As more tasks are delegated to machines, the question arises if this can also be done for artistic creation. For some, art is one of the last domains that have not been taken from us yet, a domain we like to claim exclusively for us, humans. Others do not have a problem admitting that machines can create art. And, perhaps for most of us, things are not that clear at all. We are not sure. Is it really art, and if so, is it different from human art? What exactly is the status of these works and these creative acts?

The problem is not a merely abstract one: people have tried to make machines that create art, and many works created by machines are already presented as art.^Footnote1 But if a computer is said to compose music, is the machine really “creative”? And, is the product really art? What should we think of claims that, for instance, a neural network has created a Van Gogh^Footnote2 or a robot is able to draw portraits of people?^Footnote3 We can see the outcome and performance, and perhaps, we see something that looks like art. But, is it art? Is for instance the robot really drawing? Is the process really creative? There is uncertainty about the status of these works of art and creative processes.

Interestingly, it does not suffice to answer these questions by saying that the results of these artistic and scientific experiments are merely “programmed”. It is more complicated than that. They are programmed in the sense that the algorithm, the code, is programmed, but the end product—what is claimed to be the work of art—is not directly made by a human being. The algorithm, not the human, is the “artistic” agent. The human is the creator of the code, not of the work of art. The non-human creator is created by human creators, but the work created by the non-human agent is not directly created by the humans (compare this to the idea that human beings are created but then in turn themselves become creators, become themselves a demiurge—a mortal one, but a creator nevertheless). It seems that the creativity is no longer entirely in the programmer but has migrated to the technology. This is especially the case when the machine has the capacity to learn or when, in other ways, the process cannot simply be reduced to the execution of a code written by humans (the promise of artificial intelligence and artificial creativity). Thus, machines seem to enter the sphere that was previously reserved for humans. But, in what sense does the machine ‘create’ the work, is what goes on here really creativity and is the result really a work of art?

These questions are not only interesting from the point of view of determining the status of machine art and machine creativity, they also make us reflect on the nature of human art and human creativity. They are interesting for researchers in cognitive science and artificial intelligence who want to explain human creativity (see below), but also for philosophers thinking about art, about the human and about the ways humans may relate to technology. Thinking about machine art forces us to re-examine our classic definitions of art and creativity. What exactly do we mean when we say that someone is creative? What is art creation and what is art? Similarly, these questions make us think about what “humanness” means as opposed to the “machine” character of things and activities. What exactly is so special about us compared to machines? What do we mean when we say that humans can create ‘original’ art?

Finally, this exercise of questioning machine art and machine creation is also important for the philosophy of technology, since as I will show, it raises the question concerning the relation between art and technology. What exactly is the role of technology in art? Are there similarities between artistic creation and technology? What do we mean by technology anyway? Moreover, as the beginning of this introduction suggested, the discussion about the artistic status of machine “art” seems also part of a broader discourse and anxieties/enthusiasm concerning the question if machines will take over, if they will make humans obsolete in a lot, if not all, domains of previously exclusively human activities. Consider for instance the discussion about robots in healthcare or the discussion about automation and employment: will robots replace nurses and perhaps replace all kinds of jobs previous done by humans? Will they even take over more intelligent and indeed more creative jobs? But, what do we mean by creative?

In response to these problems, this paper offers a framework of concepts and questions that can be used to discuss the main question in a more precise way when faced with particular cases and claims about machine art and machine creativity.

First, the paper breaks the main question down in three sub-questions, and then analyses each question in order to arrive at more precise problems with regard to machine art and machine creativity: What is art creation? What do we mean by art? And, what do we mean by machines create art? This analysis then provides criteria we can use to discuss the main question in relation to particular cases. In the course of the analysis, the paper engages with theory in aesthetics and literature on computational creativity and contributes to the philosophy of technology and philosophical anthropology by reflecting on the role of technology in (all human) art creation. Although this discussion is in no way exhaustive of all the relevant theories that may be found in these fields, the emphasis is on the articulation of some of the main positions and criteria.

Then, starting from these questions, the paper contributes its own argument about the status of machine art, which does not only respond to the subject-object discussion but also enables a questioning of the question regarding criteria. Articulating and criticizing some unexamined assumptions in the previous discussion, it is first argued that the distinctions between process versus outcome criteria and subjective versus objective criteria of creativity are unstable, that we should consider non-human forms of creativity and that we should not only consider cases where either humans or machines create art but also collaborations between humans and machines—a thought which invites us to further reflect on human-technology relations. Finally, the paper questions the very approach that seeks criteria. It is suggested that the artistic status of machines may be shown and revealed in the human/non-human encounter before any theorizing or agreement takes place, and that this epistemology of machine creativity hints at a more general model of what happens in artistic perception and engagement as a hybrid human-technological and emergent process. It is a hope of the author that this model leaves more room for letting ourselves be surprised by creativity—human and perhaps non-human.

A first way to break down the large question “can machines create art?” into smaller parts is to distinguish between process and outcome. We can focus either on the creative process or on the work of art. One could add more elements^Footnote4 and later on in the paper, I will question this distinction, but it is a good way to start the analysis.

It is also a distinction that can be found in discussions about ‘computational creativity’ in artificial intelligence, cognitive science and related areas. Whereas some researchers focus on creating art works with their machine, on the ‘external’ outcome, others focus more on the ‘internal’ workings of the machine, on the process by which the art work is created. An example of the first approach is the so-called Turing test for art works: people are asked to say which work of art is created by a human and which one is created by a computer. A machine work of art passes this Turing test if people are unable to make this distinction, that is, if they think it might as well be created by a human. For instance, Boden defines the criterion as follows: for a program to pass the Turing Test ‘would be for it to produce artwork which was (1) indistinguishable from one produced by a human being and/or (2) was seen as having as much aesthetic value as one produced by a human being’ (Boden 2010, p. 409). But, if a machine passes this test—and many people in the field claim machines have already done so—then is this machine really creative? This leads many researchers in computational creativity (including Boden) to take the second approach, which tries to define creativity in a non-behavioural way. An example of the second approach is discussions about what creativity is and what capacities are needed for creativity. For instance, one may argue that what is needed is a system that ‘legitimately instantiates mechanisms with some similar properties to those that result in the appearance of mental states in cognitive agents’ (McGregor et al. 2014). Or, one may argue that creativity requires imagination and/or that embodiment is necessary for creativity. One may also ask if the capacity to create presupposes the capacity to evaluate and appreciate art. These discussions have an overlap with discussions in the philosophy of the mind (see for instance McGregor et al. 2014) and of course artificial intelligence in general. For instance, the attempt to create a machine that has a genuine creative process and capacities (rather than merely imitating this process and these capacities) has been termed ‘strong computational creativity’ as opposed to its ‘weak’ counterpart which only tries to mimic the creative process, in analogy with ‘strong AI’ versus ‘weak AI’ (Al-Rifaie and Bishop 2015).