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Joanne McNeil reviews the Crisis Text Line scandal for Vice:

The way Crisis Text Line behaved with its sensitive user data is a shocking example that shows Silicon Valley beliefs in personal data as a commodity and privatized infrastructure have spread to nonprofits and "tech for good" initiatives.

In March, Michael Murtaugh writes about an experimental approach to creating feminist infrastructures at Constant, the Brussels-based artists’ association.

In our work maintaining the infrastructure of Constant web publishing, we find inspiration in the figure of the sponge.

Sponges are porous. We engage with "bridging" protocols that honor the complexity of diverse practices (library sciences, informatics, archival practices, writing, and the intersectionality that feminisms bring to each), and engage with standards while maintaining our own terms.

Sponges are slow. Our work resists the ruptures of the "new," preferring care; graceful forms of maintenance given limited resources and continuity.

An earlier article in the same publication provides additional insights into Constant’s ways of working.

At FemLab.co, Aditi Surie and Krishna Akhil ask important questions about the growth of ed-tech in India:

If EdTech companies start to adopt the business models of gig platforms like in food delivery, or the ride-hailing sector, then how do we see the future of our educators? What does EdTech do to the nature of the teacher’s work? How do the patterns of the Indian education sector relate to the ways in which we think about the kind of employment EdTech companies offer educators using their platforms?

Julian Posada writes about data annotation work as a survival tactic in Logic Magazine‘s "Beacons" issue:

[T]he political and economic crisis in Venezuela, as well as the pandemic and remote schooling, have turned out to be productive for data annotation platforms, their clients, and the venture capitalists that back them. … The thousands of companies and research institutions that develop artificial intelligence are using platforms to find cheap outsourced labor, especially from low-income economies, for global markets in which data and labor are sold as commodities.

Internet Policy Review is publishing contributions on some of the defining concepts of the digital society.

Based on the latest research, yet broad in scope, the contributions offer effective tools to analyse the digital society. Their authors offer concise articles that portray and critically discuss individual concepts such as algorithmic governance, datafication, platformisation, [and] privacy with an interdisciplinary mindset. Each article contextualises their respective origin and academic traditions, analyses their contemporary usage in different research approaches and discusses their social, political, cultural, ethical or economic relevance and impact as well as their analytical value.

Already published contributions include Datafication by Ulises Mejias and Nick Couldry, Platformisation by Thomas Poell, David Nieborg and José van Dijck, and Data Justice by Lina Dencik and Javier Sanchez-Monedero.

In Fieldsights’ Teaching Tools section, Alexandria Petit-Thorne revisits Relata, an experimental tool to map anthropological debates by identifying analytical relations between scholarly works. It is built on research by our colleague Rodrigo Ochigame.

As an instructor, I see a few keys ways in which Relata might be used in teaching or instructional support. Thinking specifically about the introductory first-year courses I teach, Relata might be useful in teaching about researching and writing essays because it offers an interactive and dynamic way of visualizing conversations between scholars or schools of thought. The mapping of conversations produces easy to follow visuals of how different papers and ideas build onto and off of each other. I often find myself trying to create graphics that do just that when I teach students how to build arguments for their essays in introductory anthropology courses.

The Digital Infrastructure Incubator at Code for Science & Society is hosting a series of public events on "Political Imagination to Support and Sustain Digital Infrastructure":

These discussions connect conversations on sustainability, governance, and community health in digital public infrastructure to wider political horizons. Invited panelists draw from their experiences in unionization drives, climate actions, abolition movements, among others. Together these events draw out interdisciplinary resonances and invite participants to make connections to neighborhoods and communities on and off line.

The next event on February 23, 2022, is on "Coloniality of Digital Infrastructure."

Meredith Whittaker takes on corporate AI in the ACM’s Interactions:

Modern AI is fundamentally dependent on corporate resources and business practices, and our increasing reliance on such AI cedes inordinate power over our lives and institutions to a handful of tech firms. It also gives these firms significant influence over both the direction of AI development and the academic institutions wishing to research it. Meaning that tech firms are startlingly well positioned to shape what we do—and do not—know about AI and the business behind it, at the same time that their AI products are working to shape our lives and institutions.

The peer-reviewed journal Big Data & Society has begun publishing contributions to its "Machine Anthropology" special issue edited by Morten Axel Pedersen.

Bringing together a motley crew of social scientists and data scientists, the aim of this special theme issue is to explore what an integration or even fusion between anthropology and data science might look like. Going beyond existing work on the complementarity between "thick" qualitative and "big" quantitative data, the ambition is to unsettle and push established disciplinary, methodological and epistemological boundaries by creatively and critically probing various computational methods for augmenting and automatizing the collection, processing and analysis of ethnographic data, and vice versa. Can ethnographic and other qualitative data and methods be integrated with natural language processing tools and other machine learning techniques, and if so, to what effect? Does the rise of data science allow for the realization of Levi-Strauss’ old dream of a computational structuralism, and even if so, should it? Might one even go as far as saying that computers are now becoming agents of social scientific analysis or even: are we about [to] witness the birth of distinctly anthropological forms of artificial intelligence? By exploring these questions, the hope is not only to introduce scholars and students to computational anthropological methods, but also to disrupt predominant norms and assumptions among computational social scientists and data science writ large.

A group of junior anthropologists has contributed "A View from Anthropology: Should Anthropologists Fear the Data Machines?"

If you are an anthropologist wanting to use digital methods or programming as part of your research, where do you start? In this commentary, we discuss three ways in which anthropologists can use computational tools to enhance, support, and complement ethnographic methods. By presenting our reflections, we hope to contribute to the stirring conversations about the potential future role(s) of (social) data science vis-a-vis anthropology and ethnography, and to inspire other anthropologists to take up the use of digital methods, programming, and computational tools in their own research.