Mathieu Jacomy and Anders Munk, TANT Lab & Public Data Lab
6 minutes read
Gephisto is Gephi in one click. You give it network data, and it gives you a visualization. No settings. No skills needed. The dream! With a twist.
Gephisto produces visualizations such as the one above. It exists as a website, and you can just try it below. It includes test networks, you don’t even need one. Do it! Try it, and come back here. Then we talk about it.
https://jacomyma.github.io/gephisto/
Continue readingA short piece on “Algorithm Trouble” for AI Now Institute‘s A New AI Lexicon, written by Axel Meunier (Goldsmiths, University of London), Jonathan Gray (King’s College London) and Donato Ricci (médialab, Sciences Po, Paris). The full piece is available here, and here’s an excerpt:
“For decades, social researchers have argued that there is much to be learned when things go wrong.¹ In this essay, we explore what can be learned about algorithms when things do not go as anticipated, and propose the concept of algorithm trouble to capture how everyday encounters with artificial intelligence might manifest, at interfaces with users, as unexpected, failing, or wrong events. The word trouble designates a problem, but also a state of confusion and distress. We see algorithm troubles as failures, computer errors, “bugs,” but also as unsettling events that may elicit, or even provoke, other perspectives on what it means to live with algorithms — including through different ways in which these troubles are experienced, as sources of suffering, injustice, humour, or aesthetic experimentation (Meunier et al., 2019). In mapping how problems are produced, the expression algorithm trouble calls attention to what is involved in algorithms beyond computational processes. It carries an affective charge that calls upon the necessity to care about relations with technology, and not only to fix them (Bellacasa, 2017).”
Over the past year researchers and students at institutions associated with the Public Data Lab have contributed to a series of collaborative digital investigations into the online circulation of COVID-19 misinformation and conspiracies.
Researchers and students contributed to a series of “engaged research led teaching” projects developed with journalists, media organisations and non-governmental organisations around the world.
These were undertaken in association with the Arts and Humanities Research Council funded project Infodemic: Combatting COVID-19 Conspiracy Theories, which explores how digital methods grounded in social and cultural research may facilitate understanding of WHO has described as an “infodemic” of misleading, fabricated, conspiratorial and other problematic material related to the COVID-19 pandemic.
These projects led to and contributed to a number of stories, investigations and publications including: