*Article* **Communication Machines as Art**

#### **Ernest Edmonds**

IOCT, Leicester Media School, De Montfort University, The Gateway, Leicester LE1 9BH, UK; ernest@ernestedmonds.com

Received: 30 December 2018; Accepted: 4 February 2019; Published: 9 February 2019

**Abstract:** The paper presents a personal history of making machines as artworks. The particular kind of art machines that have been made since around 1970 are communication machines: ones that enable humans to interact with each other. However, they do not provide communication in the normal sense, but use a small bandwidth for relatively complex connections, making the experience of the interactions the art experience. The paper concludes by explaining how it later became possible to use computer networking and the Internet to make artworks that were more complex and, in part, autonomous generative machines whilst retaining the earlier communication machine functions.

**Keywords:** art; computer; communication; machine

#### **1. Introduction**

The paper follows an earlier one in this journal in which I described my personal development in relation to art made by algorithmic machines (Edmonds 2018a). For completeness, I will repeat a few of the points made in that earlier description. However, this paper deals with a different aspect of that personal development. In this case, I will review my art that is about human-to-human communication through machines. So the algorithm in the machine, that is central to that other stream of work, is not the point here. Instead, machines have been constructed as artworks through which people communicate with one another. The forms of communication are not linguistic, or meaningful in that explicit sense, but nevertheless what one person sees or hears in the machine is determined by the actions of others. These art works are communication machines, machines that, when operated at least, are art. I presented a paper at a 1970 Computer Graphics conference, Computer Graphics '70, together with Stroud Cornock. It was titled "The Creative Process where the Artist is Amplified or Superseded by the Computer". We discussed the implications of the computer for art and for the role of the artist. We asked: would this machine become the artist of the future? Would the artist of the future have any role at all? The paper was later published in Leonardo (Cornock and Edmonds 1973). Although not discussed in that paper, I was also asking a closely related question: would the machine become the art? The context in which I was asking this last question was communication. As I will explain, I had become interested in human-to-human communication processes and I saw one route forward in my exploration of the computer and art in communication machines. The paper will show how this began using purpose-built logic circuits rather than computers as such and how it has developed into Web-based art machines.

This paper discusses a certain path in the history of interactive art and discusses the context of that history. Whilst considering the works reported, a number of other, non-historical, research questions come to mind. Some of these have been investigated and such work is briefly introduced in Section 5.

#### **2. Machines (as Art)**

A machine can be defined as "a piece of equipment with several moving parts that uses power to do a particular type of work"1. Today, the notion of "equipment with several moving parts" is taken to include electronic devices, such as the computer. There is expected to be a clear task that a machine should undertake and normally its operation is deterministic: it will always operate in the same way. Another important characteristic of a machine is that it needs a human operator who, at the very least, sets it going. Until it is "going" a machine has little meaning. If we take an interest in the aesthetics of a machine, then that can only be considered when the machine is in action (Edmonds 1987). As Werner Gräff said of the 1925 Berlin bus, " ... the shape of a vehicle must be preserved above all when it is in motion ... OUR NERVES demand PNUMATIC TYRES ... And our aesthetic sense too" (Gräff 1926).

A machine that is art is a working machine that is doing something. We might argue, taking this point further, that the art in an art machine is in what it does much more than in how it looks. Perhaps how it looks is of little concern at all. One perspective on machines as art is to consider them doing something that creates the aesthetic experience that defines the art. It is this view that informs the kind of machine as art that I am reporting here. The machines that I have built and that I describe below are electronic machines, sometimes using computers. Their appearance is often not material. It is primarily the experiences that they facilitate in the audience that is at the core. In this case the audience consists of the operators of the machines, so we would normally call them the participants. The art forms of my machines discussed in this paper are particular cases of interactive art, forms in which the interaction is between different participants through the machines.

#### **3. The Communications Game Concept**

At the same time that Stroud Cornock and I were discussing what became the Computer Graphics '70 conference paper referred to above, I was following psychological research about language and learning. I was most influenced by the work of T.G.R. Bower. He neatly described the key points in a book a little later (Bower 1974). As I have described elsewhere, my focus was on a notion of communication that "was one of meaningful interaction in the sense of, for example, the ways that T.G.R. Bower found that newborn infants explored the world around them. They took actions, observed what happened and, in a very real sense, seemed to form theories that could be tested. They began learning how to communicate through the exploration of actions purposefully taken." (Edmonds 2016). The exploration of interactive art using computers, that was at the heart of the Cornock and Edmonds paper, informed my thinking about this early infant behavior: about the early communications with the world that a newborn makes. Perhaps I could make interactive art, in some sense, that explored these psychological findings about learning to communicate?

My concept was to build an art machine that in itself had no aesthetic, or other, interest but that facilitated some kind of low bandwidth exchange between people, where the involvement in that exchange was the art work experience. The machine I devised was called a *Communications Game*. I used the label "game", not because there was any "computer game" or party aspect to it but so as not to stress my intention to make "art" and so risk participants putting barriers up.

The idea was to provide very simple communication networks between participants who could not see one another. Each participant would access *Communications Game* through their own unit or station. A way of adding a small amount of complexity, that to me seemed to be a vital part of the real world, was to have at least three participant units and for the networks to cross over, so that there was only ever a partial direct link. Thus each unit was to be equipped with an input switch for turning on lights in units of the same network and a single light for output. For each participant, the lights provide the stimuli and the switches, the means of action or response. As I indicated, screens would

<sup>1</sup> Machine, definition, Cambridge Dictionary: https://dictionary.cambridge.org/dictionary/english/machine (accessed on 28 December 2018).

keep participants from seeing each other. The illumination of a light on one unit is controlled by the other participants by opening or closing their switches. The truth table shown in Figure 1 shows how I planned one configuration to work, where for example a person at A can control switch A and sees light A.


