Stupidity: Human and Artificial

NATASHA LUSHETICH

University of Dundee, UK

 

Abstract

In this brief commentary, I trace the ‘development’ of stupidity from human (individual and social) stupidity, via technologically and heteronomically facilitated stupidity, to the more recent human-artificial variant in an attempt to define the difference between human-artificial stupidity, ‘milintelligence’, and artificial intelligence.

Keywords

stupidity, automation, AI, Durkheim, Stiegler, Malabou

 

In a highly amusing book entitled La bêtise s’améliore (Stupidity is Improving), Belinda Cannone argues that stupidity is becoming increasingly sophisticated. Concerned with human, rather than artificial stupidity, the book sheds light on the reductionist appropriation of complex ideas by grossly oversimplifying or ‘stupidifying’ them (Cannone, 2007). This, in itself, is neither strange nor new. Revolutionary, avant-garde, or subcultural ideas are regularly recycled in and by mainstream culture, or else turned into a mere signifier. To many, Che Guevara is an intense-looking bearded figure from T-shirts. More interestingly, Cannone addresses the multiplication of stupidity, the fact that reductionism, which flattens complex propositions that resonate in eighteen or more different fields, into a single (and, usually, the most banal) one, is now possible in many spheres simultaneously – the implication being that stupidity is spreading like a viral disease (Cannone, 2007). At first sight, the proliferation of communicational channels and automated processes seems like the most likely reason for this. If we imagine a successful artwork, which, by definition, resonates in the symbolic, aesthetic, formal, thematic, cultural, perhaps also metaphorical, philosophical, anthropological, historical and/or educational realms – and reduce this complex interplay of factors to a single parameter, a question like ‘how much does it cost?’, a justification such as ‘in order to list 100 million artworks on different platforms, we need to limit their description to a single simple parameter’ may seem like a feasible reason for reductionism. But is ‘quantity over quality’, or ‘simplification as the inevitable part of massification’ the only reason? Or does the widespread use of what is usually referred to as ‘artificial intelligence’ breed new forms of human-artificial stupidity?

 

Individual and Social Stupidity

Human stupidity is, without a doubt, a historical force to be reckoned with. Already in Karl Marx and Friedrich Engels, it is a great power in the making of history (Marx and Engels, 1965). Usually associated with inertness, slow-wittedness, and the petrification of thought, stupidity exhausts knowledge. However, it should not be confused with idiocy. Idiocy, which, etymologically, comes from the same root as idiosyncrasy, refers to a particular mixture of bodily humours. The idiot is by definition insensitive to the norm. For some philosophers, such as Byung-Chul Han, idiocy is the very condition of philosophy: ‘[e]very philosopher who has brought forth a new ideation – a new language, a new way of thinking – has necessarily been an idiot. Only the idiot has access to the wholly Other’ (Han, 2017: 81).

Stupidity, on the other hand, is inseparable from conformism, the unquestioning adherence to the norm, or to oversimplified ‘verities’. It is both produced by and productive of inattention, automatic piloting, blind repetition, and carelessness. It is also diametrically opposed to memory and the ‘depth of field’ implied by memory – the perpetual re-appraisal of past knowledges in light of new ones. This doesn’t mean that new patterns and inter-relationships cannot be gleaned from what Franco Moretti has called ‘distant reading’, the opposite of ‘close’ or ‘deep’ reading (Moretti, 2013). A machinic comparison of the illuminated sections of hundreds of thousands medieval manuscripts is bound to reveal new insights. Nor does it mean that distant (machinic) reading cannot produce depths of a different kind, such as a semantic relationship between the illuminations’ colour and the scribe’s school of thought. Rather, it means that the ‘depth of field’ implied by human memory is inseparable from judgment, seen, in Kantian vein, as an activity that links all the faculties of the mind, including analysis, comparison, (re)-appraisal, perception and imagination (Kant, 2007).

