algorithms | Platypus

Cultures of Trust in Computing and Beyond

 Samantha Breslin  May 28, 2024

What does it mean to trust? In this post I explore how there are specific ways of producing trust in computer science education. I draw on ethnographic fieldwork conducted for my PhD in an undergraduate computer science program in Singapore, where I examined the “making” of computer scientists—how students are shaped as socio-technical persons through computer science education. During my fieldwork, I conducted participant observation in eight undergraduate computer science courses across all years (first to fourth) with a focus on required core courses for the computer science program, which is what I draw primarily on for this post. I also conducted interviews with students, professors, and administrators; policy and curriculum analysis; and participant observation in the department, university, and tech community more generally. I also myself studied computer science as an undergraduate student, which led to my interest in this topic. (read more...)

Algorithmic Imaginations in Agriculture: Automation?

 Ziya Kaya  November 28, 2023

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In 2022, I was conducting my doctoral dissertation research on data-driven, automated digital farming technologies (drones, autosteering, sensors, GIS, smartphones, Big Data) in Turkey. Amidst the global hype for digital agriculture, often referred to as “smart” farming or precision agriculture, new agritech companies and startups in and beyond Turkey have been emerging alongside agribusiness corporations. These companies invest in and prioritize data-driven and algorithmic technologies over human involvement in agriculture with the assumption of the former’s objectivity and precision (Bronson 2022). For instance, the market in Turkey provides farmers with access to drones for precise chemical spraying, including fertilizers and pesticides. These drones operate autonomously, enabling farmers to target specific sub-fields rather than resorting to mass spraying. Farmers can also access various smartphone applications that, for instance, claim to offer real-time data on soil conditions at the sub-field level collected through sensors and algorithmic recommendations ensuring precise irrigation. Additionally, the companies imagine generating valuable insights into the agricultural sector for agricultural corporations, financial and biotechnology firms, and public institutions through these data-driven technologies. While not all of these technologies are extensively used by farmers in Turkey, the companies continue developing, marketing, and showcasing them and many others to automate and gather data for a wide range of agricultural operations with the claim of improving food security and ecological and socioeconomic welfare. (read more...)

On Algorithmic Divination

 Rebecca Carlson, Heikki Wilenius, Jonathan Corliss  October 31, 2023

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Algorithms are tools of divination. Like cowry shells, scapular bones, or spiders trapped under a pot, algorithms are marshaled to detect and relay invisible patterns; to bring to light a truth which is out there, but which cannot ordinarily be seen. At the outset, we imagine divination is a means to answer questions, whether in diagnosis of past events or for the prediction and guidance of future outcomes, choices or actions (Ascher 2002, 5). Yet, divination has an equally potent capacity to absorb the burdens of responsibility, to refigure accountability and, in so doing, to liberate certain paths of social action. (read more...)

“The Day I Discovered I Was Collaborating on a Eugenics Project”: On Imponderables in Collaborative Research

 Sandra Avila, Marisol Marini  September 26, 2023

Este conteúdo também está disponível em português

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The title that opens this reflection is a statement by computer scientist Sandra Avila, who is also a co-author of the lines that will flow here. Her account took place during the recording of a podcast on science and feminism. In that situation, Avila recounted a non-trivial research experience. She may never have been able to talk about it with her colleagues in computer science, let alone with collaborators in dermatology who offered their “expertise advice.” It was in informal conversations with feminist researchers that Avila found a safe place to talk about a situation that had made her cry with anger because she felt cheated. (read more...)

AI, Climate Adaptation, and Epistemic Injustice

 Angelina Chamuah, Hema Vaishnavi Ale, Vikrom Mathur  July 20, 2023

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Amid global climate impacts, vulnerable communities—including indigenous peoples, farmers, fisherfolk, and low-income groups—are frequently expected to adapt, change, and build resilience to uncertain climatic futures. Under these changing conditions, what knowledge practices and frameworks should guide the decision-making of vulnerable communities in addressing climate challenges? What knowledge sources and perspectives should be considered when developing resilience policies and plans, from the supranational to the local level? (read more...)

Transpositioning, a Hypertext-ethnography

 Rebecca Carlson  March 21, 2023

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This is a work of hypertext-ethnography. It is based on my research of a small genetics laboratory in Tokyo, Japan where I am studying the impact of the transnational circulation of scientific materials and practices (including programming) on the production of knowledge. In this piece, I draw primarily from my participant observation field notes along with interviews. I also incorporate other, maybe more atypical, materials such as research papers (mine and others), websites and email. The timeframe for this work is primarily the spring of 2020 and the setting is largely Zoom. Although I began my research in 2019 physically visiting the lab every week, in April 2020, it—and most of the institute where the lab is located—sent researchers home for seven weeks. That included me. Luckily, the lab quickly resumed its regular weekly meetings online (between the Principal Investigator (PI) and individual post-docs for example, as well as other (read more...)

If I Could Talk to the Algorithm

 Patricia G. Lange  January 31, 2023

In the film Doctor Dolittle (1967), the title character yearns to “Talk to the Animals,” as the song goes, to understand their mysterious and often vexing ways. It is interesting to observe a similar impulse to understand and communicate with algorithms, given their current forms of implementation. Recent research shows that intense frustration often emerges from algorithmically driven processes that create hurtful identity characterizations. Our current technological landscape is thus frequently embroiled in “algorithmic dramas” (Zietz 2016), in which algorithms are seen and felt as powerful and influential, but inscrutable. Algorithms, or rather the complex processes that deploy them, are entities that we surely cannot “talk to,” although we might wish to admonish those who create or implement them in everyday life. A key dynamic of the “algorithmic drama” involves yearning to understand just how algorithms work given their impact on people. Yet, accessing the inner workings of algorithms is difficult for numerous reasons (Dourish 2016), including how to talk to, or even about, them. (read more...)