**Figure 1.** Truth table drawing, *Communications Game* (c. 1970), © Ernest Edmonds.

The *Communications Game* machine was not defined as any particular physical object. I defined it functionally but was very clear that it could be realized in many different ways. See my note from that time, for example, the "specification" remark in Figure 2. I was emphatic that this was not to be an aesthetic physical object. It was not a crucial issue that it should look a particular way, be in a particular color or be made of a particular material. In a sense, the art was conceptual but the point was that the art was the machine in action, providing the interchange between people that I termed, perhaps rather grandly, "communication". The concept of this work was of a particular machine that was the art, at least once it was in action. By definition, however, there was never meant to be only one physical object. As with most machines, it could be copied, varied and reproduced, as I will describe below.

**Figure 2.** Notes about *Communications Game* (c. 1971). © Ernest Edmonds.

#### **4. Realizing Communications Games**

The first *Communications Game* that I constructed was shown in the *Invention of Problems II* Exhibition at the City of Leicester Polytechnic in 1971. The work has six stations and there are three networks of three units. Screens kept the participants apart. The general physical arrangement is shown in Figure 3.

**Figure 3.** Sketches of the *Communications Game* layout (c. 1971). © Ernest Edmonds.

I designed electronic circuits to implement the connection logic of the networks, along the lines of the truth table in Figure 1. The actual construction of the connection logic, at that time, involved the use of a soldering iron rather than software, as is more convenient today.

In 1972 I was invited to show in the exhibition organized in Nottingham by Stephan Willats, *Cognition and Control* at the Midland Group Gallery (Edmonds 1972, 1975). For this, I constructed a second version that accommodated three, rather than six, participants. My informal evaluation of the first version was that it was rather over complex and I felt that reducing the number of stations, whilst retaining the rest of the design as before, improved the work. See Figure 4.

**Figure 4.** Sketch of *Communications Game version 2* (c. 1972). © Ernest Edmonds.

A little later, I made a three-station version which used sound output rather than lights. Three boxes were installed in different parts of an informal exhibition, also at Leicester Polytechnic. Figure 5 shows part of the circuit diagram used in this version.

**Figure 5.** Circuit diagram (detail) of *Communications Game* with sound output (c. 1972). © Ernest Edmonds.

I left my work on communication art machines aside for quite some time, until 1990, when Willats invited me to show in his *Art Creating Society* exhibition at what was then called the Museum of Modern Art, Oxford. By now, I could build networks in software, of course, and I built a new version in which each participant saw a screen rather than lights. The screen showed a sequence of images based on my *Fragment* video construct. See Figure 6 and more about *Fragment* in Edmonds (2018a). The operations performed by other participants changed the image sequence. The network, in this version, contained a number of computers as shown in Figure 7. I had intended to make the stations remote by using wide area network connections to a VAX computer in Oxford, but the collaboration was not sealed in time and that aspect was not realized. The use of wide area networks had to wait until the next phase, as described in Section 4.

**Figure 6.** Fragment 1984–5, still from the exhibition 'Duality and Co-existence' Exhibiting Space, London, 1985. Photo Ernest Edmonds, © Ernest Edmonds.

Much later I started to hold retrospective exhibitions of various kinds and it became useful to construct new implementations of *Communications Game*. I used the second, *Cognition and Control*, version for these reconstructions. The first was shown in 2015 in the *Códigos Primordiais* (Primary Codes) exhibition at Oi Futuro Flamengo, Rio de Janeiro (Poltronieri and Menezes 2017). The electronics was reproduced to function exactly as in 1971, but this time implemented in software on Arduino computers. Visually, it looked very similar to the earlier version, see Figure 8.

**Figure 8.** *Communications Game* in the 'Primary Codes' exhibition. 2015. Photo Ernest Edmonds. © Ernest Edmonds.

A very similar reconstruction was shown in 2017 at a one-person retrospective, *Constructs Colour Code: Ernest Edmonds 1967–2017* in The Gallery, De Montfort University, Leicester.

#### **5. Communications Game Machines and the Internet**

Historically, the time when I first developed my *Communications Game* machines was just as the the first working version of ARPANET, the Internet's predecessor, was put together, in 1969 (Leiner et al. 1997). Of course, the idea of an electronic, computer-based network had been under discussion for some time but the Internet itself awaited the key concepts published in 1974 (Cerf and Kahn 1974). Although *Communications Game* was a machine concept developed before Internet art, it was natural to think about implementing it on the Internet once it was available. However, I never considered making a simple direct version.

I reflected on my Oxford experience of making the computer-based version that employed a local area network and worked towards an extension of the concept. Eventually I started to make a series of works, called *Cities Tango,* that were distributed widely over the Internet (Edmonds and Franco 2013). Briefly, images from remote location are dynamically shown within an otherwise abstract colour structure. The images are treated as abstract objects within the work. The colours used and the pace of the work are influenced by a combination of the audience behaviours at the various locations.

*Cities Tango* is not a simple machine like *Communications Game*. It incorporates a different interaction paradigm drawn from my *Shaping Form* pieces. These are individual works, first exhibited in 2007 in Washington, DC (Jennings 2007). In these, images are generated using rules determining the colours, the patterns and the timing. The generative works are also changed by inputs from the environment: movement is detected and causes continual changes to the rules, so that changes are made to the generative process. Thus, many of the changes are only apparent over time. A first viewing followed by another weeks or months later will reveal noticeable developments in the colours and patterns. The *Shaping Form* works might be considered machines, but they are not machines in the sense focused upon in this paper. Therefore, by combining *Communications Game* with *Shaping Form, Cities Tango* demonstrates a more complex machine form.

