The terms “unpolitics” and “unpolitical” must be understood here in light of the distinction between politics and police that we will introduce later. Similar images of AI are certainly “political” insofar as they contribute to a certain distribution of the sensible. They are, however, “unpolitical” because the manner in which they do so is that which serves to maintain the status quo rather than undermine it.
At the end of the previous section, we have reached a possible result. Such a result would consist of formulating recommendations for stakeholders about not using images of AI like Images 1 and 2 in their science communication, and, more generally, about moderate use of visual representations of AI—moderation is commonly considered to be a virtue. In its most radical, iconoclastic version, such recommendations might consist of inviting stakeholders to not use images at all when it comes to science communication of innovation in AI. While a similar conclusion is at the opposite of our intention in this article, we believe that it is already a good result, at least insofar as it problematizes a topic—the ethics of AI images—that the literature has completely ignored. In this section, however, we want to go beyond this perspective. The thesis of this section is that images of AI like Images 1 and 2 are not unethical; or, at least, the fact of being unethical according to a referential perspective is so evident that it does not represent a true problem. Similar images are rather “unpolitical.” To demonstrate this, we use in this section the thought of the French philosopher Jacques Rancière, in particular the concepts of “distribution of the sensible” (Rancière, 2004), “disagreement” (Rancière, 1999), and “pensive image” (Rancière, 2009a).
The recourse to Rancière’s thought is not accidental here. This article is included in a topical collection devoted to “Philosophy of Technology and the French Thought.” Esposito (2018) distinguishes German Philosophy, French Theory, and Italian Thought. For Esposito, the salient feature of the first, particularly the Frankfurt School, is Negativity. In Hegel, negativity was still only a passing moment; with Adorno and Horkheimer, it becomes insuperable instead. As for French Theory, its core category is the Neutral. For example, “Deconstruction is neutral, suspended between yes and no, positioned at their point of intersection. It marks its distance both from the paradigm of crisis and that of critique” (Esposito 2018, p. 16). In either case, he says, one ends up in an impasse of thought. The Italian Thought — Esposito thinks of a tradition in political philosophy going from Machiavelli to Agamben — would instead be able to avoid this impasse, being an “affirmative thought”: “it can be argued that, by and large, the main effort of Italian philosophers has been to think not in a reactive but in an active, productive, affirmative way” (Esposito 2018 p. 17). Following this distinction (admittedly simplistic in many ways, but nonetheless useful), we assert that Rancière’s thought is properly a representative of the French Thought because, while embracing a certain critical, and even neutral, attitude of French theorists (evident especially in the notion of “distribution of the sensible”), he also embraces the affirmative attitude of Italian thinkers, as emerges especially from the concepts of “disagreement” and “pensive image.” For instance, as will be shown in the conclusion, disagreement does not coincide with mere chaos, but rather with the concrete possibility of thinking and building a new form of (technological) democracy.
Our first hypothesis is that AI images like Images 1 and 2 are “unpolitical” because they contribute to the framing of a specific “distribution of the sensible” in the technological innovation in AI. For Rancière (2004, p. 12), the expression indicates “the system of self-evident facts of sense-perception that simultaneously disclose the existence of something in common and the delimitations that define the respective parts and positions within it.” In other words, the distribution of the sensible regards the constitution of a shared time, space, and horizon of understanding, and the distribution of access and roles (that is, recognition, legitimacy, and ultimately power) within such a delimited space, time, and horizon of understanding. The distribution of the sensible, and the consequent distribution of access and roles, imply exclusions, sometimes from specific access and roles, sometimes from the whole space, time, and horizon of understanding. The distribution of the sensible is for Rancière a political practice, because “politics revolves around what is seen and what can be said about it, around who can see and the talent to speak, around the properties of space and the possibilities of time” (Rancière, 2004, p. 13). Politics and aesthetics are strongly connected, where “aesthetics” is to be understood both in the sense of the Greek aisthesis, which means “perception,” and in the sense of art and cultural productions in general. On the one hand, politics is a matter of distribution (or exclusion from) roles and access to perception—seeing/being seen, listening/being listened to, etc. On the other hand, art and cultural productions can either contribute to the reproductions of the dominant regimes of perception or contribute to their suspension and eventual transformation.Footnote 15
We contend that the dominant imagery of AI implies a specific distribution of the sensible whose ultimate effect is to mark a gap between experts and non-experts, insiders and outsiders. It has been argued that the use of images in science popularization has an introductory function. For instance, Gigante (2018) coined the term “portal images.” However, we contend that stock images of AI in science communication are “screen images,” where “screen” refers to its etymology, meaning “to cut, divide, cover, shelter, and separate.” The fact is that one can watch thousands of similar images of AI without having to develop any critical reasoning about AI. These images instead have an “anesthetic” effect, which means that the reiterated contact with them makes non-experts and outsiders less and less sensitive to the most urgent issues related to AI and increases their feelings of resignation about AI.
