Richard Bright: Your forthcoming book explores the subject of creativity. It is a vast subject. What approach are you taking?
Arthur I Miller: It’s an understatement that creativity is a vast subject. It’s become an industry. Bookstore shelves groan under the weight of books claiming that anyone can become a genius if you work hard enough. My book is not of that sort.
We can improve our creativity only up to a point by hard work but never attain the stratospheric heights of a Bach, Shakespeare, Mozart, Beethoven, Ida Lovelace, Einstein, Picasso, Virginia Wolf, Bill Gates, Steve Jobs, Elon Musk and so on. It is not an even sea. Some people are born much smarter than others.
We call them geniuses. They radically alter our view of the world about us. Their extraordinary creative powers set them aside from most others and cannot be attributed to sheer hard work. Their products are beacons that define the high road of civilisation. We can learn and be inspired by studying their lives and the way they think.
I have always believed that creativity can be unravelled. One strategy I have taken is to use information from case studies of highly creative individuals as grist for the mill of cognitive science and theories of psychology. Then I explore how the results can be generalised. In my forthcoming book I discuss this with focus on the 21st century and beyond where the very notion of creativity is being redefined in this age of machines and so we will have to re-think what we mean by thinking.
After all, are we not merging with machines? Already we have mechanical hips, knees and organs. A chip in our heads capable of communicating with our brains is already a reality. Around the corner awaits brain-boosting technology that can be plugged directly into our neurocircuitry, analogous to how cochlear implants connect to auditory nerves to aid the hearing impaired. Now we will have access to all knowledge instantly. We will be computer like and then be the machines themselves. Creativity will have no bounds.
We are entering an age where the notion of what it means to be a human being will be redefined.
These are among the issues I grapple with in my forthcoming book.
RB: Can creativity be defined and, if so, how would you define what creativity is?
AM: Yes. I define creativity as the production of new knowledge from already existing knowledge. Creativity is essentially problem solving. Not very romantic but what else can it be? Information enters our brain and knowledge emerges. What happens in between is the $64,000 question.
RB: Creativity can occur in many ways. Can you give some examples of different ways it has, and can, occur in the arts and the sciences?
AM: Among what I call conditions for creativity are:-
- The ability to notice connections between disciplines or concepts that, at first sight, seem unconnected;
- Unconscious thought;
- Problem discovery.
In line with the theme of this issue of Interalia I’ll begin with the power of metaphors.
A metaphor is a means for explaining something less well known in terms of something that is better known. It enables scientists to begin to understand poorly known phenomena in terms of better understood phenomena.
A wonderful example is the great Danish physicist Niels Bohr’s 1913 theory of the atom which is based on the metaphor:
The atom acts as if it were a miniscule solar system.
The instrument of the metaphor – as if – enabled Bohr to formulate a theory of the poorly-understood atom in terms of the better understood mechanics of solar systems suitably modified for the atomic world with Max Planck’s quantum theory. This visual metaphor permitted Bohr to visualise atoms as miniscule solar systems. Visual imagery has always been a powerful tool in scientific research. Bohr’s theory had about ten years of stunning success before it succumbed to more precise experimental data. He responded with a version based on another metaphor in which the atom had no visual image. It would spark Werner Heisenberg’s discovery, in 1925, of the modern atomic physics, quantum mechanics.
Now to someone’s ability to discern connections among disciplines or concepts that, at first sight, seem unconnected. This hallmark of high creativity, of genius, cannot be taught.
A prime example is Einstein’s discovery of relativity in 1905. Of great importance to him was a connection he realised between the theory of heat, thermodynamics, and objects moving in space and time. What on earth could this be? Well, it was that the theory of thermodynamics is based on statements that must be accepted as true without theoretical or experimental proof. Scientists call these sort of scientific statements axioms. You don’t question them. You accept them and see what follows. The first axiom of thermodynamics states that energy must be conserved in any process. This is a law so basic that without it science would be unthinkable.
Einstein based his relativity theory on two axioms. One of them asserts that the speed of light is the same for all observers regardless of their relative motion. It was at odds with the physics of 1905 where it was valid only in certain cases. From this he deduced amazing consequences such as the relativity of time.
Then there is Pablo Picasso’s realisation of the connection of art with mathematics, science and technology. This enabled him to go beyond the styles of his day as well as probing worlds beyond our perceptions, as do scientists.
In a broader sense all this means that highly creative work involves thinking outside one’s discipline.
