Star computation scientist Stephen Wolfram has said\u00a0that in order to accelerate the capacity of artificial intelligence towards a much more powerful artificial\u00a0general<\/em>\u00a0intelligence (whatever that might be), it is first necessary to \u201cdetermine\u201d the main \u201csymbols\u201d of \u201cour civilization\u201d\u00a0(Wolfram 2023). These \u201csymbols\u201d should act as more abstract algorithmic categories or \u201cpockets of reducibility\u201d (ibid.), that is, as computational shortcuts that would allow data to be more rapidly and efficiently processed within \u201cneural nets\u201d (which is the brain-inspired name given to current AI algorithmic structures). Determining and mathematically codifying the \u201csymbols\u201d of \u201cour civilization\u201d would add a more abstract dimension to computational taxonomies, an overarching algorithmic layer that could enhance the capacity of current AI systems and allow them to rapidly process and articulate data without being \u2018slowed down\u2019 by the minutiae of real-life and difficult-to-classify nuances. The endeavor sounds ambitious and intriguing, but it also invites some urgent questions, such as: What is \u201cour civilization\u201d? What should its \u201csymbols\u201d be? And, above all,\u00a0who<\/em>\u00a0could \u201cdetermine\u201d them?<\/p>\n What computer scientists mean by \u201cour civilization\u201d or its \u201csymbols\u201d surely differs from how people in anthropology, history, and related disciplines understand these terms. To begin with, the latter recognize the existence not of\u00a0one<\/em>\u00a0but of\u00a0many civilizations<\/em>. Also, at least among anthropologists, there is unease with the not-so-clear context outlined by the pronoun \u201cwe\u201d\u00a0(Chua and Mathur 2018). The \u201cour\u201d in \u201cour civilization\u201d makes for a fuzzy and problematic positionality.\u00a0Moreover, the hasty treatment of the notion of \u201ccivilization\u201d is but a reverberation of how \u201cwe\u201d understand the very idea of \u201cintelligence<\/a>\u201d. It is thus of vital importance that we revisit and, perhaps, reclaim, the concepts that drive the current boom of artificial intelligence.\u00a0<\/p>\n In this short commentary, I argue that\u00a0<\/strong>some of the currently proliferating computational narratives are running \u201cwild\u201d in the sense that they seem to be\u00a0out of control<\/em>\u00a0in their blatant appropriation and reduction of central terms and analogies from cognitive or social sciences and the humanities.\u00a0\u00a0These narratives\u00a0not only involve conceptual appropriations but also enable new forms of concentration of epistemic and technopolitical power. I suggest contesting and even taming wild computational narratives by resituating key terms in a radically pluralistic and open-ended world, a world still full of in-flux civilizations, irreducible intelligences, and incomputable possibilities.\u00a0<\/p>\n Recursive asymmetries<\/strong><\/p>\n The path toward the so-called artificial general intelligence is often depicted as one leading to a \u201csuperintelligence<\/a>\u201d of sorts. The superlative makes the asymmetry obvious. It is not only assumed that machine intelligence will be superior to that of humans. It is also that this grand computational achievement is designed by a handful of scientists and business people in elite and mainly Western research institutions and companies. These people imagine and design technologies according to their own definitional parameters for \u201ccivilization\u201d, \u201cintelligence\u201d, and their superlative versions. And this, without much cultural self-reflection, or attention to historical precedent. The iteration of \u201csuperintelligence\u201d resonates, in fact, with old affirmations of the superiority of Western soul, civilization, culture, or rationality. In the age of computation, artificial intelligence emerges as the new bible, the ultimate script or tool that all humans should embrace.\u00a0Here is where the supposedly futurist scenario of \u201csuperintelligence\u201d reveals itself as the potential repetition of an unfortunate gesture of the past, a colonial move that involves the erasure of the Other. In other words, AI could\u00a0become yet another techno-hegemonic venture built on Western epistemic principles.<\/p>\n The problematic move is how \u201cintelligence\u201d is conceptualized\u00a0[\u2026],\u00a0and not just how it becomes mathematized in a given algorithmic structure.<\/p>\n<\/blockquote>\n From a cultural and historical perspective, the current unfolding of AI from technocapitalism (not AI as a cybernetic achievement) could be seen as the culmination of what philosopher Yuk Hui calls \u201csynchronizaton\u201d\u00a0(2019), that is, a reduction of the diverse human \u201ccosmotechnics\u201d (encompassing the intermingling of cosmologies and technologies)\u00a0\u00a0to a Western, and now globalized, technoscientific cannon. Hui rightfully suggests that the challenge lays not\u00a0in rejecting AI, but\u00a0in ensuring sufficient heterogeneity of technologies (i.e. of the \u201cartificial\u201d) for granting cross-cultural and cross-civilizational \u201ctechnodiversity\u201d\u00a0(Hui 2020). I would add that we also need an explicitly pluralistic and\u00a0down to earth<\/em>\u00a0framework for the very idea of \u201cintelligence\u201d.\u00a0The problematic move is how \u201cintelligence\u201d is conceptualized\u00a0(something at which Hui himself hints),\u00a0and not just how it becomes mathematized in a given algorithmic structure.