From a little bit different of a theoretical framework, but Allison Parrish recently did a wonderful talk about spellcheck and queer phenomenology: https://posts.decontextualize.com/queer-in-ai-2021/ <https://posts.decontextualize.com/queer-in-ai-2021/> https://www.nabeelsiddiqui.net
On Jan 21, 2022, at 11:14 AM, Alexandre Hocquet <alexandre.hocquet@univ-lorraine.fr> wrote:
Dear Jonathan,
Thank you very much for this neat example. I never use Excel so I am not sure if the autocorrect feature can be disabled in settings or not (my guess is that it surely is, but you never know). That said, I find that this is more telling about the acculturation of users to Microsoft packages than the reckless use of pieces of software, even in areas where you might think better solutions exist, especially scientific ones.
After all, a lot of scientific mistakes occur because of the (incorrect) use of default settings, even in specialized software. I have this example of a recent publication in chemistry regarding calculations of NMR chemical shifts whose output turn out to depend on.... the OS the calculations are run on ! https://pubs.acs.org/doi/abs/10.1021/acs.orglett.9b03216#
It gives me the opportunity to shamelessly self-promote my upcoming talk where I will use Jonathan's example. If you're interested in open science and its complex relationship with software
"Only the initiates will have the secrets revealed" : The politics and materialities of open science ----------------------------------------------------------------------------------------------------
Käte Hamburger Kolleg "cultures of research" lecture series in Aachen and [online](https://khk.rwth-aachen.de/lecture-series/) Wednesday, January 26th, 5pm CET
Open Science has been pervading the scientific world in the last decade. It is a buzzword, and a promise. First, through Open Access, as a combat against corporate publishers, then through Open Data as a mean to enhance sharing practices, and more recently, and more timidly, through the promotion of Open Software. Strikingly, Open Software in science has attracted until now less interest even though Open Science itself is rooted in 1980s free software principles. This talk focuses on software in science and its diversity of entanglements with openness. Software has been "eating" the world and science is no exception. From Excel to complex "big" scientific instruments, via Photoshop or molecular modelling software suites, the vast majority of software used in science is not open, and a vast majority has nothing to do with computer science. When software is open, it is very often naively represented as a solution to all issues in science, especially reproducibility. Yet, even open software is full of epistemic issues, from governance to consistency, and the consequences of its influence on the rest of open science are often misunderstood, especially regarding licensing policies.
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