We propose to apply these considerations to our object of study. In particular, we introduce the notion of “anaesthetics,” a word referring to the fact that the distribution of the sensible related to similar images (aesthetics) has anesthetic effects on those who are “outside.” The concept of anaesthetics is also important for another reason. One might think that the loss in terms of both ethics and politics at the level of the single image of AI is somehow retrieved at the level of the context in which the image is used, and to which it finally belongs. Hence, a possible criticism of our discourse might consist in affirming that there is no ethics or politics of similar images per se, because similar images are always used in context, and the ethical or political assessment should be made not on the single image, but with regard to the whole context. To put it plainly, science communication on AI is full of ugly and bad images, yet these images can still be used ethically or politically whenever they are integrated into a rigorous discourse. However, such criticism not only forgets that in the media environment in which we live, images are most often detached from, and perceived outside from, their context. Think of how often we content ourselves with scrolling the home screen of our news feeds without actually reading the article or even the titles. This criticism also forgets that similar images can, through their “force,” anesthetize the communicational context in which they are supposed to be embedded and on which they are supposed to depend.Footnote 16
Our second hypothesis is that stock images of AI are also unpolitical because they impede or anesthetize any form of “disagreement.” Above, we have argued that politics has to do with the distribution of the sensible. However, on other occasions, Rancière proposes distinguishing more carefully between politics and police. We might say that the distribution of the sensible as a form of domination is related to the police, while politics in a proper sense is rather related to the practice of disagreement, which can also be understood as a suspension of the dominant distribution of the sensible. Rancière (1999, p. 29) defines the police as “an order of bodies that defines the allocation of ways of doing, ways of being, and ways of saying […]; it is an order of the visible and sayable that sees that a particular activity is visible and another is not, that this speech is understood as discourse and another is noise.” He defines politics as “an extremely determined activity antagonistic to policing: whatever breaks with the tangible configuration whereby parties and parts or lack of them are defined by a presupposition that, by definition, has no place in that configuration” (Ibid.). He also says that “political activity is whatever shifts a body from the place assigned to it or changes a place’s destination. It makes visible what had no business being seen and makes heard a discourse where once there was only place for noise” (Rancière, 1999, p. 30).
Politics in a proper sense implies the possibility of disagreement, which is neither ignorance nor misunderstanding. Disagreement is neither a matter of teaching to others what they do not know yet, nor is it a question of explaining more, to allow better understanding. Disagreement is somehow more radical: it is “a specific type of speaking situation (situation de parole): one where one of the interlocutors does not hear what the other is saying. Disagreement is not the conflict between the one who says white and the one who says black. It is the conflict between the one who says white and the one who says white but does not hear the same thing” (Rancière, 1995, p. 12. Translation is ours).Footnote 17 Police anesthetize disagreement and promote consensus, but the consensus is nothing but the disappearance of politics.
Let us now apply these ideas to the use of stock images and the like in science communication about AI. We already said that stock images are usually characterized by their generalized and stereotyped way of representing reality. These images regard the imaginaries, that is, the fears and hopes, enthusiasms, and hostilities about AI that the concerned group of non-experts (but also experts, insofar as experts are not constantly reasoning and acting as experts) has about AI. Stock images and all sorts of popular representations of AI might be considered public arenas that attract different audiences trying to cope with AI despite its inaccessibility and “black-boxness.” However, this is still a desideratum, because many stock images of AI currently have little to do with disagreement. On the contrary, one can say that they anesthetize disagreement by promoting forms of consensus about the general hopes and fears about AI.
A general optimism permeates the visual representations of AI one can find on the online catalogs of stock image providers like Getty Images and Shutterstock. For instance, Image 3 is the first result for the quest “facial recognition AND Artificial Intelligence” on the search engine of Getty Images (December 2020, options “most popular” and “creative”). This image, titled “Businessman using face recognition outdoor” and authored by Wonry, has no alarming element, although facial recognition is a much-debated topic in AI ethics precisely because of its potential risks.Footnote 18 Rather the image recalls progress, future, and, we could even say, quiet and security. Even when pessimism emerges, for instance via more explicit searches, stock images tend to represent it as a caricature, as if the quest for differentiation and opposition were more important than a real engagement with the issue. Image 4 is the first result for “war AND Artificial Intelligence” on the search engine of Getty Images (December 2020, options “most popular” and “creative”).Footnote 19 Two robots (one of them recalls the ED-209 villain robot of the movie RoboCop) and a drone are represented in what looks like to be a post-apocalyptic environment. Incidentally, the alarming red color of the image opposes the reassuring blue color that dominates the current popular imagery of AI.