In eliminating difference, change and otherness, stupidity, by contrast, turns repetition into a form of dwelling. On an individual level, this ‘stasis’ is the result of the inability to learn from experience, demonstration, or proof. On a collective level, the circular return to the already established, often in the form of imitative, empty signs, ‘cements’ sameness into a form of aggressive homeliness. Yet, as Jacques Derrida has noted, even the most intelligent and knowledgeable person will occasionally catch themselves doing something really stupid, usually because they are not paying attention (Derrida, 2008: 192). This means that stupidity cannot be defined by intent, despite its apparent systematicity. Rather, it is a failure of judgment bound to involuntary acts. For Roland Barthes, stupidity is the very base of intelligence as the first thought that comes to mind, on any topic, is invariably stupid (Barthes, 1955: 253). For an intellectual – a professional thinker, who, we could say, depends on the ‘depth of field’ – it is a subterranean force ready to erupt at any moment, much like chaos lurks beneath all forms of order, natural or social. Worse still, for Barthes, stupidity is a ‘thing’ that persistently evades symbolisation: a stubborn, immutable obstacle (253).

Indeed, in Yiddish, the expression for a question or utterance of unspeakable stupidity that astounds everyone and destroys the possibility of further dialogue is klots kashe – a tree trunk that falls in the middle of the road and can neither be removed nor circumvented. In other words, stupidity is a social problem. While an intelligent yet malevolent person works to their advantage and to the disadvantage of (specific or nonspecific) others, a stupid person works to everyone’s disadvantage, their own included. Their actions have social repercussions which is why it’s important to understand stupidity both as an existential structure that fixes behaviours and a drive to closure. To a degree, all social systems enclose. However, they also evolve. Stupidity, by contrast, is fixed and fixing, yet performative. Stupid statements may be devoid of all content yet they nevertheless shape social reality, as the klots kashe example shows. Despite the fact that stupidity institutes itself performatively in and through repetition, nothing is ever learnt from repetition. No change is possible. On the contrary: the more a statement is repeated, the more it forecloses thought and turns every thing and every place into generic blandness. Generalisation, equivalence, and systematicity are stupidity’s main modi operandi. As an iterative social phenomenon, based on the reduction – and denial – of knowledge, it is a collective passion for superficiality, sameness, and the status quo however counterproductive they may be.

 

The Socio-Technical Evolution of Stupidity: A Brief Sketch

The insistence on superficiality, sameness, and the status quo constitutes what may be called ready-made stupidity. This brand of stupidity doesn’t deny specific-domain knowledge, or thought. It operates as a generic, cross-temporal and cross-generational practice of what Émile Durkheim has called the ‘refusal to think’ (Durkheim, 1960: 62). Differentiating between societies of organic and mechanical solidarity, Durkheim suggests that in societies of organic solidarity (where labour structures are not dictated by heteronomy as an externally imposed, pre-formed organisation of labour), individuals are individualised; in societies of mechanical solidarity, or industrial societies (where both the collective and social consciousness are based on heteronomic modes of production, consumption, and equivalence), individuals are de-individualised (54–62). This means that they are socialised into a standardised form of collective consciousness, where individual personalities do not arise from a dynamic relationship with the environment and other individuals, comparable to the above-mentioned ‘depth of field’ dynamic, but from the sum total of pre-formed, pre-scripted functions they perform in different social contexts. If we take the example of an industrial worker, they read the newspaper on the train to work in the morning, punch the clock card upon arrival, execute self-same actions all day long, chat to the cantina cook with the same level of familiarity, take the train home, watch the news while eating a pre-cooked dinner, after which they retreat into a pre-scripted universe of private consumption or ‘free time’ activities suggested by advertising such as bodybuilding. The reason why, for Durkheim, sociality in industrial societies equals the practice of non-thinking is that direct engagement with any potentially new situation is replaced by prefabricated structures. Individuals here live in a pre-thought world. The different forms of solidarity, as Durkheim calls them, have far-reaching effects. The many different states of consciousness that exist in societies of organic solidarity have a mutually weakening effect. Identical ones, which exist in societies of mechanical solidarity, have a mutually strengthening effect. This is why, for Durkheim, the distinction between the two kinds of society is not about whether a person possesses – or could hypothetically possess – an inalienable individuality, but about the social sphere where entire domains of action are automated and pre-thought (66). The field of the possible is fixed, as is the relationship between all of the field’s elements. Meaningfulness is derived from systematisation. The refusal to think is the foundation of sociality: thinking is replaced by automated logics in which only the initial principle or equation is thought through; the rest is not. The rest is merely brought into alignment with the initial principle or equation.