Another important metaphor for our age of information is:-
The mind acts as if it were an information processing system. This cornerstone of cognitive science enables scientists to explore the human mind using as a guideline how a computer works. So, in analogy with a machine’s architecture made of built in hardware for storing, retrieving and altering data, we speak of the mind’s ‘cognitive functional architecture’ made up of innate or built-in structures that act on input data in order to, for example, solve problems. In this way scientists have reached a deeper understanding of how we reason both logically and with images. Reasoning, that is, problem solving, is the essence of creativity.
Stunningly the information processing metaphor is beginning to cross the line into physical reality because scientists have shown that silicon-based artificial neurons can communicate with real neurons. This is evidence for the neural code being a computational code. We are more machine-like than meets the eye.
Unconscious thought is an essential part of creativity. It is best described within the four-stage model of discovery – conscious thought, unconscious thought, illumination and verification. I have found that this is useful when supplemented with cognitive science and theories of psychology. The four-stage model goes back at least to the first decade of the 20th century when the great French polymath Henri Poincaré wrote about the nature of creativity.
Working consciously on a problem often leads to an impasse. The experienced researcher will put the problem aside and cease conscious work. But the passionate intense desire to solve a problem keeps it alive in the unconscious where it can be turned over in ways not possible in conscious thought with its barriers and inhibitions. In the unconscious additional facts can be taken from long-term memory and connections drawn between apparently unconnected disciplines. In this way an illumination can occur – the solution to the problem – which bubbles up into consciousness and can then be verified.
The vital parts of this model – unconscious thought and illumination – take place in the theatre of the unconscious where the information processing metaphor comes into play. This model underscores that there is no creation out of nothing, no ‘Aha’ experiences.
Examples abound: Poincaré, himself, in 1908, gave a detailed discussion of a major discovery he made in mathematics. Then there are Einstein’s and Picasso’s realisations of connections between disciplines. They emerged after intense work on the problems they grappled with. And we must not forget Steve Jobs’ struggle to come up with a design for a case for the Apple II. One day, while wandering around the appliance section in Macy’s, he was struck by the one-piece moulded plastic case for Cuisinart food processors. That was it.
And then there is problem discovery. This hallmark of genius also cannot be taught. It is an inborn talent. At any time the vast majority of scientists in any field of study work on the theory in vogue, making it better, testing it and so on. Similarly many artists ply the style in vogue. Every now and then someone comes along and says, “You’re all wasting your time. You’re working on the wrong problem.”
Einstein did this in 1905 when scientists working on fundamentals were seeking to understand the dynamics of the electron. He alone realised that the physics of 1905 was not up to the task. No one listened. Besides the radical nature of the proposal, Einstein was a complete unknown. He was a patent clerk third class in the Swiss Federal Patent Office in Berne, an intellectual backwater. When his relativity paper received any compliments at all it was usually for the wrong reasons. It would not be until 1911 that scientists agreed that Einstein had done something radically different regarding space and time. Einstein remained in the Patent Office until 1909. That 1905 was his anus mirabilis was in retrospect.
Picasso’s Les Demoiselles d’Avignon broke sharply with the art of his day which he believed was going in the wrong direction in developing versions of Impressionism. When Picasso unveiled the painting his friends thought he had lost his mind. He couldn’t sell it and didn’t exhibit it until 1916. He finally sold it in 1925.
Both men had the self-confidence to believe that their ideas would be accepted. They did not become discouraged.
Problem discovery can be a risky business as it was for Galileo some three hundred years earlier. He believed that instead of studying the behaviour of falling bodies according to Aristotle’s laws, fall through a vacuum should be explored. This view went against everyone’s grain both scientific and, most dangerously, theological.
Instead of working along one of the many different directions in which 17th century music was moving, Johann Sebastian Bach decided to unify them. In so doing he produced melodies that seem as if he touched the cosmos. Yet after his death Bach’s music fell into almost total obscurity for over a century until resurrected by Felix Mendelssohn, who understood what he had done.
RB: Do you have any specific examples where artistic explorations have helped to guide scientific thinking? And vice versa?
AM: Einstein discovered relativity by thinking like an artist, that is, by focusing on issues of symmetry and beauty. He makes this abundantly clear in the very first sentence of his relativity paper where he suggests using aesthetics as a guideline for research.
Picasso thought like a mathematician, scientist and technologist in creating his breakthrough painting of 1907, Les Demoiselles d’Avignon, the harbinger of Cubism. He used notions of four-dimensional geometry which he heard about from a friend who showed him a book on the subject. (Picasso, of course, could not understand the mathematics but was dazzled by the illustrations; the fourth dimension was a spatial dimension.) In addition the phenomenon of x-rays (what you see is not necessarily all there is) was of importance to his thinking as well as cinematography and photography. In other words, mathematics, science and technology.