In one example of *Cities Tango*, the cities, Belfast and Sydney, interacted with one another (Edmonds 2009). The colours, shapes and timings used at one location were driven by movements at the remote one. Sometimes, real-time images from the remote location are shown. Immediate responses to movement in the remote location are seen by participants in their own location. See Figures 9 and 10. Further developments have been made in collaborative projects (Edmonds and Clark 2016).

**Figure 9.** *Cities Tango* in Sydney. 2009. Photo Ernest Edmonds. © Ernest Edmonds.

**Figure 10.** *Cities Tango* in Belfast. 2009. Photo Ernest Edmonds, © Ernest Edmonds.

These works include the communication machine functions discussed above but they are overlaid on a generative process that is independent of any "operator" (participant) action. The *Cities Tango* works are still machines, so "machines as art", but they have partial autonomy and so are more complex than the machines I made in the 1970s.

#### **6. Research Questions Arising from this History**

The primary contribution of this paper is historical but, as the new art forms described above were invented and explored, various research questions arose. Indeed, as I have explained, the initial impetus arose from research in psychology. However, the questions that the work gave rise to, were from the practice-based research viewpoint (Candy and Edmonds 2018) and related more to computer–human interaction than to psychology itself. A full review of such research, from a broader context, is the subject of a recent book that emphasizes how much computer–human interaction research can learn from interactive art research (Edmonds 2018b). I will now give a flavor of research relevant to the art reported in this paper.

Specific issues relating to the artwork *Communications Game* and its developments, technical matters aside, include two main classes of research question: (1) what are the experiences of and influences on the artist, and (2) what are the experiences of the participating audiences?

In relation to the first class of question, I have documented my reflections in the classic practice-based research manner. As yet, most of that research has not been published but, briefly, the key points to note are:


In relation to the second class of question, I should first emphasis that the intended experiences are aesthetic, art, ones. Hence they do not relate to any task or purpose, which would be expected in a more typical computer-human interaction case. The methods used for these studies are those described in two books (Candy and Edmonds 2011; Candy and Ferguson 2014). Those books include various examples of those methods in use together with descriptions of the results.

A specific relevant case of such research was an empirical study of an interactive public installation of an early element of *Cities Tango* (Bilda et al. 2017). The interactions (driven by sound pickup up by a microphone) were quite abstract and participants were at times inclined to "think of sound waves, sunshine and the horizon. Other participants felt happiness, liveliness, a festive or party feel; while still others thought of rhythm and music or a discotheque". A small number of "participants stated that they would have engaged more comfortably if it was in a museum/art gallery context, and that they would prefer an enclosed space with a feeling of an individual experience rather than an open and social one", and "one stated he became self-conscious when he thought he was being monitored". These last two concerns relating, in one way or another, to privacy are of on-going and increasing interest. The future of art of the kind described above must address such concerns, which can indeed become one of the subjects that the art addresses.

The art history described in this paper is one that has led to a particular stream of research about artist and audience experience that is increasingly strong. To review it would require a second paper, at the very least, and here I simply wanted to acknowledge that outcome and point to some of the resulting work.

#### **7. Conclusions**

I have presented a personal history of the making of machines as art. The particular machines that I have made, I have termed "communication machines". The term "communications" has only been used to indicate that participants interact with one another through the machines. There is no suggestion or intention that meaningful communication in any deep sense takes place. The interaction

is aesthetic. It is the art experience. These machines are not of any particular aesthetic interest as objects, only as machines whose operation is being used by the participants. *Communications Game* was a pre-Internet concept but, in the later part of the paper, I indicate how I developed the idea to both employ the Internet over large distances and incorporate generative, autonomous, approaches from my *Shaping Form* works, thus making the *Cities Tango* series. A full discussion of my work is available in Francesca Franco's book (Franco 2018).

**Acknowledgments:** I am grateful to Sean Clark for his help in reconstructing *Communications Game* for the 2015 and 2017 exhibitions. As I was preparing the final version of this paper I discovered that Stroud Cornock had sadly passed away. His collaboration and many conversations inspired much of the work that I have done over the fifty years since we first met.

**Conflicts of Interest:** The author declares no conflict of interest.

#### **References**


Edmonds, Ernest. 2018a. Algorithmic Art Machines. *Arts* 7: 3. [CrossRef]


#### *Arts* **2019**, *8*, 22

Leiner, Barry M., Vinton G. Cerf, David D. Clark, Robert E. Kahn, Leonard Kleinrock, Daniel C. Lynch, Jon Postel, Larry G. Roberts, and Stephen Wolff. 1997. Brief History of the Internet. Available online: https://www. internetsociety.org/internet/history-internet/brief-history-internet/ (accessed on 18 December 2018). Poltronieri, Fabrizio, and Caroline Menezes. 2017. *Primary Codes*. São Paulo: Caosmos.

© 2019 by the author. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

## *Essay* **The Machine as Artist: An Introduction**

#### **Glenn W. Smith <sup>1</sup> and Frederic Fol Leymarie 2,\***


Academic Editor: Annetta Alexandridis Received: 2 March 2017; Accepted: 28 March 2017; Published: 10 April 2017

**Abstract:** With the understanding that art and technology are continuing to experience an historic and rapidly intensifying rapprochement—but with the understanding as well that accounts thereof have tended to be constrained by scientific/engineering rigor on the one hand, or have tended to swing to the opposite extreme—it is the goal of this special issue of *Arts* to provide an opportunity for artists, humanists, scientists, and engineers to consider this development from the broader perspective which it deserves, while at the same time retaining a focus on what must surely be the emerging core of our subject: the state of the art in mechatronics and computation is such that we can now begin to speak comfortably of the *machine as artist*—and we can begin to hope, as well, that an aesthetic sensitivity on the part of the machine might help lead to a friendlier and more sensitive machine intelligence in general.

