Ted Striphas’ book Algorithmic Culture Before the Internet has been translated in Italian language and is forthcoming from the publisher Mimesis in the “philosophy of digital” series. This is the English translation of my Italian preface.
La cultura algoritmica prima di Internet is about the development and emergence of a human and social life’s new condition due to the growing intertwining between computing and culture.
The argument is an enormously and relevant issue thinking about how systematically such an encounter marks us as “onlife” beings (Floridi, 2016), meaning people who constantly live and orient their understanding of the world through and together networked algorithmic applications mediating what distinguishing us as human beings – the ability to understand or create meaning for ourselves and others through the means and forms of voice, symbols, sounds, and images.
Today we are aware of how much internet’s novelties developed during the last decades have homeopathically predisposed us to this. At the same time, we have at our disposal a vast scientific and popular literature trying to explain or criticize some aspect of this cybernetic turn in the ways of communicating, producing and consuming culture.
Instead, the work of Ted Striphas, professor of cultural studies, is more ambitious: gaining us an overall and longer-range overview capable of interpreting both the orientational and existential reflections of this cultural condition and the way in which, mostly uncritically, we have “come to terms” with it. That is, to accept the continuing shift toward a replacement of traditional human intermediaries in favor of programmed and automated systems that concur to guide us in the discovery of “personal and professional connections, products and services, news and knowledge, taste and opinions,” and in many other things as well (2024, p. 26).
To do so, the author invests in the heuristic power and explanatory productivity inherent in the apparent dissonance – because of the problematic relationship between culture and technology experienced in our tradition of thought – of the definition of “algorithmic culture”. According to the author, digging into the long genealogy of the same defining and ultimately mutually interacting terms of culture and algorithm can bring to the surface reasons and issues that have fueled hopes regarding how this union could relieve us from the complicated management of human coexistence in such hard matters as, i.e., state politics, wars, imperialism/colonialism, race, gender, sexuality, family, normativity, totalitarianism.
Really, Striphas’ work is a tenacious quest in recovering the deep and complex intermingling of issues and aspirations that only can explain that enormous industrial and social enterprise enabling – or inducing – billions of people to heavily infrastructure their life practices with digital technologies, with all the inevitable cultural fallout this would have entailed (Pinnix, Volmar, Esposito, Binder 2023).
It is not paradoxical, at least for those who appreciate media archaeology approach, that the gain in perspective author achieved occurs by utilizing those intellectual sensibilities that take it upon themselves to look forward by critically reopening what in the past can actualize the present.
As sociologist and philosopher Michael Löwy states “the opening-up of the past means also that the so-called ‘judgements of history’ have nothing definitive or unchangeable about them. The future may reopen ‘closed’ historical cases, may ‘rehabilitate’ misrepresented victims, revive defeated hopes and aspirations, rediscover forgotten batdes or batdes regarded as ‘Utopian’, ‘anachronistic’ or ‘running against the grain of progress’. In this case, the opening-up of the past and the opening-up of the future are intimately linked” (2001, p. 115).
On this path, then, social sciences have much to say by countering the storytelling of techies and engineers, so steeped in the flat newness of an unpostponable digital disruption. Striphas recalls the scene of having to descend escalators made to turn backwards in order to reconstruct gradually with more exactitude what really led to the arrival point, but one may also recall the Benjamian description of the angel painted by Paul Klee – in his imaginary “the angel of history” (Benjamin 1940, p. 392) – advancing into the future looking backward, dramatically aware that “the rapture of the unique, the new, the yet unborn is combined with that bliss of experiencing something once more, of possessing once again, of having lived” (1933, p. 715).
So, reflecting and reasoning in and on the terms of an algorithmic culture also seems to us to be a successful attempt to solicit confrontation between those who are more inclined to operate and examine current issues through the lens of algorithmic-related techniques, and those who are more accustomed to lingering in the realm of cultural studies.
From this point of view, any reasoned critique can thus contribute to the development of a more equitable and socially sustainable algorithmic culture since we have to coexist – in the concrete environments of life (habitus) – with the co-evolution of a human culture that spills over into machinic codes, which then, in turn, end up retroacting in/on the culture itself (Airoldi 2021).
On the human need for measuring, quantifying, calculating and correlating there would be much to say. Some historians – precisely in response to an insufficient historical record – have given us a glimpse of the roots of this kind of social urgency by lifting the veil over the many areas of opacity concerning the enormous volumes of basic elementary activities conducted daily by people, finally concluding that “material life constitutes, throughout the ancien regime, the broadest layer of all” (Braudel 1979, p. 22). Indeed, mathematics as an empirical tool to intermediate with calculation practical and basic needs, another means of expanding the human body’s propensity for technicality1.
In a brief history on the path of humanity, historian and philosopher Yuval Noah Harari reminds us how mathematical language was absolutely the first recording technique regarding human events – an important first step for the possibilities of intra- and inter-generational communicative and knowledge transmission.
However, it showed a limitation: its applicability concerned only the activities of production and exchange of products. Because of this one-sidedness in content, Harari calls it a “partial” language as opposed to the “total” one developed later and that we now universally use, i.e., “a system of material signs that can represent spoken language more or less completely… [that can] express everything people can say, including poetry” (2011, p. 139).
In any case, mathematics gradually fostered the ideational ability to abstract numbers from the specific physical objects/subjects to which they referred by urging the creation of new kinds of correlations, bringing “a gain in generality” through the action that “purifies the mind by drawing it away from the contemplation of the sensible and perishable” (Kline, 1964, p. 52, emphasis added).
Over time, a formal mathematics developed and became increasingly specialized that systematized and interrelated – in non-arbitrary and general notions – what we were cognitively acquiring in intuitive terms with a sense for numbers, or for shapes and space.
Cognitive scientist Steven Pinker has tried to list the relationships between human activities and the development of mathematical domains: counting (arithmetic and number theory); measuring (real numbers, calculus, analysis); shaping (geometry, topology); forming, as in architecture (symmetry, group theory); estimating (probability, measurement theory, statistics); moving (mechanics, calculus, dynamics); calculating (algebra, numerical analysis); proving (logic); puzzling (combinatorial analysis, number theory); grouping (set theory, combinatorial analysis).
Thus, it is possible to say that “The power of mathematics is that the formal rule systems can then ‘codify deeper and nonobvious properties of the various originating human activities’” (1998, p. 340).
A great power therefore whose strength we find to be one of the “three metrics” and “cornerstones of the Age of Progress.” For economist and sociologist Rifkin, our modern era has succeeded in guaranteeing us great affluence in living conditions by relying on “the wonders of science and the exactitude of mathematics; the new practical technologies to ease life; and the lure of the capitalist marketplace in advancing the economic well-being of society”.
In doing so, however, modernity has reorganized the spatial and temporal orientation “every individual, the community, and the economy and society at large” toward efficiencyist dynamics that have proved insensitive to a more general self-reflection on the sustainability – social, material, environmental – of its own developments (2022).
That stubbornness of purpose and broader indifference seem to persist even in the informational turn based on the massive use of networked computers for the exchange, recording and processing of data imposed in recent decades, so much so that the same kind of criticism hangs over it for the exaggerated overconsumption of environmental resources by its infrastructure (Signorelli 2023) and for nonetheless being – compared to the totality of human communities and its supposed instrumental neutrality – a partial and colonizing system based on certain “expectations, ideologies, desires and fears” (Crawford 2021).
Fueled by a cultural industry that has become whirling – whose only purpose seems to be to spin data that is likely to become contents in some way (Eichhorn 2022) – return illuminating some considerations about the authority assumed by mathematical language, which has become even more central to the many developments supported by algorithmic logics.
Harari observes that “although this system of writing remains a partial script, it has become the world’s dominant language…. Every piece of information that can be translated into mathematical script is stored, spread and processed with mindboggling speed and efficiency” while “experts do their best to translate even ideas such as ‘poverty’, ‘happiness’ and ‘honesty’ into numbers (‘the poverty line’, ‘subjective wellbeing levels’, ‘credit rating’)”.
Indeed, even the digital turn, turning all signs into symbols of 0s and 1s suitable for understanding computing, can be seen as a way to help mathematical writing become “total.” “Our computers have trouble understanding how Homo sapiens talks, feels and dreams. So we are teaching Homo sapiens to talk, feel and dream in the language of numbers, which can be understood by computers” (2011, pp. 147-148).
Within these “reductionist” dynamics, at least from an anthropological point of view, fall even the most sophisticated developments such as those of Artificial Intelligence: unlike the individual and collective potentialities, permeabilities and sensitivities that nurture a “metaphysics of will” proper to human experience, in today’s practical reality these algorithmic applications still remain within the limits offered by a “metaphysics of measurement” (D’Acquisto 2021, p. 16).
This means that the new intelligent machines function within an arc of possibilities entirely known at the outset and through a single representation of the world compatible with this scheme of full rationality – that is, through the availability of measures concerning certain states of the world. And it is only from the comparison “of metrics placed in specific relations – in terms of order (X is greater than Y); probability (X is less uncertain than Y); logic (if X therefore Y) – that the autonomous action of the machine can descend” (Petullà 2023, p. 199).
Ultimately, those who think and work in environments attentive to the reasons for quantifying, measuring, and correlating have a great gap to fill in their ability to represent and manage – in their complexity and generativity – the events that occur – and continually acquiring meaning – in the individual and social world. Which also means (if it is ever possible) having to re-include, in these inevitably partial and biased representations in their objectives, the proper characterizations produced by that “sensible and perishable” which mathematical techniques tend to abstract from real lives – and which instead gives shape and makes human beings vibrate.
