Étiquette : crowdsourcing (Page 1 of 2)

“Newcomers to Wikipedia may not understand that discussion about what gets added or deleted from entries isn’t done behind closed doors. Rather, it happens on the publicly accessible “notes” pages of each entry—where volunteers will discuss edits and have open discussions on whether changes should go forward or not. Editing Wikipedia pages helps users understand just how malleable knowledge is, says Alex Jung, the University of Toronto’s Wikipedian-in-residence. If someone makes substantive edits to an entry, “someone who visited the page today will have an entirely different idea of the topic than someone who visited it yesterday. Knowledge is fluctuating all the time.””

Source : Why universities are hiring “Wikipedeans-in-Residence”

“The Wikimedia Foundation believes that, working with checkusers, stewards and vandal-fighters, it’s possible to figure out a way to protect our users’ privacy while keeping our anti-vandalism tools working at-par with how they work now. Hence, it has decided to work on shielding IP addresses from our wikis — including restricting the number of people who can see other users’ IP addresses, and reducing the amount of time IP addresses are stored in our databases and logs. It is important to note that a critical part of this work will be to ensure that our wikis still have access to the same (or better) level of anti-vandalism tooling and are not at risk of facing abuse”

Source : IP Editing: Privacy Enhancement and Abuse Mitigation – Meta

Waze

«Au nom de l’amélioration de la sécurité routière, les applications GPS comme Waze et Coyote qui permettent, outre de guider les automobilistes pendant leur trajet, de les prévenir en cas de présence de radars ou d’agents de police sur la route, auront peut-être très bientôt l’obligation de cacher temporairement certains signalements sur des zones désignées par les forces de l’ordre».

Source : Pour rester discrète sur les routes, la police pourra interdire les signalements sur Waze et Coyote – Politique – Numerama

« The news is broken and we can fix it. We’re bringing genuine community control to our news with unrestricted access for all. We’re developing a living, breathing tool that’ll present accurate information with real evidence, so that you can confidently make up your own mind ».

Source : Wikitribune – Evidence-based journalism

« Dès les premières minutes qui ont suivi la mise en ligne de ce clip, la définition Wikipédia a fait l’objet d’une petite guerre de réécriture, entre les internautes s’amusant à ajouter des ingrédients nocifs (clous et autres morceaux de rats) et les équipes de Burger King qui corrigeaient ces changements. The Verge, rapporte que la définition normalement prévue, qui détaillait tous les ingrédients, a été modifiée directement par le chef du marketing de la chaîne, Fernando Machado, avec le même pseudo que son compte instagram, Fermachado123 (pas très discret) ».

Source : Burger King détourne Google Home pour faire sa publicité, Google riposte – Tech – Numerama

Machine Learning (ML) is a fast-moving, competitive field. As important as good algorithms are to ML, the state-of-the-art algorithms are reliably available. Compute clusters are also an important ingredient, and they too are easy to access (especially using services like Amazon EC2 and Amazon EC2 Elastic GPUs). What isn’t reliably available are large-scale high quality data sets. The things you need to train your classifiers. That’s where MTurk comes into play.

Source : re:Invent 2016 recap — Machine Learning with Amazon Mechanical Turk

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