A degree of stupidity is therefore unavoidable in modernity and post-modernity. Indeed, Avital Ronnell could not be more right when she says that ‘stupidity is an indelible mark of modernity’ and ‘our symptom’ (Ronell, 2006: 27). In fact, Durkheim’s diagnosis is very similar to Gilles Deleuze’s, for whom de-individuation is wedded to technological standardisation and its attendant modes of control. Deleuze uses the expression ‘dividual’ to articulate the difference between the processes of individuation characteristic of Michel Foucault’s disciplinary society to what he calls the society of control: ‘the numerical language of control is made of codes that mark access to information or reject it. Individuals […] become dividuals […] samples, data, markets or “banks”’ (Deleuze, 1992: 5).  In its more contemporary use, ‘dividual’ also suggests specific ‘processes of [technological] participation’ (Ott, 2018: 35) that are inseparable from the automation of memory.

As Bernard Stiegler has argued, all technical objects – the camera, the telephone, the computer, and their modes of practice – constitute an intergenerational support of memory, which, as material culture, determines learning, behaviour, and mnesic activities. A newborn child arrives into a world where ways of being, experiencing, and memorising are already grammatised. This means that the neurochemical activity is already inscribed in the neurobiological substrates of memory and knowledge, which are in turn inscribed in cultural history. The process of grammatisation is one of ‘discretisation’; it isolates ‘the gestures of producers’ with the aim of ‘making possible their automatic reproduction’ (Stiegler, 2010: 33). Perception and experience are here over-written by techno-cultural practice, which in turn over-writes the ‘affective activity of the nervous system’ (33). This further leads to ‘proletarianisation’ – a word Stiegler uses for the process of ‘the loss of knowledge(s) as savoir-faire and savoir-vivre, in the absence of which all savour is lost’ (30). This loss of savour, which is not only the loss of sensorial and intellectual knowledge, but also the loss of idiosyncratic desire, further links the practice of the refusal to think to technological modifications of the political and the economic through parrhesia and ostentatious additivity.

Parrhesia is the externalisation of the speaker’s truth claim. As Foucault notes, in ancient Greece, it ‘was a guideline for democracy as well as an ethical and personal attitude characteristic of the good citizen. Athenian democracy was defined very explicitly as a constitution (politeia) in which people enjoyed demokratia, isegoria (the equal right of speech), isonomia (the equal participation of all citizens in the exercise of power), and parrhesia. As a requisite for public speech, parrhesia takes place between citizens as individuals, and also between citizens construed as an assembly’ (Foucault, 2003: 122). It is a practice and a right that regulates personal, interpersonal, and intrapersonal conduct. Ostentatious additivity – the amassment of goods – stems from Max Weber’s paradigm laid out in The Protestant Ethic and the Spirit of Capitalism (Weber, 1992). Here, the Protestant work ethic – answering the call of ‘duty’ – is paired with virtue, as is all goal-oriented action. Virtue is inseparable from success, and success is inseparable from the amassment of material attributes that are both quantifiable and cumulative. By tirelessly displaying the fruits of her labour in the form of accumulated worldly possessions, the early capitalist, like the Protestant believer, sought to display, and, in this way, authenticate predilection – the status of being chosen by her god (Weber, 1992). At the same time, the coveted status of divine predilection is manifested in no other way but through the accumulation of wordly possessions.