Consequently, as Striphas suggests, in this continuing claim to the extension of “algorithmic rationalities into the deepest recesses of daily life” algorithmic engineering cannot fail to take into account the “culture’s continuing importance as a site of investment, identification, negotiation, action, judgment” (2024, p. 25, p. 38). This entails a responsibility to know how to deal, in all their multifaceted dimensions, with the relational entanglements and distances between technological doing and those more intangible but so central qualitative issues, in terms of expectations and justice, in the embodied lives of individuals and communities.
The book will provide a wide range of such concerns, but we can close here with the considerations that, with respect to the frequent categorical exemplifications made on account of representability and computation, historian and gender scholar Susan Stryker (2017) develops on the concept of identity.
Identity is who you are. It’s a word with a paradox at its core. It means that two things that are not exactly the same can be substituted for one another as if they are the same. In math, to say that (1 + 4) = (2 + 3) is to say that even though the two sets are made up of different numbers, they are mathematically identical because they add up to the same thing. In society and culture, the concept of identity works similarly. When you say, “I am a Socialist” or “I am a Hindu” or “I am a musician” or “I am a woman,” the “am” is like an equal sign, and you are saying that your individual sense of being something (an “I”) is described by a category that you consider yourself as belonging to. You and the category are not exactly the same thing, but under certain circumstances one canbe substituted for the other. In social life, it’s often quite important to say what categories you identify with or to call attention to categories you get placed in, whether you identify with them or not. Of course it’s possible to have many different, overlapping, or even contradictory personal identities and for people who are significantly different from one another in some ways to be included in the same category.
References
Airoldi, M. (2021). Machine Habitus: Toward a Sociology of Algorithms, London: Polity.
Benjamin, W.
(1933). “Agesilaus Santander (Second Version)”, in Id., Selected Writings. Vol. 2, Part 2 1931-1934, 714-16. Cambridge, Ma: Harvard University Press, 2005.
(1940). “On the Concept of History” in Id., Selected writings. Vol. 4, 1938-1940, 389-400. Cambridge, Ma: Harvard University Press, 2006.
Borrelli, D. (2004). “Mano”, in Abruzzese, A., Lessico della comunicazione, Roma: Meltemi.
Braudel, F. (1979). Civilization and Capitalism.15th-18th Century. Vol. 2: The Wheels Of Commerce, London: Book Club Associates, 1982.
Crawford, K. (2021). Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence, New Haven & London: Yale University Press. (digital edition).
D’Acquisto, G. (2021). Intelligenza artificiale. Elementi, Torino: Giappichelli.
Eichhorn, K. (2022). Content, Boston: The Mit Press. (digital edition).
Floridi, L. (2016). The Fourth Revolution: How the Infosphere is Reshaping Human Reality, Oxford: Oxford University Press.
Harari, Y. N. (2011). Sapiens: A Brief History of Humankind, London: Vintage Books.
Kline, M. (1964). Mathematics In Western Culture, Oxford: Oxford University Press.
Löwy, M. (2001). FIRE ALARM. Reading Walter Benjamin’s On the Concept of History’, London-New York: Verso, 2005.
Petullà, L. (2023). “Cultura algoritmica e intelligenza artificiale”, in Wolton, D., Borrelli, D., Grassi, C., (Eds.) Sociologia della cultura, Napoli: Editoriale scientifica.
Pinker, S. (1998). How The Mind Works, Castelvecchi, London: Penguin Books.
Pinnix, A., Volmar, A., Esposito, F., Binder, N. (Eds.) (2023). Rethinking Infrastructure Across the Humanities. Bielefeld: Transcript Verlag.
Rifkin, J. (2022). The Age of Resilience: Reimagining Existence on a Rewilding Earth. New York: St. Martin’s Press. (digital edition).
Signorelli, A. D. (2023). “Intelligenza artificiale, quanto consumi? L’insostenibile costo ambientale dell’AI”, Domani, October 29, visited 10/30/2023, https://www.editorialedomani.it/fatti/intelligenza-artificiale-quanto-consumi-linsostenibile-costo-ambientale-dellai-eq7ee7fi.
Striphas, T. (2024). La cultura algoritmica prima di Internet. Milano: Mimesis.
Stryker, S. (2017). Transgender History: The Roots Of Today’s Revolution. New York: Seal Press.
1Just “on the fingers that the knowledge of calculating and measuring the world is built” (Borrelli 2004, p. 316) so much so that the “Traces of this ancient way of counting are imbedded in our own language, the word digit meaning not only the numbers 1, 2, 3 . . . but a finger or a toe as well. The use of the fingers undoubtedly accounts for the adoption of our system of counting in tens, hundreds (tens of tens), thousands (tens of hundreds), and so forth” (Kline 1964, p. 13).