<\/p>\n I highlight \u201cdown to earth\u201d to make an important distinction. Yuk Hui suggests that\u00a0the recursive self-organization of contemporary systems of computation challenges the separation between mechanisms and organisms that has defined Western philosophy (and technology) for centuries. Inspired by the practical and epistemic possibilities unveiled by the field of cybernetics, current digital machines do not operate in linear, mechanistic logic, but with recursive algorithmic loops that enable them to constantly revise, reattune their responses, and, in a sense, re-configure themselves in a contingent manner. This constitutes, according to Hui, a sort of machine vitalism that requires that we go beyond the organisms \u2013 machines\u2019 duality.\u00a0<\/p>\n Cybernetics have brought machines to another level of autonomy and agency, but they are still a key part of human strategies of power accumulation. Since their inception, machines have served to redistribute energy, time, and space for the benefit of a few\u00a0(Hornborg 2001). From an economic, political, and ecological point of view, machines have not only enabled or reproduced the asymmetries of the modern era, they have also created\u00a0new<\/em>\u00a0forms of inequality. An example of what AI may create is a world where automation takes away not only the space of factory workers but also the labour involved in many intellectual and creative professions. Translators, programmers, graphic designers, and the like will perhaps find new ways of working, but everything suggests that AI\u00a0will not undo the divide<\/a>\u00a0between the mightiest and the more vulnerable.<\/p>\n We should neither underestimate the history, nor the politics that technologies embody. Thus, while philosophical and technical challenges to mechanic-organic dualisms are timely and relevant, we should continue to make some distinctions. Even though the cybernetic properties of contemporary machines (like the self-organizing or recursive nature of neural nets) make them resemble organisms, the fact is that these \u201cintelligent\u201d systems are inserted in a technocapitalist industry that enables a high concentration of\u00a0automated power. This is why, besides the insights from cybernetic philosophy, we need to make sure that the concept of \u201cintelligence\u201d does not end up serving recursive machines that are also\u00a0historically recursive<\/em>, that is, machines that reinstate already-known social, economic, and ecological asymmetries.<\/p>\n On legitimate aliens<\/strong><\/p>\n A related way of depicting the virtues and pitfalls of the current trend toward wild computing is the figure of the algorithmic alien.\u00a0Philosopher of computation Luciana Parisi, for instance, suggests that we should embrace the \u201calien subject\u201d of AI as a potentially emancipatory force\u00a0(2019), something that could liberate humans from a master-slave model by challenging the \u201cservo-mechanic\u201d or instrumental idea of the machine. The \u201calienness\u201d of AI is the condition of its exemplary autonomy or freedom. Such freedom is expressed in the fact that we already cannot understand the kind of thinking behind complex, self-constituting algorithms, because they neither obey natural laws nor logical reason. The idea resonates with what Stephen Wolfram calls \u201ccomputational irreducibility\u201d\u00a0(Wolfram 2023)\u00a0and the fact that, because neural nets construct their own logic of functioning, AI is already unpredictable. The \u201calien\u201d argument also resonates (even if loosely) with some alarmistic prophecies of guru-historian Yuval Harari according to which alien autonomous machines are about to subjugate\u00a0the entirety of humanity<\/a>.\u00a0<\/p>\n Parisi rightly considers the \u201cpolitical possibilities\u201d of a \u201cdenaturalized\u201d form of thinking or intelligence that goes beyond patriarchal and colonial reason\u00a0(2019: 31). But one keeps wondering about the very fetishization of a human-made algorithm that becomes, by the magic of computation, suddenly \u201calien\u201d, truly autonomous, or superintelligent.\u00a0Does the philosophical construction of an epistemic \u201calienation\u201d with respect to machine thinking have an emancipatory potential after all? Is this particular alien fit for the task of denaturalizing our current problems?\u00a0What if we consider self-organizing neural nets not only as a cybernetic achievement, but also as an instrument of technocapitalism which is de facto owned by a few big tech lords? Are then these autopoietic systems still a realistic way out of patriarchal and colonial forms of concentration of power?<\/p>\n Anthropology has been classically occupied with tracing how colonial narratives conflate wildness with alienness. Connecting some aliens to some sort of inherent ferocity and lack of civilization has mostly been about legitimating the exercise of power. The story usually goes that, after verifying\u00a0the wildness of the alien, uncivilized Others, a group of Selves find a\u00a0casus belli<\/em>: a reason to intervene and liberate these alien Others from their struggle with uncertainty, anarchy, nature, and savagery. The story usually ends with a violent transformation of Others into aspirants to Selves. The \u201ctrue\u201d Selves then take hold of the alien world, while aliens renunciate their alienness, and of course their wildness.\u00a0<\/p>\n Wild computational narratives also play with the notions of alienness and wildness as part of a neocolonial gesture. But they do so differently from previous colonial narratives. A key concept in the AI world is\u00a0\u201ccomputational irreducibility\u201d. This idea implies that intelligent machines are already unpredictable (we cannot foresee their responses and creations). Because of computational irreducibility, AI machines embody a new, algorithmic form of wildness, and hence, we need to accept that the runaway world they will create for us can only be mastered again if we embrace, literally, \u201ca new kind of science\u201d\u00a0(Wolfram 2002), an all-encompassing form of computation.