**Keywords:** art; science; technology; artificial intelligence; aesthetics; empathy; embodiment

#### **The Machine as Artist: An Introduction**

If we can accept the 1967 founding of the journal *Leonardo* [1] and the 1968 publication of Jack Burnham's *Beyond Modern Sculpture* [2] as milestones—and the latter of which had an extensive chapter on "Robot and Cyborg Art"—it must come as a shock to realize that the study of electronic techno-art has been established as a formal discipline for half a century, and which study since placed in brackets with the appearance of at least two comprehensive surveys [3,4]. It continues to be the case, however, that there has also been constant and now breath-taking progress, and to the extent that *we can at present begin to think of the machine, not as the artist's subject matter or medium, but as creator or co-creator*. Indeed, it is this subject to which the current special issue of *Arts* is dedicated; and we begin by noting that the literature bears ample witness to this emergence, and with the contributions documented therein falling into several major sub-fields:


**Figure 1.** Baxter Signing His Name in Graffiti Style [22].

It is of particular interest and significance, moreover, that these sub-fields tend to overlap within the genre of the traditional *graphic arts*—the physical robotic systems producing sophisticated portraits, and the purely computational systems generating sophisticated analyses and transformations of historic and well-known paintings—for we have here a coming-together of a number of critical threads.

This overlap is due, in the first place, to the fact that graphic art can of course be represented by two-dimensional arrays of pixels, and is thus ideally suited for computational analysis. Indeed, virtually all of the important results reported under categories 5, 6, and 7 above have been achieved with that same family of computational techniques—the "deep neural network", or DNN—that has also been responsible for the recent and unprecedented victories of computer over human in master-level Go and Poker tournaments. In other words, *the graphic arts have emerged as a vital research arena for the artificial intelligence community, and to some extent as a replacement for the board game*—and along with this circumstance comes the opportunity for our own contributors to address the larger questions associated with AI.

And the ultimate question at this point is no longer whether or not artificial intelligence will be capable of achieving some real degree of autonomy [43]; the question, rather, is the degree to which such an autonomous or semi-autonomous intelligence can be designed to operate in a consistently humane and responsible manner [44], and with "responsible", in this day and age, understood to include an environmental dimension.

But of course it is not merely the status of the graphic arts as a computer-friendly medium that should encourage its various practitioners to take on the question of a humane AI: the far larger point is that the graphic arts represent a creative and non-competitive and distinctly human activity—an activity, in fact, intimately associated with the emergence of humankind from a preoccupation with mere survival [45,46]—and an activity as well in which the entire focus is on sensitivity of observation and execution.

In short—and if we can thereby conclude with Herbert Marcuse that "the aesthetic values are the non-aggressive values par excellence" [47]—then *the addition of aesthetic capabilities to the machine intelligence armamentarium would perhaps bring us an important step closer to the addition, as well, of a sense of empathy and responsibility*—and it is this possibility that we would like to propose as the focus of our special edition on "The Machine as Artist".

But let us emphasize here—and as strongly as possible—that it is not only those who have been involved with the computational graphic arts who are making, or who are in a position to make, an important contribution to the genesis of a "friendly AI". In particular, the artists and scientists and engineers who have worked to bring the robot out of the factory and into public gallery and exhibition spaces are playing a critical role in introducing machine intelligence as a physical as well as mental presence, and we are eager to hear more of their work; and to the extent that our basic thesis is correct, most such contributions will tend to have at least some bearing on the question, "Can there be a humane intelligence apart from the sense of balance and harmony and attention to detail that we normally associate with aesthetics?"

Given, however, the speculative and cross-disciplinary nature of this question, it is anticipated that many of the submissions to this special edition will take the form of scholarly *essays* or even *communications* (albeit still subject to peer review); i.e.,—and at the risk of repeating ourselves—we hope to provide here an opportunity for specialists in the fields of computer science, neuroscience, anthropology, and art history to share their thoughts on a more open-ended basis.

In this context—and we rush here to our conclusion, and by way of returning to our central theme—the status of the graphic arts is given a powerful boost by the fact that so distinct is the emergence, and so invariant over time the performance and reception of certain of its styles, that we are entitled to regard it as a *phenomenon*—a phenomenon as yet imperfectly understood, but no less worthy of study, and potentially no less rewarding, than the phenomenon of a certain mineral ore able to fog unexposed photographic plates. Or in other words, we have here a near-ideal venue for interaction between the humanities and the sciences in respect to the question of a humane machine intelligence; and in support of this claim we exhibit following a group of drawings from the Chauvet Cave created some 32,000 years ago (Figure 2)—and the freshness and clarity and sensitivity of which must instill in us a deep wonder:

**Figure 2.** Group of Chauvet Cave Drawings. By Nachosan - Own work, CC BY-SA 3.0, https:// commons.wikimedia.org/w/index.php?curid=32316562.

And given, finally, that no modern intellectual enterprise can be complete without a reference to the very real environmental threat facing our planet, we note that here also the graphic arts have a critical role to play, and as likewise deeply embedded in our culture and history—and there is perhaps no better example than Audubon's depiction of the Swallow-tailed Kite (Figure 3).

A computational analysis of the exquisite lines thereof (refined, as we must note, by the master engraver Havell) would almost certainly reveal, from a human factors standpoint, some noteworthy, if not indeed uncanny, qualities; but what should strike us as most uncanny is the fact that the collected set of such images—the graphic art created by Audubon under humble circumstances as he trekked through the wilds of North America—has been responsible for an outpouring of public commitment to environmental preservation to which no modern public relations campaign can bear comparison; i.e., we have here an example of the fact that art has a very real and unique power, and a greater appreciation and understanding of which has now become a vital matter.