In the past years, some efforts have been made by stock image providers to promote different visual representations of social reality. For instance, in 2016, Getty Images, in collaboration with Women’s Sport Trust, launched a new collection on its online catalog called “Sporting Women,” whose aim is “increasing the visibility of female athletes” and “challenging the way female athletes are portrayed in imagery.”Footnote 20 Citizen Stock is an attempt to produce generic images from “real people.” The initiative is presented as follows: “Citizen Stock was launched in May 2010 as a source of new images […] depicting real people. Models are not role models at all, but children, moms, dads, grandparents, skateboarders, lawyers, teachers, musicians […] and small business owners […].”Footnote 21
Our third hypothesis is that a similar initiative might be undertaken in what concerns stock images of AI, and more generally stock images of science and technology.Footnote 22 In particular, we believe that more engaged imagery of AI could be created not so much following the classic urge for reference, but rather pursuing what Rancière has called the “pensiveness” of the image. According to the French philosopher, “a pensive image is […] an image that conceals (recèle) unthought thought, a thought that cannot be attributed to the intention of the person who produces it and has an effect on the person who views it without her linking it to a determinate object” (Rancière, 2009a, p. 107. Translation modified).Footnote 23 Among the several examples, he considers the famous 1865 photo by Alexander Gardner of the sentenced-to-death Lewis Payne.Footnote 24 The pensiveness of this photography depends on the tangle between several forms of indeterminacy: (1) The one concerning the visual composition: we cannot know if the position—Lewis Payne is seated according to a highly pictorial arrangement—has been chosen by the photographer or not. We do not even know whether the photographer has simply recorded the wedges and marks on the wall, or whether he has deliberately highlighted them; (2) The one concerning the work of time: the body, the clothes, the posture of Lewis Payne are at home in our present, yet the texture of the photograph bears the stamp of times past; (3) The one concerning the attitude of the character: we know that Lewis Payne is going to die, but we cannot read his feelings in his gaze.
It might be thought that the pensiveness of the images depends exclusively on our ignorance and the resistance of the image to be interpreted—for instance, when its provenance or the thought of its author is unknown. However, Rancière insists on the fact that pensiveness rather depends on the capacity of the image to bring together different regimes of expression without homogenizing them. He talks, for example, of “dis-appropriate similarity” (Rancière, 2009a, p. 129), which is more than mere juxtaposition and yet less than identification. In other words, images are pensive insofar as they form always-open and never-exhausted metaphors on different spatial and temporal levels.
The concept of the pensive image is particularly interesting because it detaches the possibility for an image to be pensive from the need for it to be adherent to the reality it represents. Whether adherent to reality or not, an image can be thoughtful to the extent that it can provoke thought in the spectator. The presence of multiple planes, spatial and temporal, of interpretation, in short a metaphoricity intrinsic to the image itself, is what allows it to be pensive. Now, why are the AI stock images we have considered not pensive? Precisely insofar as they direct thought in a unique direction, for example, hope, fear, or trust. Without going into the details of the analysis, we can consider again the abundant use of a calming, anesthetizing color like blue as an example.
The paradigm through which Rancière builds his notion of a pensive image is art. We believe as well that artistic productions today offer several possibilities for visually representing AI beyond the usual clichés, and without much concern for the reference to the technical artifact. Let us consider the robotic sculpture Black Box by the French artist Fabien Zocco.Footnote 25 Robotic black cubes move slowly on the ground. Their movements let a sort of enigmatic behavior emerge, lending a semblance of life to these minimalist artifacts. Black Box thus aims to give substance to the often used, but less often thought of, metaphor of the “black box,” which in the ethical discourses on AI indicates the inaccessibility to the internal functions of a system such as a machine learning algorithm. This work does not refer to AI as a collection of techniques and technologies—we do not know how the black boxes move. It rather refers to AI as an imaginary, which is, however, not anesthetized according to the easy opposition between fear and hope. Black Box inspires both fascination and uncanniness, attraction, and repulsion. The black boxes move, they behave and seem alive, and yet they cannot be understood. A second example is the Anatomy of an AI System by Crawford and Joler,Footnote 26 whose goal is to present Amazon Echo as “an anatomical map of human labor, data and planetary resources.” We believe that this map can be approached from two different levels. The first one is the level of representativeness. For instance, one can download and read the map in its details to have a better understanding of AI not in isolation, but rather in its multiple human and environmental implications. The second other one consists of perceiving the map as a whole. In this second case, the spectator is taken by a kind of vertigo, given the complexity and the many dimensions that are suggested by the opening of the AI black box — like the opening of a human body and the arrangement of all its internal organs. The effect, after all, is not unlike that of the Black Box. Certainly, this latter work extremizes opacity, while the other one extremizes “monstration.” Yet, in both cases, it is a matter of problematizing AI and our daily relationship with it.
We believe that the main challenge for the ethics of AI images would consist of going beyond the limits of the artistic (and hence most often elitist) production to import the pensiveness of works like Black Box and the Anatomy of an AI System in more popular contexts, in particular in the context of the production of stock images about AI, and science and technology in general.