A favourite example of mine for an effect of art on science is how Cubism helped Bohr come to grips with the highly counterintuitive wave/particle duality from quantum physics. According to quantum physics an electron can be wave and particle simultaneously, that is, at the same time. Such a ‘thing’ is unimaginable and so unimageable. Cubism offered Bohr a way to come to grips with this phenomenon.
Bohr was an urbane scientist with interests that went beyond science per se into philosophy and art. He read widely in both subjects. No doubt he read Jean Metzinger and Alfred Gleizes’s 1912 book, On Cubism. These cubist artists described a Cubist painting as representing a scene as if the observer was “moving around an object [in order to] seize it from several successive appearances.” The Cubists achieved this motif through representing a subject from different perspectives all at once on a single canvas. How you view the subject, that is what it is. In 1927 Bohr offered a motif of the world of the atom with striking parallels to the motif of multiple perspectives from Cubism. He called it complementarity. According to complementarity the atomic ‘thing’ has two sides, wave and particle. Depending on how you look at it, that is, what experimental arrangement is used, that is what it is.
Another effect of art on science is Harry Kroto’s discovery of the structure of the carbon 60 (C60) molecule, in 1985, as a “Buckminsterfullerene,” since its shape has strong similarities to Buckminster Fuller’s geodesic dome. Kroto recalled that his background as a graphic artist was essential for constructing a three-dimensional representation of C60 from the two-dimensional diagrams for the chemical bonds between its constituent elements.
Regarding the other direction – how science and technology have affected art – I remind you how these subjects influenced Picasso’s creation of Les Demoiselles d’Avignon.
In the 1960s, at places like Bell Labs, in Murray Hill, New Jersey, scientists started to use computers to do more than graph numerical outputs from complex scientific calculations. They began to construct algorithms for drawing with computers. Thus began computer art.
While in New York City Nam Jung Paik turned to the latest in electronics, including television, to produce electronically-based art.
The 1960s also witnessed the start of full-fledged collaborations between artists, scientists and technologists culminating in 9 Evenings: Theatre and Technology, produced by Billy Klüver, a scientist from Bell Labs who was an integral part of the New York art community, and the eminent artist Robert Rauschenberg.
Combining dance with cutting-edge interactive digital art and rigorous molecular dynamics, the Bristol University scientist David Glowacki’s Hidden Fields shows how the interaction between art and science can go both ways. “Hidden Fields” combines dancers’ movements with cutting-edge interactive digital art and physics, transforming dancers’ movements into what he calls energy fields that create disturbances in computer simulations of molecular dynamics. “Hidden Fields” enables viewers to appreciate the beauty of everyday movements in a unique manner provided by 21st century science and technology.
But Hidden Fields offers more. It turns out that the super-fast algorithms originally cooked up for dance have led to new avenues of scientific research including a means for scientists to interactively manipulate chains of protein molecules towards exploring how they can bond together in ways that avoid potentially disastrous structures. These methods are sometimes 10,000 times faster than brute-force structure-finding algorithms. This is an unexpected result from the frontier where artistic and scientific creativities fuse. An in-depth interview with Glowacki is in the May 2016 issue of Interalia Magazine
RB: A number of contemporary science-influenced artists use data visualisation as a primary means of their creative output. Can you give examples of this?
AM: First of all, we are not dealing here with “science-influenced artists,” or artists collaborating with scientists, but with people who are artist, scientist and technologist wrapped into one. This is the avant-garde 21st century artist. From extensive interviews with some of them for Colliding Worlds – dispatches from the edge – I drew the conclusion that art, science and technology as we know them today are disappearing, fused into what I call a Third Culture which produces a new form of art I refer to as “artsci,” for lack of a better term. It is the new avant-garde because it produces work that differs radically from anything that has gone before. This Third Culture is in addition to the two traditional cultures of the Arts and the Sciences.
In the 21st century we have moved from the age of technology to the age of information, the age of data, the age of data visualisation art. The data visualisation artist uses algorithms to mine huge caches of data and represent them aesthetically.
A stunning example is Aaron Koblin’s Flight Patterns, which represents data from 250,000 airplane flights across the United States on 12 August 2008. This electronically-based installation constantly evolves https://www.youtube.com/watch?v=ystkKXzt9Wk . A pattern emerges – the outline of the continental United States. Patterns are essential for data visualisation art, as they have always been for data analysis because patterns are the DNA of nature.
RB: Following on from this, what is the relationship between information content and aesthetics?
