Computing [in] Crisis

Climate Crisis, democracy in crisis, a global pandemic – multiple crises linked together define the first quarter of the 21st century [3]. In filling in the bracket between Computing and Crisis it seems only natural, in 2025, to also attest Computing the status of being in Crisis. Consequently, in order for computing to be a discipline counteracting crises caused by and affecting humanity, criticising its internal misalignments marks a necessary starting point.

First of all,
even though computer scientists driven by the Californian ideology try to frame it as such, computing solely is not the solution to social or societal crises; rather, many (aggravations of) crises stem from how computing is understood and applied – dominated by a mindset that turns social problem-solving into an engineering problem. Thus, neglecting a broader theoretical and social perspective, underscoring the need for common ground to reimagine computer science as more than just a tool for technical fixes of the world.

Computing suffers from a lack of interdisciplinary perspectives [4] and a persistent tendency to frame itself through "killer story" narratives. Despite repeated calls for interdisciplinarity, the field has increasingly aligned itself with technical and engineering paradigms, perpetuating a separation from the social sciences and humanities which in turn impacts teaching, research, and collaboration (a well as the power dynamics therein). This ongoing struggle highlights the necessity of re-examining the epistemological foundations of computer science, as supported by recent scholarly discussions and literature [51].

Another internal crisis of computing is that of participation in the design of technologies and digital living spaces: For instance, drawing on a current example, Large Language Models (LLMs) and Machine Learning (ML) highlight critical tensions in the realm of participation, as their application often remains confined to centres of power, restricted by privately owned and highly complex systems and companies, and instrumentalised as tools of and for political action. The immense resources that are required to train and design LLM-based systems also renders computing one of the most tightly monopolised industries in history.

Last but not least, a crisis of computing is constituted by the negligence of the material and rather “mundane” aspects of Computing. Many scholars by now have pointed out that computing runs on the labor and physical contributions of multiple humans and non-humans, including earth bodies (from data labelling to earth minerals) that not only compose computing infrastructures but also are essential to their maintenance [5, 6, 7, 8]. Through this, computing is also entangled with mundane - in a sense of well entrenched - and very material forms of exploitation and inequality, reproducing them with updated operational settings for the digital age [9, 10].

Taking all those crisis together, it seems that computing (as a meta-science) is veering “off track”. If it was ever on the right track at all. Whilst other scientific disciplines have different subjects of investigation in the physical world, computing as a self-entailed academic discipline, has always had the task to find its place and angles from which to tell its own stories [11].

In the worst cases, this leads to developing and applying computing technologies just for the sake of it, not thinking of the broader consequences. Just as Mary Shelley’s Dr. Frankenstein [12] built his creature without thinking what it might entail, leading, in the end, to tremendous suffering of all involved. Who, ultimately, is the monster? The creature – or its creator?

Thus, we want to trace some of the historical, etymological and conceptual trajectories of computing, in order to construct lateral genealogies, minor lines that can critically query where the stories that define computing as a discipline practised and taught today come from. This closer look to its roots, we believe, might offer different perspectives: after all, computing history is more rhizomatic than linear, and thus offers “hidden figures” that constitute an alternative canon and perhaps even change, or at the very least multiply, the story of computing.

We are inspired here by many feminist excavations of such hidden figures across other fields. For instance, in biology and genetics, one could think of Lynn Margulis, who not only discovered “jumping genes” but also went against the grain of the genetic theories at the time, to propose that evolution proceeds, not so much through conflict and destruction of the “weakest” by the “fittest”, but rather through symbiogenesis. Proposing a more collaborative, symbiotic perspective, her work, in collaboration with James Lovelock, laid further scientific ground for the “gaia hypothesis”, which approaches the earth as a complex living organism [13].

In criticising the tone and motive of computing’s storytelling, we use the Carrier Bag Theory of Fiction by Ursula K. Le Guin [1989] as a speculative tool for formulating an alternative. This re-contextualisation challenges the prevailing narrative of computing and its need to tell a heroic "killer story" – one defined by conquest and dominance – in order to justify itself, and instead explores the potential for transformative change by foregrounding the life stories of computing. Such a shift could offer a richer, more inclusive understanding of the discipline, opening pathways for more equitable, holistic, and participatory practices.

Retelling the story of computing, on the basis of our criticism expressed above, leads us to referring back to computer science as a Gestaltungswissenschaft, as a much more fitting carrier.

Let’s gather around the campfire and tell a Carrier Bag Theory of Computing.