**Figure 3.** *Swallow-tailed Kite* by John James Audubon.

**Acknowledgments:** The authors would like to thank the hard-working artists, scientists, and engineers who have made this special issue a possibility.

**Conflicts of Interest:** The authors declare no conflicts of interest.

#### **References**


#### *Arts* **2017**, *6*, 5


© 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

## *Essay* **Art in the Age of Machine Intelligence†**

#### **Blaise Agüera y Arcas**

Research and Machine Intelligence, Google Seattle, 601 N 34th St, Seattle, WA 98103, USA; blaisea@creativemachine.org.uk

† Although the following essay has already been published by Medium

(https://medium.com/artists-and-machine-intelligence/what-is-ami-ccd936394a83), it is being re-published here by an agreement between the author himself and the editorial staff of both Medium and MDPI, and on the grounds that a work dealing in such a clear, comprehensive, and compelling manner with the critical social issue of a rapidly emerging machine intelligence deserves widespread dissemination; furthermore, given that the essay is also thoroughly grounded in respect to the histories of both art and science—and with appropriate citations—such a dissemination might well include academic publication; and given still further that its focus is the advent of machine intelligence as a mighty new factor in the arts, the current Special Issue of Arts on "The Machine as Artist (for the 21st Century)" would seem to be an ideal venue, and wherein it will stand as an important complement to our own introductory essay.

Received: 7 September 2017; Accepted: 14 September 2017; Published: 29 September 2017

**Abstract:** In this wide-ranging essay, the leader of Google's Seattle AI group and founder of the Artists and Machine Intelligence program discusses the long-standing and complex relationship between art and technology. The transformation of artistic practice and theory that attended the 19th century photographic revolution is explored as a parallel for the current revolution in machine intelligence, which promises not only to mechanize (or democratize) the means of reproduction, but also of production.

**Keywords:** art; science; technology; machine learning; artificial intelligence; aesthetics; photography

#### **Art in the Age of Machine Intelligence**

Art has always existed in a complex, symbiotic and continually evolving relationship with the technological capabilities of a culture. Those capabilities constrain the art that is produced, and inform the way art is perceived and understood by its audience.

Like the invention of applied pigments, the printing press, photography, and computers, we believe machine intelligence is an innovation that will profoundly affect art. As with these earlier innovations, it will ultimately transform society in ways that are hard to imagine from today's vantage point; in the nearer term, it will expand our understanding of both external reality and our perceptual and cognitive processes.

As with earlier technologies (Figure 1), some artists will embrace machine intelligence as a new medium or a partner, while others will continue using today's media and modes of production. In the future, even the act of rejecting it may be a conscious statement, just as photorealistic painting is a statement today. Any artistic gesture toward machine intelligence—whether negative, positive, both, or neither—seems likelier to withstand the test of time if it is historically grounded and technically well informed.

**Figure 1.** An American daguerreotype from 1839—amateur chemist and photography enthusiast Robert Cornelius in Philadelphia taking, as far as we know, the world's first selfie. Image permission: this image is in the public domain. United States National Archives, Washington, DC, USA.

Walter Benjamin illustrated this point mordantly in his 1931 essay, "Little History of Photography" (Benjamin 1999), citing an 1839 critique of the newly announced French daguerreotype technology in the Leipziger Stadtanzeiger (a "chauvinist rag"):

To try to capture fleeting mirror images," it said, "is not just an impossible undertaking, as has been established after thorough German investigation; the very wish to do such a thing is blasphemous. Man is made in the image of God, and God's image cannot be captured by any machine of human devising. The utmost the artist may venture, borne on the wings of divine inspiration, is to reproduce man's God-given features without the help of any machine, in the moment of highest dedication, at the higher bidding of his genius. (Benjamin 1999, p. 508)

This sense of affront over the impingement of technology on what had been considered a defining human faculty has obvious parallels with much of today's commentary on machine intelligence. It is a reminder that what Rosi Braidotti has called "moral panic about the disruption of centuries-old beliefs about human 'nature'" (Braidotti 2013, p. 2) is nothing new.

Benjamin (1999) goes on to comment:

Here we have the philistine notion of "art" in all its overweening obtuseness, a stranger to all technical considerations, which feels that its end is nigh with the alarming appearance of the new technology. Nevertheless, it was this fetishistic and fundamentally antitechnological concept of art with which the theoreticians of photography sought to grapple for almost a hundred years, naturally without the smallest success. (Benjamin 1999, p. 508 )

While these "theoreticians" remained stuck in their thinking, practitioners were not standing still. Many professionals who had been making their living painting miniature portraits enacted a very successful shift to studio photography; with those who brought together technical mastery and a good eye, art photography was born, over the following decades unfolding a range of artistic possibilities latent in the new technology that had been inaccessible to painters: micro-, macro- and telephotography, frozen moments of gesture and microexpression, slow motion, time lapse, negatives and other manipulations of the film, and so on.

Artists who stuck to their paintbrushes also began to realize new possibilities in their work, arguably in direct response to photography. David Hockney interprets cubism from this perspective:

cubism was about the real world. It was an attempt to reclaim a territory for figuration, for depiction. Faced with the claim that photography had made figurative painting obsolete, the cubists performed an exquisite critique of photography; they showed that there were certain aspects of looking—basically the human reality of perception—that photography couldn't convey, and that you still needed the painter's hand and eye to convey them. (Quoted in (Weschler 2008, p. 294))

Of course, the ongoing relationship between painting and photography is by no means mutually exclusive; the language of wholesale embrace on the one hand versus response or critique on the other is inadequate. Hockney's "joiners" explored rich artistic possibilities in the combination of photography with "a painter's hand and eye" via collage in the 1980s, and his more recent video pieces from Woldgate Woods do something similar with montage.

