?

As impressive as all of this is, it creates a particularly thorny, visceral problem:  If creativity can be reduced to an algorithm, doesn’t it lose its soul?

While I admit, I find something troubling in all of this as well, after thinking it through I have come to believe that artificial intelligence actually has the potential to help us appreciate creativity even more, in much the same way as Richard Feynman explains how understanding the inner workings of a flower help him acknowledge its beauty.

Our brains, in many ways, are inferior to computers.  They transmit information at the relatively feeble rate of 200 mph, vs the speed of light for computer chips.  They get tired, need nourishment, age, forget things and don’t interface with other databases of information effectively.  Objectively speaking, they are slow, inefficient and prone to error.

Their saving grace is that they are a massively parallel complex network.  They are made up of 100 billion neurons and each one can connect to any other.  These interfaces, calledsynapses, optimize themselves as they strengthen and decay with use and link to the outside world through our five senses of sight, touch, taste, hearing and smell.

While computers have relatively few active pathways at work at any given time, we have millions, giving rise to infinite permutations of thoughts, feelings, bodily functions and sensory inputs.  Perhaps not surprisingly, these hierarchies get tangled, resulting instrange loops that manifest themselves in what we have come to know as original creativity.

As Douglas Hofstadter said, “In the end, we self-perceiving, self-inventing, locked-in mirages are little miracles of self-reference.”

Rethinking the Creative Process

The creative process has always been cloaked in mystery and artistic types tend to be resistant to formality.  Nevertheless, professional individuals and organizations strive to develop an effective framework to enhance the productivity and quality of their work and creativity researchers have been able to identify some basic principles of creativity.

However, in light of the breakthroughs in machine creativity, I think that we need to revisit past thinking about creativity and identify three major processes:

Forming Intent: Every creative endeavor has its purpose.  Designers work on a brief that someone else creates while true artists form their own purpose, but in either case, the final result is, in essence, a solution to a particular problem.

For example, my purpose in creating ads was to sell a product, while Picasso’s purpose in creating cubism was to establish a fundamentally different way at looking at the world. In the final analysis, both are judged by the significance and the degree to which the original intent was fulfilled.

Searching the Domain:  As Howard Gardner explained in his highly regarded study,Creating Minds, great creativity requires a thorough knowledge of the domain.  Picasso’s cubism, for example, was inspired by his encounter with obscure African art.  The larger your database of experience, the greater your ability to create.

Computers obviously far outperform humans in this regard.  They have practically limitless memory and their vast computational power enables them to search incredibly quickly and accurately.

Tangling Hierarchies:  As I’ve written before, great breakthroughs come fromsynthesizing across domains, whether that be Picasso’s blending of European and African art or Rock and Roll’s unique fusion of various american music styles.  It is when two or more ideas collide in a meaningful way that people find inspiration and creative flow.

It is this last trick, that of emulating the strange loops in our mind, which computers have recently learned how to do, that has given rise to machine creativity.  David Cope, for example, found that his computer generated music was dull and lifeless until he injected an element of randomness into his algorithms.

Flying By Wire

Pilots don’t really fly planes anymore as much as they direct them.  These days, their controls and instruments don’t actually connect to the plane’s mechanism, but to computers which translate their intent into meaningful action.  In doing so, they make flying far safer and more efficient.

This is known as flying by wire and we don’t see anything threatening or strange about it. While at first it may seem to be a bit more disconcerting when computers start navigating the realm of abstract thought rather than the mechanics of aviation, it shouldn’t be, any more than driving a car should affect our feelings about walking.

So what makes us creative?  Our ability to form our own intent.  It is only through creating a purpose that is uniquely our own that we can fully embody the human spirit.

This post originally appeared at DigitalTonto

Tags: artificial intelligence, creativity, creativity studies, emergence, greg satell, machine intelligence

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