Konrad Hinsen's blog
Convivial technology was defined by Ivan Illich in his 1973 book "Tools for conviviality" as technology that supports a convivial society, which is a society that strives to grant each of its members as much agency as is possible without infringing on other members' agency. Conviviality is thus about equality, about the absence of dominance relations. Convivial technology is shaped by its users according to their needs, rather than being controlled by entities such as companies or governments, which then derive power over the user base by exercising control.
One of Illich's examples is transportation, with bicycles being convivial whereas railways and cars are not. Cars in particular have turned into what Illich calls a "radical monopoly": a technology that imposes itself on everyone. Once a society has adapted its landscape and infrastructure to cars, walking or cycling become insufficient as a means of locomotion for most people, if only because typical distances are now typical distances for driving, not walking. Moreover, the total societal cost for car-based mobility is enormous, if you count in the cost of road construction, traffic accidents, environmental pollution, and much more.
A recent paper entitled "Conviviality for Digital Degrowth", by Sophie Quinton and Jean-Bernard Stefani, discusses how today's digital technology is not convivial, and outlines how this could change as part of a transition to a degrowth society. It motivated me to finally write down my personal story, which is about something much more modest: the conviviality of digital technology in scientific research. It's something I have been thinking about for thirty years, even though I wasn't aware of Illich's work and terminology until recently.
Let me start with the observation that most pre-digital technology in scientific research is convivial. Theoretical tools (theories, models, etc.) are developed and evolved completely inside the scientific community and belong to no individual nor any institution. Scientific instruments and experimental setups are designed either by scientists, or explictly for scientists and in close collaboration with them. Neither kind of tool is controlled by outside entities, with the possible exception of very large instruments such as CERN. Nobody can decide that scientists may no longer use NMR spectrometers, nor that they have to replace all pre-2000 microscopes by new ones. This has changed with the adoption of digital tools and the integration of digital technology into scientific instruments. Theoretical tools are now often software, whose complexity makes its behavior inscrutable to its users and puts them at risk of losing their tools to software collapse. Scientific instruments increasingly rely on built-in computers that create exactly the same issues. Finally, digital technology has enabled industrial-scale production of data, e.g. in DNA sequencing, and that technology is itself not convivial either.
Conviviality matters for science for multiple reasons. One of them is epistemic: if you want to derive knowledge from your work, you need to know exactly what you are doing, and that includes a detailed understanding of your tools. Moreover, research is much facilitated if you also have the inverse: the ability to create a tool that does exactly what you want to do. And since science is a collective activity, in which participants critique and build on each other's work, the understanding of tools needs to be shared inside a discipline. There have always been limits to this shared understanding, in particular concerning specific physical devices or unique experimental setups, but building shared understanding on a best-effort basis has always been one of the tacit underpinnings of science. This best effort has been abandoned in the digital era, as I discuss in an analysis of trust issues with scientific software,in which conviviality plays an important role.
When I started doing computational studies of colloidal suspensions in the late 1980s for my master's degree and then my PhD, research software was still quite convivial. Like most PhD students, I wrote medium-size Fortran programs, which ran on any computer with a Fortran compiler, from the Atari ST I had at home to the Cray X-MP that I used for production runs. Other scientists could read and understand my code in a few days, given sufficient motivation, and I know that some actually did, because I received questions from them by e-mail. It was also quite common for PhD students to look at and comment each other's programs. Publishing software was still exceptional, but publication venues did exist, and I ended up publishing the main code library underlying my work in low-Reynolds-number hydrodynamics in 1993. Unfortunately I didn't publish, nor properly archive, the small bits of code that did the actual computations for concrete specific systems, and that is why the results of my papers aren't...