This paradoxical, performatively inaugurative relationship of action to cause and effect is at the heart of data-driven transparentisation, where the public externalisation of one’s thoughts combines with the ostentatious amassment of statements-and-people-cum-goods, whose function is quintessentially performative. As Jodi Dean has noted in her analysis of communicative capitalism, the value of communication lies not in content, but rather in additivity, in the comments or statements’ ‘capacity to circulate, to be forwarded, counted’ (Dean, 2013: 66). This additive value is based on ‘fundamental communicative equivalence’: facts, theories, judgments, opinions, fantasies, jokes, lies ‘all circulate indiscriminately’ (66). What matters is not what is said but that something is said, and that this ‘something’ circulates and stimulates further communication-cum-circulation. In the political and socio-economic sphere, technologisation is a process of easification and acceleration, but also one of vectoralisation that perpetually re-organises informational flows along different axes (Wark, 2019). This weds subterranean machinic processes to indiscernible yet performatively efficacious forms of reduction. Although data science, the main method behind these processes, is usually seen as neutral, it is, as Dan McQuillan has pointed out, a neoplatonic ‘organising idea’, which, in revealing ‘a hidden mathematical order in the world that is superior to our experience’, perpetuates thoughtlessness (McQuillan, 2018: 264).

McQuillan’s use of the word ‘thoughtlessness’ is a reference to Hannah Arendt’s observation of Adolf Eichmann’s actions during his 1961 Jerusalem trial for genocide. Arendt’s labelling of what is, in fact, a ‘retreat into procedure’ – a legal move designed to distance the defendant from the indictment (increasingly used by neoliberal managerial structures too) – as ‘thoughtless’ presupposes oversight and responsibility. Indeed, McQuillan’s use of the word refers to human-machinic, rather than machinic ‘thoughtlessness’. However, the problem of the Durkheimian mechanical-automated refusal to think is not related only to data science, or dataism. It’s embedded in a long history of automated content-less-ness whose performative effect shares many ‘methodological’ similarities with human stupidity, namely the elimination of difference, the imposition of aggressive reductionism, and the systematisation of both. Given that ‘artificial intelligence’ is not an algorithmic variation on human consciousness, as authors such as Niels Nilsson have suggested (2010), but the digital systems’ ‘ability to make generalizations’ based on ‘limited data’ and ‘iterative sequences’ (Kaplan, 2016: 5–6), stupidity is, to a degree, ‘baked into’ AI, although, as Joe Davidson humorously put it, it’s important to understand the context of this expression: ‘[w]hen you’re fundraising, it’s Artificial Intelligence. When you’re hiring, it’s Machine Learning. When you’re implementing, it’s logistic regression’ (Davidson, 2018: np).

I don’t mean to say that there is no intelligence in artificial intelligence, as some, such as McQuillan, have suggested, purely because machinic intelligence doesn’t learn the way humans do (McQuillan, 2018b: np). What McQuillan has in mind is a ‘depth-of-field’ notion of intelligence, where humans can easily discern the formation of new conclusions emerging from a re-examination of past knowledges in light of new propositions. But this point of view is predicated on human temporality, not of a single human, but of humans as a species, neither of which can perceive temporally extremely diffuse or extremely condensed processes. In this respect, I agree with Benjamin Bratton for whom the intelligence in AI is vastly different from human intelligence and therefore must be evaluated on its own terms (Bratton, 2021).

In order to advance the discussion – and awareness of – stupidity in the age of AI, it’s important to differentiate between artificial stupidity, artificial milintelligence (military intelligence) and artificial intelligence proper. The first category consists of two subcategories: under-informed and inconsistent programming and over-determination. While human stupidity and its repetitive reductionism are, without a doubt, exhausting and exasperating, they can nevertheless be amusing. I’ll borrow an example from the Italian comic Dylan Dog where the protagonist, Dylan Dog, is trying to reach the chief inspector of Scotland Yard, Bloch, also called the ‘Old Man’, but his efforts are thwarted by Bloch’s proverbially stupid assistant Jenkins:

DD: Can I speak to the Old Man?

J: I’m sorry I can’t help you; there are no old men here. Police employees are asked to retire at a certain age. They leave the force before they get old.

DD: No, I don’t mean any old man, I mean the Old Man – Bloch.

