With the Fourth Industrial Revolution, everything became possible, and the cognitive imagination based on science and laboratory research became what leads the human mind towards discovering new horizons for humanity that did not exist before, especially with the huge leaps that have occurred and are still occurring every day in programming sciences, algorithms and artificial intelligence. And machine learning, the Internet of things, cloud computing, and the emergence of a new concept, "Computational Creativity".
Computational creativity is defined as the study of creating creative programs to discover new concepts and ideas in a variety of fields, such as literature, art, games, engineering, music, and others. Scenarios and other applications of computer creativity Computer creativity programs are commonly used in creative writing and editing photos and videos, according to the GlobeNewsWire platform in a recent report.
According to a recent report issued by MRFR (Market Research Future), the global market size in this field is expected to reach about $1.15 billion by 2026.
But how was the beginning?
Where did the first spark in this human effort towards the future come from?
Australian writer and writer Richard Moss tries to answer this question by tracing the development of the concept of computational creativity, and the use of artificial intelligence in the creative process that was believed until very recently to be the preserve of humans.
Moss begins his article from the very beginning, when British artist Harold Cohen met his first computer in 1968, and then wondered if machines could help solve a puzzle that had baffled him for a long time: How do we look at a drawing, and a few little scribbles , see a face?
Five years later, Cohen created a robot "artist" he called AARON to explore this idea, and he provided the robot with basic rules and data for drawing, how to draw body parts, and he sat and watched the results.
Not far from this was the composer David Cope, who coined the phrase “Musical Intelligence” to describe his experiences with AI-assisted music composition.
In this context, Cobb told Richard Moss that as early as the 1960s it seemed to him "perfectly logical to do creative things with algorithms, rather than write every word in a story, perform every brushstroke in a painting or compose every note into a melody." ...", and in 1981 Cope turned to computers to chase this dream.
In the late 1990s, computational creativity became a formal curriculum for study with a growing group of researchers (Getty Images)
creative machines
Cohen and Cope were among a handful of "freaks" who sought to make computers produce creative things against their cold, mechanistic nature, and the concept of artificial intelligence at the time was still in its infancy and focused directly on some hard concepts such as thinking and planning, or on performance tasks such as playing chess or solving mathematical problems, and no one thought about the idea of “creative machines” at the time.
But slowly, when Cohen and Cope launched a series of academic papers and books related to their work, things began to change, and a new field of research emerged called “computational creativity.” This new field involved the study and development of autonomous creative systems, interactive tools that support human creativity, and the mathematical approach. To model human creativity.
In the late 1990s, computational creativity became an official curriculum for study with a growing group of researchers, and eventually this new science had its own journal and annual conference as well.
Soon, creative AI was able to assimilate real-world data and identify patterns and rules to which its creations could apply, thanks to new techniques in machine learning and artificial neural networks where connected computer nodes try to mirror the workings of the brain, Moss explains in his article.
Creativity according to mood
Computer scientist Simon Colton, who was at Imperial College London and now at Queen Mary University of London and Monash University in Melbourne, Australia, spent much of the first decade of the 21st century building the Painting Fool. ).
The software analyzed the text of news articles and other written work to identify sentiment and extract keywords, then combined that analysis with automated searches on the photography website Flickr to help it create moody collages at the heart of the original article.
Later, the "Painting Fool" learned to draw pictures in real time of the people he met through an attached camera, according to his "own mood", and sometimes the program refused to paint anything because he was in a "bad mood". , and does not wish to draw, as Moss emphasized in his article.
In early 2010 computational creativity shifted to games (Anatolia)
What does it mean to be creative?
Likewise, in early 2010 computational creativity turned to games, artificial intelligence researcher and game designer Michael Cook dedicated his PhD thesis at University College London to making ANGELINA, which designed simple games based on news articles from The Guardian. Guardian), these games combine current-event text analysis with hard-coded design and programming techniques.
Moss quoted Colton as saying that artificial intelligence systems during this era have become like creative artists, through their ability to integrate elements of creativity such as intent, skill, appreciation and imagination, and this was followed by the global debate about what it means to be creative.
The writer asserts that these new techniques that excelled in classifying data to high degrees of accuracy through iterative analysis have helped artificial intelligence to master current creative methods, as artificial intelligence can now create works such as works of classical composers, famous painters, international novelists, and others.
For example, a single painting created by artificial intelligence such as thousands of paintings painted between the 14th and 20th centuries sold for $432 to $500,000 at auction. In another case, many struggled to distinguish between Johann Sebastian Bach's musical phrases and those created by a computer program called Kulitta was trained on Bach's writings.
And it came down to cooking. IBM got into the field when it commissioned its Watson AI to analyze 9,000 recipes to create its own kitchen ideas.
Elaborate simulation or real creativity?
At this point, the writer, like many others, wonders whether these artificial intelligence systems show true creativity. All previous experiences were attempts to imitate works that really exist, and although they are sophisticated in imitating them, these creative artificial intelligence systems seem unable to real innovation because they lack to the ability to incorporate new influences from its environment.
In this context, Colton and colleagues said, it requires "a lot of human intervention, supervision and high technical knowledge".
In general, as composer Pal Dalstead said, "these AI systems converged towards the middle, creating something typical of what already exists, while creativity is supposed to veer away from everything that is typical."
In order to take a step toward true creativity, Dalstead suggested that AI “must understand, comprehend, and formulate the reasons for the existence of music, and the conditions for its appearance, not just its consequences.”
Here, Richard Moss asserts that "true creativity lies in the search for originality, it is the recombination of disparate ideas in new ways, and the presentation of unexpected solutions that may appear in the form of literature, music or painting, and it is also a flash of inspiration that helps progress in various areas of life such as the way Arranging electric lights in the streets, or inventing aircraft, and in the view of many, the machines have not been able to reach that point.”
Creative machines are changing our understanding of ourselves
In the past few years, creative AIs have expanded to their own “Style Invention,” which has enabled them to compose and create individually rather than imitate, meaning “meaning and intent,” which are the two essential components of the creative process.
In Richard Moss' view, this element of intent to focus more on the creative process than the final product is key to achieving creativity, but he questions whether meaning and originality are also necessary, as the same poem could lead to vastly different interpretations if the reader knew That its author is a man, a woman, or a machine.
Another question Moss asks: If AI lacks the self-awareness to think about its actions and experiences, and to communicate its creative intentions, is it really creative?
Or is creativity still with the author who fed the data and directed it to work?
In the end, the transition from ordinary machines to creative machines may change our understanding of ourselves;
70 years ago, when Alan Turing - sometimes described as the father of artificial intelligence - devised a test he called "The Imitation Game" to measure machine intelligence against our own, Swedish technology philosopher Joel Barthemore wrote, "Turing's greatest insight lies in seeing computers as a mirror that can be It enables the human mind to see itself in ways it was not possible before.”