\u00a0<\/p>\n The underlying problem, however, remains pretty much the same as in old colonial gestures, for it is a ridiculously small fraction of all participants in the story who can \u201cdetermine\u201d which are the appropriate forms of alienness, wildness, and civilization.<\/p>\n<\/blockquote>\n So,\u00a0when it comes to the alien subject of AI or its computational irreducibility, there is an interesting shift in the narrative, since the alienness and the wildness of machines seem to be in that case a model, a reference, or even a source of metaphysical and technopolitical inspiration. The underlying problem, however, remains pretty much the same as in old colonial gestures, for it is a ridiculously small fraction of all participants in the story who can \u201cdetermine\u201d which are the appropriate forms of alienness, wildness, and civilization. They say, paraphrasing Wolfram\u2019s opening words (2023):\u00a0here are the \u201csymbols\u201d of \u201cour civilization\u201d and here are the sheer computational premises and tools with which we may go beyond them<\/em>. In other words, we cannot just celebrate the emancipatory force of AI while neglecting that, behind the bewildering dance of zeros and ones, there is a bunch of guys who are monopolizing the right to both define civilization and become its legitimate aliens. Partial incomputabilty<\/strong><\/p>\n In fact, the problem we have is not only with how a few lords of algorithms aim at reducing and propagating an anthropocentric and overtly ethnocentric version of \u201ccivilization\u201d.\u00a0\u00a0The issue is perhaps even more deeply rooted in the epistemics of the very idea of \u201cintelligence\u201d. Wild computing is indeed operating with a rather poor conceptualization of intelligence and cognition. However, as with the hasty treatment of civilization, the scientifically disputed and culturally biased approach to the concept of intelligence has a possible upside.\u00a0\u00a0After all, a good thing about the popularization of AI is, probably, that it has sparked an intense quest to define what are the limits (if any) between machine and human intelligence, thus requiring an increasingly nuanced definition of the idea. In this area, there are different epistemic positions.<\/p>\n \u00a0Unlike people within the world of computing, many scientists\u00a0in social, cognitive, and biological sciences remain cautious (if not skeptical) of claims of having replicated human-like minds artificially. Among other things, AI cannot generalize what it learns, as humans do, nor act across contexts and sensory modalities\u00a0(Mitchell 2019). Also, Large Language Models are designed to give statistically plausible but not necessarily true information, thus irreverently inventing facts. This pervasive phenomenon is now popularly known as \u201challucinations\u201d\u00a0(Marcus and Davis 2023), yet some say it would be more accurate to identify it as mere computational forms of \u201cbullshit\u201d\u00a0(Hicks, Humphries, and Slater 2024).<\/p>\n Another crucial point is that intelligence cannot really be dissociated from the feelings, emotions, and sensations that allow organisms to constantly attune and reattune to their everchanging environments; something that bodyless machines can\u2019t possibly do for now\u00a0(Dam\u00e1sio 2006). These and other shortcomings in computer-based notions of intelligence partly explain the fact that we don\u2019t yet understand how AI can beat master chess players but not load a dishwasher better than a six-year-old\u00a0(Bennett 2023).<\/p>\n So, my concluding question is that, if we cannot even replicate a child\u2019s embodied \u201cintelligence\u201d, how could anyone algorithmically \u201cdetermine\u201d a whole \u201ccivilization\u201d?<\/p>\n After all, there might be an important part of intelligence that has to remain, in Yuk Hui\u2019s terms, \u201cincomputable\u201d (2019: 158). Interestingly, partial incomputability does not even need to have humans with their complex intelligences and civilisations in the equation. In fact, it just takes a very simple worm like the\u00a0C. elegans<\/em>\u00a0with its 300 neurons (humans seem to have about 86 billion) to prove that we do not fully understand its choices or how its 300 hundred neurons work together. Therefore, we cannot claim to be able to algorithmically model anything close to its \u201cgeneral intelligence\u201d\u00a0(Sumpter 2019).\u00a0<\/p>\n These computational limitations seem to deeply pervade both human and nonhuman cognitive worlds.\u00a0\u00a0\u00a0<\/p>\n As a possible path to tame the most radical AI narratives, partial incomputability can also be traced by attending to the difference between what we could call\u00a0probabilistic<\/em>\u00a0and\u00a0possibilistic<\/em>\u00a0notions of intelligence. Playing with statistical probabilities and working with what already exists is the gift of the mathematized aliens that already write, design, or compose music for us. In return, organic intelligence, engaged in everchanging environments, seems to be equipped to face new situations, situations an organism does not know and for which it lacks a robust model\u00a0(Mitchel 2023; Krakauer 2024.).<\/p>\n These forms of embodied cognition are not only what makes life viable, but also, and despite wild computing aspirations, what turns \u201cintelligences\u201d and \u201ccivilizations\u201d into open-ended and hence incomputable arrays of possibilities.\u00a0<\/p>\n<\/blockquote>\n\n
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