J: Oh, why didn’t you say so? I’m afraid that Bloch is not here.

DD: I see. Would you be able to give me his mobile?

J: I’m afraid not. If I give it to you, he won’t have it. I’m not sure that I’m authorised to do that.

DD: No, I don’t mean his mobile phone, I mean his mobile phone number… Never mind, please just ask him to call me when you speak to him.

J: I will but you won’t hear him you if you’re far away. Where are you?

DD: No, I meant ‘call’ as in ‘phone’, not call as in shout…Never mind, I’ll try to reach him some other way. Thank you, Jenkins (Sclavi, 2009: np).

Jenkins excels at creatively misunderstanding the obvious, which makes the conversation both absurd and unnecessarily longwinded. A similar detour is present in many poorly programmed applications with systematic inconsistencies or illogical differences. For example, we have all been faced with online forms, where, in one part of the form, the country usually referred to as the ‘United Kingdom’ is found neither under ‘U’ for ‘United Kingdom’, nor under ‘G’ for ‘Great Britain’ but under ‘B’ for ‘Britain’. Likewise, the currency is found neither under ‘B’ for ‘British pound’ nor ‘P’ for ‘Pound Sterling’ but under ‘S’ for ‘Sterling’, which requires scrolling through endless menus in the hope of deciphering the programmer’s particular brand of ‘creativity’.

This is very different from purposefully sought unpredictability, which, in artistic practice, goes by the names of chance operations and stochastic procedures. The purpose of both is to provoke non-anthropocentric reactions in objects, instruments, surfaces, and materials, unencumbered by human taste, education, and habit. For example, experimental composer Brian Eno, known for his autonomous music-composing systems, calls the system’s aptitude to produce something other than which it’s programmed for ‘artificial stupidity’ (Eno quoted in Beer, 2016). However, his use of the word ‘stupidity’ implies a limited notion of intelligence as the ability to execute the programmed. I would suggest that intelligence proper (but not milintelligence), in humans and other-than-humans, algorithms and machines included, is the very opposite of executing the programmed. It’s a subtle dance (rather than a linear operation) with novel (in other words: unknown) complexity (Lushetich, 2021).

The second category of artificial stupidity is more native to algorithmic procedures, although it still has humans ‘in the loop’, namely over-determination. Over-determination is the application of shortcutting algorithmic procedures to complex decision processes, which create what could be called ‘future from structure’ by turning possibilities into probabilities, and probabilities into mathematical-logical ‘necessities’. In everyday life, over-determination can be felt in ‘automatic’ bank account termination and ‘automatic’ health insurance claim or loan application refusals. Over-determination is also a form of machinic enunciation, a variation on (human) authoritarianism, minus the human agent: ‘you will either use the grossly reductive online form or you will not be able to submit your health insurance claim’. Or: ‘despite the fact that the decision to reject your loan application was arrived at using oversimplified, and therefore inaccurate parameters, the decision is irrevocable’.

Artificial milintelligence is, for its part, essentially a target machine concerned with understanding the enemy’s whereabouts, movements, and practices. Its purpose is to translate information into actionable knowledge and strategic advantage. Artificial milintelligence is not entirely separate from stupidity either as it forces order on disorder, often by extremely violent means. We could, of course, say that all algorithmic operations are rooted in disorder, in the sense of Claude Shannon’s information theory, which doesn’t apply to the individual message but to signal crafted from noise (Shannon, 1949). However, artificial milintelligence is equally related to Robert Musil’s notion of stupidity, which he describes variously as ‘a person who has lost his head’ and ‘an insect that bumps against the closed half of a window until by accident it “plunges” through the open half to freedom’ (Musil, 1990: 279). Both examples are, for Musil, the epitome of military strategy because they ‘“saturate” a target with a volley’, ‘sweeping fire’, ‘shrapnel or grenades’ (279).