Hockney was also responsible, in his 2001 collaboration with physicist Charles Falco, for reigniting interest in the role optical instruments—mirrors, lenses, and perhaps something like a camera lucida—played in the sudden emergence of visual realism in early Renaissance art.1 It has been clear for a long time that visual effects like the anamorphic skull across the bottom of Hans Holbein's 1553 painting The Ambassadors (Figure 2) could not have been rendered without clever optical tricks involving tracing from mirrors or lenses—effectively, paintbrush-assisted photography. Had something like the Daguerre-Niépce photochemical process existed in their time, it seems likely that artists like van Eyck and Holbein would have experimented with it, either in addition to, in combination with, or even instead of paint.

**Figure 2.** The Ambassadors by Hans Holbein, 1533. Oil on oak, 207 x 209.5 cm. *The National Gallery*, London. Image reproduced with permission (left). Digitally reprojected image of the anamorphic skull in the bottom center of the painting. The imperfections evident in the left eyesocket may have been due to the need to move or refocus the optics halfway through. Image permission: courtesy Thomas Shahan, https://commons.wikimedia.org/wiki/File:Holbein\_Skull.jpg. (right).

<sup>1</sup> The Hockney-Falco thesis is explained at length in Hockney (2001) book *Secret Knowledge: Rediscovering the Lost Techniques of the Old Masters*. While critiques of their methodology and expository approach have been made, both by scientists and by art historians (see, for example, Tyler (2004)), the basic point, that the Old Masters used what was at the time state-of-the-art optical technology to render effects in painting, is not in serious dispute.

So, the old European masters fetishized by the Leipziger Stadtanzeiger were not reproducing "man's God-given features without the help of any machine", but were in fact using the state of the art. They were playing with the same new optical technologies that allowed Galileo to discover the moons of Jupiter, and van Leeuwenhoek to make the first observations of microorganisms.

Understanding the ingenuity of the Renaissance artists as users and developers of technology should only increase our regard for them and our appreciation of their work. It should not come as a surprise, as in their own time they were not "Old Masters" canonized in the historical wings of national art museums, but intellectual and cultural innovators. To imagine that optics somehow constituted "cheating" in Renaissance painting is both a failure of the imagination and the application of a historically inappropriate value system. Yet even today, some commentators and theoreticians—typically not themselves working artists—remain wedded to what Benjamin called "the philistine notion of 'art'", as pointed out in an article in *The Observer* from 2000 in response to the Hockney-Falco thesis:

Is [the use of optics] so qualitatively different from using grids, plumb-lines and maulsticks? Yes—for those who regard these painters as a pantheon of mysterious demigods, more than men if less than angels, anything which smacks of technical aid is blasphemy. It is akin to giving scientific explanations for the miracles of saints. (Marr 2000)

There is a pungent irony here. Scientific inquiry has, step by step, revealed to us a universe much more vast and complex than the mythologies of our ancestors, while the parallel development of technology has extended our creative potential to allow us to make works (whether we call them "art", "design", "technology", "entertainment", or something else) that would indeed appear miraculous to a previous generation. Where we encounter the word "blasphemy", we may often read "progress", and can expect miracles around the corner.<sup>2</sup>

One would like to believe that, after being discredited so many times and over so many centuries, the "antitechnological concept of art" would be relegated to a fundamentalist fringe. However, if history has anything to teach us in this regard, it is that this particular debate is always ready to resurface. Perhaps this is because it impinges, consciously or not, on much larger issues of human identity, status and authority. We resist epistemological shock. Faced with a new technical development in art it is easier for us to quietly move the goalposts after a suitable period of outrage, re-inscribing what it means for something to be called fine art, what counts as skill or creativity, what is natural and what is artifice, and what it means for us to be privileged as uniquely human, all while keeping our categorical value system—and our human *apartness* from the technology—fixed.

More radical thinking that questions the categories and the value systems themselves comes from writers like Donna Haraway and Joanna Zylinska. Haraway, originally a primatologist, has done a great deal to blur the conceptual border between humans and other animals;3 the same line of thinking led her to question human exceptionalism with respect to machines and human-machine hybrids. This may seem like speculative philosophy best left to science fiction, but in many respects, it already applies. Zylinska, in her 2002 edited collection *The Cyborg Experiments: The Extensions of the Body in*

<sup>2</sup> Even works that eschew modern technology are often enriched owing to that choice—whether through new perspectives on traditional techniques, as with the analog techno ensemble Dawn of Midi (https://dawnofmidi.bandcamp.com/), or through an aesthetic or even ethic of renunciation, as with Amish furniture made entirely by hand. These artistic or design choices are of course not "wrong"; on the contrary, their "rightness" exists in relation to the technology of the culture in which they are embedded, and they would be diminished without that context. We can be as awed by contemporary renunciatory art as the artists of the past would be by today's "normal".

<sup>3</sup> From an evolutionary point of view, it is clear that other primate brains are closely analogous to those of humans, hence the widespread use of macaques for electrophysiological experiments. Many of Haraway's contributions are, however, focused on behavioral and sociological studies, domains where she shows how the cultural priors of the research community inform which questions are asked, which observations are made, and which conclusions are drawn. There is an element of subjectivity and observer bias in every branch of science, but it's especially pronounced in research areas that rely heavily on narrative and statistical observations.

