"The Uncanny Valley"is Flash Art's new digital column offering a window on the developing field of artificial intelligence and its relationship to contemporary art. The last decade has seen exponential growth in the aesthetic application of AI and machine learning: from DeepDream's convolutional neural networks that detect and intensify patterns within individual images; to NST (neural style transfer) techniques that manipulate one image into the style of another; to GANs (generative adversarial networks) that digest large datasets of images in order to generate new visions without human intervention. Although the community of computational artists and creative AI hackers still exists largely outside of the contemporary art scene, a growing body of artists has sought to traverse both territories, in the process foregrounding the cultural, ethical, and social problems that underpin our new digital architecture. In recent years, Jake Elwes has distilled the full range of AI-informed strategies into a diverse series of outputs: transcriptions of tech leaders' numerical babblings (dada da ta, 2016); video installations projecting conversations between two neural networks (Closed Loop, 2017); and 2016's Auto-Encoded Buddha -- a tribute to Nam June Paik's TV Buddha (1974) -- in which a computer struggles to depict the Buddha's true essence. Through these works and others, Elwes has actively positioned himself within the long histories of video and computer art, and against the notion that AI is capable of expressing intentionality.

On first sight, coming with a definition for "AI arts" does not sound hard. AI (an abbreviation for the term Artificial Intelligence) refers to computers being able to perform many human-like cognitive tasks, such as playing games of chess and Go, recognizing content in images, translating between languages, selecting best candidates in a job search based on their CVs, and so on. This is how AI has been traditionally understood, and we can extend this concept to the arts. Following this logic, "AI arts" would refer to humans programing computers to create with a significant degree of autonomy new artifacts or experiences that professional members of the art world recognize as belonging to "contemporary art." Or, we can teach computers skills of artists from some earlier historical period and expect that professional art historians recognize new artifacts the computer creates as possible art from this period.

On first sight, coming with a definition for "AI arts" does not sound hard. AI (an abbreviation for the term Artificial Intelligence) refers to computers being able to perform many human-like cognitive tasks, such as playing games of chess and Go, recognizing content in images, translating between languages, selecting best candidates in a job search based on their CVs, and so on. This is how AI has been traditionally understood, and we can extend this concept to the arts. Following this logic, "AI arts" would refer to humans programing computers to create with a significant degree of autonomy new artifacts or experiences that professional members of the art world recognize as belonging to "contemporary art." Or, we can teach computers skills of artists from some earlier historical period and expect that professional art historians recognize new artifacts the computer creates as possible art from this period.

"AI art", or more precisely art created with neural networks, has recently started to receive broad media coverage in newspapers (New York Times), magazines (The Atlantic), and countless blogs. Combined with the ongoing general "AI hype" and multiple recent museum and gallery exhibitions, this coverage has produced the impression of a new star rising in the art world: that of machine-generated art. It has also led to the popularization of an ever-growing list of philosophical questions surrounding the use of computers for the creation of art. This brief article provides a pragmatic evaluation of the new genre of AI art from the perspective of art history. It attempts to show that most of the philosophical questions commonly cited as unique issues of AI art have been addressed before with respect to previous iterations of generative art starting in the late 1950s. In other words: while AI art has certainly produced novel and interesting works, from an art historical perspective it is not the revolution as which it is portrayed.

Marcus du Sautoy is the kind of science writer who cares more about questions than answers. In his books he tackles "unsolved problems", "number mysteries" and "the great unknown", topics at the edge of human understanding. They are subtitled with words such as "odyssey", "exploration" and "journey". But Du Sautoy is a flaneur: his trips are not motivated by destinations. This is both the main strength and flaw of The Creativity Code, a wide-ranging and fact-packed tour d'horizon of current applications of artificial intelligence in mathematics and the arts.

It's said that all that needs to happen for something to be considered art is for someone who identifies as an artist to declare it as such. But to most of us, art is created, not just declared and should be delivered with a healthy dose of creative human agency. Regardless of definitions, most of us know art when we see it, don't we? And what does it matter in any case? The short answer is that computer art has been challenging us to confront these questions for over 50 years--the role of the artist (and that of the machine) in the field of computer art has never been completely easy to resolve.

It's an aspect of normal human intelligence, not a special faculty granted to a tiny elite. There are three forms: combinational, exploratory, and transformational. All three can be modeled by AI--in some cases, with impressive results. AI techniques underlie various types of computer art. Whether computers could "really" be creative isn't a scientific question but a philosophical one, to which there's no clear answer.

In December 1964, over a single evening session in Englewood Cliffs, New Jersey, John Coltrane and his quartet recorded the entirety of A Love Supreme. This jazz album is considered Coltrane's masterpiece – the culmination of his spiritual awakening – and sold a million copies. What it represents is all too human: a climb out of addiction, a devotional quest, a paean to God. Five decades later and 50 miles downstate, over 12 hours this April and fuelled by Monster energy drinks in a spare bedroom in Princeton, New Jersey, Ji-Sung Kim wrote an algorithm to teach a computer to teach itself to play jazz. Kim, a 20-year-old Princeton sophomore, was in a rush – he had a quiz the next morning.

Most of us are fascinated by creativity. New ideas in science and art are often hugely exciting – and, paradoxically, sometimes seemingly "obvious" once they've arrived. But how can that be? Many people, perhaps most of us, think there's no hope of an answer. Creativity is deeply mysterious, indeed almost magical.

In December 1964, over a single evening session in Englewood Cliffs, New Jersey, John Coltrane and his quartet recorded the entirety of A Love Supreme. This jazz album is considered Coltrane's masterpiece – the culmination of his spiritual awakening – and sold a million copies. What it represents is all too human: a climb out of addiction, a devotional quest, a paean to God. Five decades later and 50 miles downstate, over 12 hours this April and fuelled by Monster energy drinks in a spare bedroom in Princeton, New Jersey, Ji-Sung Kim wrote an algorithm to teach a computer to teach itself to play jazz. Kim, a 20-year-old Princeton sophomore, was in a rush – he had a quiz the next morning.