Comparto estrategias para combatir los mensajes de odio en redes sociales, sea en plataformas de villanos mustios o sea en el #fediverso. 🧼🧹
También hablo de #derechosdigitales, #cuidadosdigitales, #atención, #privacidad, #datos y de todo lo que podamos hacer para que #internet mole más. ✨
| Formo parte de Laintersección | http://lainterseccion.net/ |
Querides,
Con mucha alegría os contamos que ¡¡tenemos web nueva!! 🥳
https://proyectohortensia.net
Es una web 100% pensada para personas que no conocen las realidades #trans y que podrían convertirse en aliadas si se lo ponemos fácil. Así que ya sabes lo que te vamos a pedir ahora: que, si te gusta, la compartas (y la lleves fuera del fedi, a otros ámbitos, que aquí ya sabemos que somos mayoritariamente transaliades). 🙏🏼 #apoyomutuo
Se ha quedado un día perfecto para mudarse a @signalapp... https://signal.org/
(Antes de que me digáis que hay opciones más libres y mejores: sí, pero se trata de buscar una app donde te puedas comunicar con tus amigas, sin que sean todas ellas ingenieras informáticas o gente con mucho tiempo y voluntad).
Y tú que no te vas de la Pajarería porque MIS SEGUIDORES
#redes #X #noticias
https://www.independent.co.uk/news/world/americas/elon-musk-x-vietnam-engagement-farming-b2756948.html
Exclusive: An eight-man crew operating out of a dingy office in downtown Hanoi, Vietnam, is accused of extracting payouts from X “by manufacturing the appearance of content engagement where none really exists.”
A rapidly growing number of voices argue that AI research, and computer vision in particular, is powering mass surveillance. Yet the direct path from computer vision research to surveillance has remained obscured and difficult to assess. Here, we reveal the Surveillance AI pipeline by analyzing three decades of computer vision research papers and downstream patents, more than 40,000 documents. We find the large majority of annotated computer vision papers and patents self-report their technology enables extracting data about humans. Moreover, the majority of these technologies specifically enable extracting data about human bodies and body parts. We present both quantitative and rich qualitative analysis illuminating these practices of human data extraction. Studying the roots of this pipeline, we find that institutions that prolifically produce computer vision research, namely elite universities and "big tech" corporations, are subsequently cited in thousands of surveillance patents. Further, we find consistent evidence against the narrative that only these few rogue entities are contributing to surveillance. Rather, we expose the fieldwide norm that when an institution, nation, or subfield authors computer vision papers with downstream patents, the majority of these papers are used in surveillance patents. In total, we find the number of papers with downstream surveillance patents increased more than five-fold between the 1990s and the 2010s, with computer vision research now having been used in more than 11,000 surveillance patents. Finally, in addition to the high levels of surveillance we find documented in computer vision papers and patents, we unearth pervasive patterns of documents using language that obfuscates the extent of surveillance. Our analysis reveals the pipeline by which computer vision research has powered the ongoing expansion of surveillance.
Algorights
Laintersección
Hortensias
Thiago Ferrer Morini