*the Media Age*, interviewed the Australian performance artist Stelarc, whose views on the relationship between humanity and technology set a useful frame of reference:

The body has always been a prosthetic body. Ever since we evolved as hominids and developed bipedal locomotion, two limbs became manipulators. We have become creatures that construct tools, artefacts and machines. We've always been augmented by our instruments, our technologies. Technology is what constructs our humanity; the trajectory of technology is what has propelled human developments. I've never seen the body as purely biological, so to consider technology as a kind of alien other that happens upon us at the end of the millennium is rather simplistic. (Zylinska 2002, p. 114)

As Zylinska and her coauthor Sarah Kember elaborate in their book *Life after New Media* (2012), one should not conclude that anything goes, that the direction of our development is predetermined, or that technology is somehow inherently utopian. Many of us working actively on machine intelligence are, for example, co-signatories of an open letter calling for a worldwide ban on autonomous machine intelligence-enabled weapons systems (Future of Life Institute 2015), which do pose very real dangers. Turkle (2011) has written convincingly about the subtler, but in their way equally disturbing failures of empathy, self-control and communication that can arise when we project emotion onto machines that have none, or use our technology to mediate our interpersonal relationships to the exclusion of direct human contact. It is clear that, as individuals and as a society, we do not always make good choices; so far we have muddled through, with plenty of (hopefully instructive, so far survivable) missteps along the way. However, Kember and Zylinska (2012) point out,

If we do accept that we have always been cyborgs4 ... it will be easier for us to let go of paranoid narratives ... that see technology as an external other that threatens the human and needs to be stopped at all costs before a new mutant species—of replicants, robots, aliens emerges to compete with humans and eventually to win the battle ... [S]eeing ourselves as always already connected, as being part of the system—rather than as masters of the universe to which all beings are inferior—is an important step to developing a more critical and a more responsible relationship to the world, to what we call "man," "nature" and "technology". (Kember and Zylinska 2012, p. 193)

Perhaps it is unsurprising that these perspectives have often been explored by feminist philosophers, while replicants and terminators come from the decidedly more masculine (and speculative) universes of Philip K. Dick, Ridley Scott and James Cameron. On the most banal level, the masculine narratives tend to emphasize hierarchy, competition, and winner-takes-all domination, while these feminist narratives tend to point out the collaborative, interconnected and non-zero sum; more tellingly, they point out that we are already far into and part of the cyborg future, deeply entangled with technology in every way, not organic innocents subject to a technological onslaught from without at some future date.

This point of view invites us to rethink art as something generated by (and consumed by) hybrid beings; the technologies involved in artistic production are not so much "other" as they are "part of". As the media philosopher Vilém Flusser put it, "tools ... are extensions of human organs: extended teeth, fingers, hands, arms, legs" (Flusser 1983, p. 23). Preindustrial tools, like paintbrushes or pickaxes, extend the biomechanics of the human body, while more sophisticated machines extend prosthetically into the realms of information and thought. Hence, "All apparatuses (not just computers) are ... 'artificial intelligences', the camera included" (ibid., pp. 30–31).

That the camera extends and is modeled after the eye is self-evident. Does this make the eye a tool, or the camera an organ—and is the distinction meaningful? Flusser (1983) characterization of the

<sup>4</sup> "Cyborg" is short for cybernetic organism, meaning a hybrid of machine and biology.

camera as a form of intelligence might have raised eyebrows in the 20th century, since, surrounded by cameras, many people had long since reinscribed the boundaries of intelligence more narrowly around the brain—perhaps, as we have seen, in order to safeguard the category of the uniquely human. Calling the brain the seat of intelligence, and the eye therefore a mere peripheral, is a flawed strategy, though. We are not brains in biological vats. Even if we were to adopt a neurocentric attitude, modern neuroscientists typically refer to the retina as an "outpost of the brain" (Tosini et al. 2014) 5, as it is largely made out of neurons and performs a great deal of information processing before sending encoded visual signals along the optic nerve.

Do cameras also process information nontrivially? It is remarkable that Flusser was so explicit in describing the camera as having a "program" and "software" when he was writing his philosophy of photography in 1983, given that the first real digital camera was not made until 1988 (Wikipedia 2017a). Maybe it took a philosopher's squint to notice the "programming" inherent in the grinding and configuration of lenses, the creation of a frame and field of view, the timing of the shutter, the details of chemical emulsions and film processing. Maybe, also, Flusser was writing about programming in a wider, more sociological sense.

Be this as it may, for today's cameras, this is no longer a metaphor. The camera in your phone is indeed powered by software, amounting at a minimum to millions of lines of code (Information is Beautiful 2017). Much of this code performs support functions peripheral to the actual imaging, but some of it makes explicit the nonlinear summing-up of photons into color components that used to be physically computed by the film emulsion. Other code does things like removing noise in near-constant areas, sharpening edges, and filling in defective pixels with plausible surrounding color, not unlike the way our retinas hallucinate away the blood vessels at the back of the eye that would otherwise mar our visual field (Summers 2011). The images we see can only be "beautiful" or "real-looking" because they have been heavily processed, either by neural machinery or by code (in which case, both), operating below our threshold of consciousness. In the case of the software, this processing relies on norms and aesthetic judgments on the part of software engineers, so they are also unacknowledged collaborators in the image-making.6 There is no such thing as a natural image; perhaps, too, there is nothing especially artificial about the camera.

The flexibility of code allows us to make cameras that do much more than producing images that can pass for natural. Researchers like those at Massachusetts Institute of Technology (MIT) Media Lab's Camera Culture group have developed software-enabled nontraditional cameras (many of which still use ordinary hardware) that can sense depth, see around corners, or see through skin (http://cameraculture.media.mit.edu/); Abe Davis and collaborators have even developed a computational camera that can "see" sound, by decoding the tiny vibrations of houseplant leaves and potato chip bags (Davis et al. 2014). So, Flusser (1983) was perhaps even more right than he realized in asserting that cameras follow programs, and that their software has progressively become more important than their hardware. Cameras are "thinking machines".

It follows that when a photographer is at work nowadays, she does so as a hybrid artist, thinking, manipulating and encoding information with neurons in both the brain and the retina, working with muscles, motors, transistors, and millions of lines of code. Photographers are cyborgs.