Similar to over-determination mentioned above, this form of ‘intelligence’ which forces order – as an oversimplified, often violent solution – on disorder or indistinction, is also used in business and sport. It goes without saying that this sort of intelligence is limited to operations of the ‘goal-action-result’ kind, and is, in this sense, the antithesis of critical intelligence (in fact, for Musil, business as such is aligned with a lack of critical intelligence). For example, AlphaGo won the 2016 go match against the world champion Lee Sedol because of its capacity to peruse millions of go games, and discern unusual moves, those most likely to confuse the opponent. Artificial intelligence proper, by contrast, is not about the ability to search billions of databases in a span of a few hours, or even find incrementally different, more efficient ways of achieving the same goal. It’s about the ability of an automated process to produce something new. This notion of intelligence is related to the second meaning of the word ‘automatic’, namely: ‘all by itself’, as employed by the Surrealists in automatic drawing and writing, the purpose of which was to access and manifest a different, hidden reality – or surreality.

Indeed, as Gilbert Simondon argued over fifty years ago, ‘the true perfection of machines does not correspond to an increase in automation [seen as repetitive sameness] but ‘to the fact that the functioning of a machine harbours a certain margin of indetermination’ (Simondon, 1958: 48). Today, both the proponents of (human and artificial) neural plasticity, such as Catherine Malabou, and the proponents of ‘alien thought’, derived from Joseph Weizenbaum’s observation that machinic operations cannot not be alien when applied to human matters (Weizenbaum, 1976), such as N. Katherine Hayles (2017), have argued that there is an internal dynamic operating in axiomatic systems and procedures. In broad terms, this argument is based on the fact that much of machinic feedback today is not circular but spiral and recursive. Likewise, processes such as unsupervised training and learning, back propagation, de- and re-aggregation, do not create more of the same. They produce perpetual change.

Precisely what perpetual machinic change is, at this point in AI development, open to debate. Authors such as Malabou have convincingly shown that intelligence is primarily an operation, action, and process, regardless of agent – human, vegetal or machinic – and that the chief function of intelligence is continual re-combination and re-articulation (Malabou, 2019). This action-orientated notion of intelligence – seen not as an innate disposition or a programmed ability, but as a process that ‘unfurls continuously’ – is indebted to Jean Piaget’s interpretation of equilibrium as a ‘mobile point of stability’ (Piaget quoted in Malabou, 2019: 10) and to John Dewey’s ‘method’ (2008 [1929]), seen as a ‘constant adaptation in time’ (Malabou, 2019: 12).

What such a dynamic shows is very different from automatism as aggressive repetition, namely the Möbius-strip-like relationship of design to chance, rule to iteration, and otherness to identity (Lushetich, 2021). At this point in time, it’s important to define artificial intelligence against the backdrop of human-artificial stupidity in a reverse gesture (human stupidity is usually defined against human intelligence), in order to fully understand AI’s ability to bring novel re-articulations of the world into that world. Although both artificial stupidity and artificial milintelligence are variations – and, in fact, further elaborations of – human stupidity, enforced through prefabricated and automated functions, artificial intelligence proper, like other-species intelligence, reveals variations on automatisms with which artists from the beginning of the 20^th century to the present day (the avant-garde, neo-avant-garde, and the more recent ‘dirty new media’ movement) have sought to overcome human logics and perception, however without – and this is crucially important – a common denominator or unifying trope such as superintelligence (Bostrom, 2014).

 

References

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Natasha Lushetich is Professor of Contemporary Art & Theory at the University of Dundee, and AHRC Leadership Fellow. Her research is interdisciplinary and focuses on intermedia and critical mediality; global art and the status of sensory experience in cultural knowledge; biopolitics; datafication and performativity. Her books include Fluxus: The Practice of Non-Duality (Rodopi/Brill 2014); Interdisciplinary Performance (Palgrave 2016); The Aesthetics of Necropolitics (Rowman and Littlefield 2018); Beyond Mind – a special issue of Symbolism (De Gruyter 2019); Big Data – A New Medium? (Routledge 2020), and Distributed Perception: Resonances and Axiologies (co-edited with I. Campbell) (Routledge 2021).

Email: n.lushetich@dundee.ac.uk