The measure of aesthetics in data visualisation art is that the greater the information content in a representation of data, the greater the aesthetics. This is an extraordinary extension of the notion of aesthetics into the age of information. And it has objectivity too.
I say this because aesthetics in classical art is in the eye of the beholder and so is totally subjective. But it is good to remember that just as there has always been aesthetics in art there has always been aesthetics in science. In the 20th century aesthetics in science has become more objective. This can be traced to the very first sentence in Einstein’s 1905 relativity paper where he suggests using notions of aesthetics as a guideline for research.
Denizens of the Third Culture told me that measures of aesthetics can involve simplicity, function, balance between form and function and meaning. It is an aesthetics of coding, of images being generated before your eyes in which the viewer is often a participant.
At this point in a lecture someone usually asks me for a definition of aesthetics. And at this point the veins stand out in foreheads of dyed-in-the-wool stuck-in-the-past classical art aficionados when I reply, “Yes. Here’s a one-liner, in fact an equation.”
Aesthetics = Image (not necessarily a visual one but a mental image from one of our five senses) + the electronics that produces the image.
Artists in the new avant-garde nod in approval.
RB: Can algorithms enable us to better understand the mind of a Bach or Mondrian?
AM: Yes, but not just yet.
Algorithms have been written to produce music that is difficult to discern from that written by Bach. Those with some musical experience can usually – but not always – tell the difference. Nevertheless everyone agrees that the melodies are beautiful. Is this not creativity?
Regarding Mondrian. In the 1960s, A. Michael Noll, a scientist from, once again, Bell Labs, wrote an algorithm that connected randomly produced dots two at a time in horizontal and vertical lines. He placed the result next to Piet Mondrian’s 1917 Composition with Lines and asked a sample of one hundred people at Bell Labs to identify the computer-generated Mondrian. A mere 28% guessed right. Then he asked a more interesting question: Now that you know which is the real Mondrian, which one do you prefer? 59% preferred the computer Mondrian because, they said, it exhibited a randomness that the real Mondrian did not. To them randomness meant creativity even if it was produced by a computer.
Do these algorithms tap into the minds of Bach and Mondrian? Presently they provide hints, nothing more. I am confident that algorithms more attuned to the brain’s neuronal structure will.
RB: Can computers be genuinely creative?
AM: We have witnessed machine creativity in IBM Deep Blue, IBM Watson and Google’s AlphaGo. These machines won at chess, Jeopardy and Go. Granted Deep Blue was purpose built to play chess and was essentially a number cruncher – more exactly a move cruncher – capable of running through 200 million moves per second. But less so for Watson which was designed to reason from a vast data base of information fed into it. And even far less so for AlphaGo which runs on the latest deep neural network technology designed in analogy with the neural networks in our brains and learns by playing a million games of Go in one day.
Is not creativity the mind’s ability to sift through data and discern patterns, that is, make discoveries? While we recognise this as creativity for people, for machines we say that it is merely number crunching. Is this the correct way to approach machine creativity? The notion of ‘to understand’ with regards to humans is not necessarily the same as understanding how machines ‘understand’.
Plugged into the web, machines have all knowledge at their disposal and are potentially capable of solving any problem posed to them. They will have read about the creativity of great human thinkers and take clues from them as well as what’s written about them and will be able to weigh various views on aesthetics.
Besides stand-alone artificial intelligence (AI) there is also intelligence augmentation (IA) in which humans and computers work hand-in-hand. We do this whenever we ask Google a question arising from our research. There has been success with IA in chess where humans with laptops play each other in special tournaments. In principal the machine enhances a player’s tactical ability in sighting blunders enabling him to focus on strategy.
RB: Is intuition a part of creativity and the creative process?
AM: Yes. But by intuition I don’t mean some fuzzy notion. Intuition is a faculty that is honed by experience, by conscious thought, while working on many problems in a certain area. It is the purview of experts.
RB: Can we improve our own creativity?
AM: Yes. By improving our problem solving ability. By not being afraid to make mistakes. By learning to introspect – to sit in a room alone and think about the problem you’re working on.
Creativity will have no bounds for machines. Nor for humans who are merging with them. We are entering an age where the notion of what it means to be a human being will be redefined.
For more see my forthcoming book where I explore case studies of highly-creative individuals into the 21st century as well as how AI is transforming the very notion of creativity.
For more about the Third Culture see my Colliding Worlds: How Cutting-Edge Science is Redefining Contemporary Art
For more about metaphors and creativity see my Insights of Genius: Imagery and Creativity in Science and Art
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