*What new kinds of art become possible when we begin to play with technology analogous not only to the eye, but also to the brain?* This is the question that launched the Artists and Machine Intelligence (AMI)

<sup>5</sup> "A remarkable piece of tissue, the retina is a true outpost of the brain, peripheral only for its location on the back of the eye" (Tosini et al. 2014, p. 3).

<sup>6</sup> Similar aesthetic judgments (and impressive engineering feats to support them) were in play by the end of the film emulsion era. Kodacolor II had "as many as 12 emulsion layers, with upwards of 20 different chemicals in each layer" (Wikipedia 2017b). This chemical programming embodied aesthetic judgments, just like the software that eventually replaced it. Aesthetics imply normativity, and therefore are not neutral with respect to subject matter; so for example, photo processing explicitly favored white people until late in the film era. Some digital camera software still reflects racial bias (see Cima 2015).

program (https://ami.withgoogle.com/). The timing is not accidental. Over the past several years, approaches to machine intelligence based on approximating the brain's architecture have started to yield impressive practical results—this is the explosion in so-called "deep learning" or, more accurately, the renaissance of artificial neural networks. In the summer of 2015, we also began to see some surprising experiments hinting at the creative and artistic possibilities latent in these models.

Understanding the lineage of this body of work will involve going back to the origins of computing, neuroscience, machine learning and artificial intelligence. For now, we will briefly introduce the two specific technologies used in our first gallery event, Deep Dream (in partnership with Gray Area Foundation for the Arts in San Francisco, http://grayarea.org/event/deepdreamthe-art-of-neural-networks) 7. These are "Inceptionism" or "Deep Dreaming", first developed by Alex Mordvintsev at Google's Zurich office (Mordvintsev et al. 2015), and "style transfer", first developed by Leon Gatys and collaborators in the Bethge Lab at the Centre for Integrative Neuroscience in Tübingen (Gatys et al. 2016). It is fitting and likely a sign of things to come that one of these developments came from a computer scientist working on a neurally inspired algorithm for image classification, while the other came from a grad student in neuroscience working on computational models of the brain. We are witnessing a time of convergences: not just across disciplines, but between brains and computers; between scientists trying to understand and technologists trying to make; and between academia and industry. We do not believe the convergence will yield a monoculture, but a vibrant hybridity.

These are early days. The art realizable with the current generation of machine intelligence might generously be called a kind of neural daguerreotype. More varied and higher-order artistic possibilities will emerge not only through further development of the technology, but through longer term collaborations involving a wider range of artists and intents. This first show at the Gray Area is small in scale and narrow in scope; it stays close to the early image-making processes that first inspired our Art and Machine Intelligence (AMI) program. We believe the magic in the pieces is something akin to that of Robert Cornelius's tentative self-portrait in 1839.

As machine intelligence develops, we imagine that some artists who work with it will draw the same critique leveled at early photographers. An unsubtle critic might accuse them of "cheating", or claim that the art produced with these technologies is not "real art". A subtler (but still antitechnological) critic might dismiss machine intelligence art wholesale as kitsch. As with art in any medium, some of it undoubtedly will be kitsch—we have already seen examples—but some will be beautiful, provocative, frightening, enthralling, unsettling, revelatory, and everything else that good art can be.

Discoveries will be made. If previous cycles of new technology in art are any guide, then early works have a relatively high likelihood of enduring and being significant in retrospect, since they are by definition exploring new ground, not retreading the familiar. Systematically experimenting with what neural-like systems can generate gives us a new tool to investigate nature, culture, ideas, perception, and the workings of our own minds.

Our interest in exploring the possibilities of machine intelligence in art could easily be justified on these grounds alone. However, we feel that the stakes are much higher, for several reasons. One is that machine intelligence is such a profoundly transformational technology; it is about creating the very stuff of thought and mind. The questions of authenticity, reproducibility, legitimacy, purpose and identity that Walter Benjamin, Vilém Flusser, Donna Haraway and others have raised in the context of earlier technologies shift from metaphorical to literal; they become increasingly consequential. In the era where so many of us have become "information workers" (just as I am, in writing this piece), the issues raised by MI are not mere "theory" to be endlessly rehearsed by critics and journalists.

<sup>7</sup> Brillhart (2016) piece in the DeepDream show also makes use of virtual reality which, while not neural, represents an important advance in both cameras and displays.

We need to make decisions, personally and societally. A feedback loop needs to be closed at places like Google, where our work as engineers and researchers will have a real effect on how the technology is developed and deployed.

This requires that we apply ourselves rigorously and imaginatively across disciplines. The work cannot be done by technophobic humanists, any more than it can be done by inhuman technologists. Luckily, we are neither of the above. Both categories are stereotypes, if occasionally self-fulfilling ones, perpetuated by an unhelpful cultural narrative: the philistines again, claiming that artists are elves, and technical people dwarves, when of course the reality is that we are all (at least) human. There is no shortage today of artists and intellectuals who, like Alberti, Holbein or Hockney, are eager to work with and influence the development of new technologies. There is also no shortage of engineers and scientists who are thoughtful and eager to engage with artists and other humanists. And of course, the binary is false; there are people who are simultaneously serious artists and scientists or engineers. We are lucky to have several of such among our group of collaborators.

**Acknowledgments:** The author would like to thank Kenric McDowell, Jess Brillhart, Alison Lentz, Matt Jones, Mike Tyka, Alex Mordvintsev, Jac de Haan and Charina Choi for their inspiring work and useful feedback.

**Conflicts of Interest:** The author declares no conflict of interest.

#### **References**


Hockney, David. 2001. *Secret Knowledge: Rediscovering the lost techniques of the Old Masters*. New York: Viking Studio.


Zylinska, Joanna, ed. 2002. *The Cyborg Experiments: The Extensions of the Body in the Media Age*. New York: Continuum.

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