#dat

Preview: Amazon #s3 Tables in DuckDB – DuckDB
▻https://duckdb.org/2025/03/14/preview-amazon-s3-tables.html

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#duckd #database

Beyond the Binary: Improving #Data_Visualization for Intersectional Identities
▻https://nightingaledvs.com/beyond-the-binary

Personal and group identity are foundational to the human experience, shaping our values, relationships, and self-perceptions. These identities intersect across categories like gender, race, ethnicity,..

#Charts #Data_Humanism #Design

From Moonsighting to Ramadan Data Journaling
▻https://nightingaledvs.com/from-moonsighting-to-ramadan

As I was heading out to the mosque for the evening prayer, I heard a soft voice from the kitchen—”Abbu, wait! I’ll join you.”It was..

#Charts #Data_Visualization #Design #Kids_Dataviz

Why Your Teen Doesn’t Care About Driving
▻https://nightingaledvs.com/why-your-teen-doesnt-care-about-driving

My own parents were baffled when I showed no interest in getting a permit or driver’s license in high school, and looking around my school,..

#Charts #Data_Visualization #Interactive

‘I hope this isn’t for weapons’ : How Syrian #data_workers train AI

The development and training of AI systems depend on hundreds of millions of data workers. Many of them are situated or displaced from the Global majority, and are generally kept in the dark on how the data they produce will be used.

I met Fatma in June 2019 in Sofia, Bulgaria. Four years prior, she had been forced to leave her home in Aleppo with her whole family: her mother, father, older brother, and two younger siblings. Fatma was 17 when her parents paid the equivalent of nine thousand euros to men who smuggled the seven family members in the back of a van across landscapes and borders, until reaching Finland via Sofia. The smugglers had promised a house and a car in Finland for the sum paid, but this promise went unfulfilled. Instead, after six months, Fatma’s family was deported to Bulgaria because their “fingerprints were registered in Sofia first.” “We lost everything to have a good life because our lives were in danger,” she lamented. “Were they in danger because of the war?” I asked. “It was personal,” she replied cryptically.

Fast forward to 2019, and Fatma, now 21, was living with her family in a refugee camp in the Bulgarian capital. While assisting her father at the camp’s hairdressing salon, she also worked part-time for the data-labeling company where I was conducting fieldwork. Interestingly, she was recruited by the company at the refugee camp. Following initial training in “digital skills” and English, Fatma was ready to assume her role as a data worker. During our initial conversation, she was at the company’s office, seated alongside Diana, another Syrian asylum seeker who was engaged in labeling images of people based on race, age, and gender. In contrast, Fatma was immersed in a project that involved satellite images and semantic segmentation—a critical task for computer vision that involves the meticulous separation and labeling of every pixel in an image. This form of data work holds particular importance in generating training data for AI, especially for computer vision systems embedded in devices such as cameras, drones, or even weapons. Fatma explained that the task basically consisted of separating “the trees from the bushes and cars from people, roads, and buildings.” Following this segmentation, she would attach corresponding labels to identify each object.
Data Work Requires Skill

Explained in this manner, the work might seem trivial and straightforward. Such tasks fall under what is known as microwork, clickwork, or, as I refer to it, data work. This constitutes the labor involved in generating data to train and validate AI systems. According to the World Bank, there are between 154 million and 435 million data workers globally, with many of them situated in or displaced from the World Majority. They often work for outsourcing platforms or companies, primarily as freelancers, earning a few cents per piece or task without the labor protections, such as paid sick leave, commonly found in more traditional employment relationships. Data workers generate data through various means that range from scraping information from the internet to recording their voices or uploading selfies. Similar to Fatma, they frequently engage in labeling tasks. Additionally, data workers may contribute to algorithm supervision, such as rating the outputs of recommender systems on platforms like Netflix or Spotify and assessing their usefulness, appropriateness, and toxicity. In other instances, data workers might be tasked with plainly impersonating non-existing AI systems and be instructed to “think like a robot” while pretending to be a chatbot, for instance.

Despite its crucial role in the development and maintenance of AI technologies, data work is often belittled as micro or small, involving only a few clicks, and dismissed as low-skill or blue-collar. In fact, the platform Clickworker, a prominent provider of on-demand data work, claims on its website that “the tasks are generally simple and do not require a lot of time or skill to complete.” However, this assertion is inaccurate. During my fieldwork in Bulgaria, for instance, I attempted to segment and label satellite imagery, finding it extremely challenging. The work demands precision when drawing polygons around different objects in the pictures, which is also strenuous on the eyes and hands. Moreover, it requires contextual knowledge, including an understanding of what vegetation and vehicles look like in specific regions. Following the segmentation and labeling process by Fatma and her team, a rigorous quality check is conducted by a woman in the client’s company. Fatma’s manager in Bulgaria mentioned that the quality control person was “remarkably fast with the quality check and feedback” and added, “She’s able to do this quickly because she knows the images and the ground.” While taking note of this, I wondered how well the quality controller knows the ground. Does she come from the area where these images were taken? Is she, like Fatma, a refugee? Has her displacement been leveraged as expertise?

I asked Fatma if the satellite images she was working on could be of Syria. She said she thought the architecture and vehicles looked familiar. Staring at the screen, she whispered, “I hope this isn’t for weapons.” Neither she nor I could be certain.
The Known and the Unknown

Fatma’s fear of the satellite images being used for AI weapons is not unfounded. The proliferation of autonomous drones and swarm technologies has experienced exponential growth in recent years, facilitated by the integration of AI in reconnaissance, target identification, and decision-making processes. Illustrating a poignant example, facial recognition technologies have been utilized to uphold the segregation and surveillance of the Palestinian people, while automated weapons have played a crucial role in the ongoing genocide in Gaza. Companies like the Israeli SmartShooter boast about their lethal capabilities with the slogan “One Shot, One Hit.”

Surveillance drones, predictive analytics, and decision support systems are utilized for strategic planning in “threat anticipation” and real-time monitoring along border regions. For instance, the German Federal Office for Migration and Refugees (BAMF) employs image biometrics for identity identification and voice biometrics for dialect analysis to ascertain asylum seekers’ country of origin and evaluate their eligibility for asylum. This system purportedly recognizes dialects of Arabic, Dari, Persian/Farsi, Pashto, and Kurdish. As revealed by BAMF in response to a query initiated by German MPs, data workers subcontracted through the platform Clickworker (the same platform that claims tasks are simple and low-skill) participated in producing the voice samples required to develop the system.

Fortunately, the data company in Bulgaria has a strong policy in place to reject requests related to warfare technologies. Fatma’s manager explained that “we have rejected projects related to (…) training artificial intelligence for different types of weapon applications. So, I felt that this really did not fit with our social mission, and when I responded to the client, I said that we’re working with conflict-affected people, and that’s why (…) But it was also a kind of boycott of such projects to be developed at all.” She added that the satellite imagery labeled by the team had been commissioned by a central European firm developing autonomous piloting systems for air transportation, not weapons. This information correlates with the client’s website. However, the website also states that their technology is additionally used for unmanned aerial vehicles (UAV), commonly known as drones, with applications including surveillance.
Workers’ Ethical Concerns

Privacy infringements and the potential for discriminatory profiling are among the most obvious concerns related to AI systems applied to border surveillance and warfare. Despite these risks disproportionately affecting their own communities, sometimes with lethal consequences, most data workers are kept in the dark concerning the ultimate purpose of the data they contribute to producing. The outsourcing of data work to external organizations, often situated far away from the requesters’ geographical location, complicates workers’ efforts to navigate the intricate supply chains that support the AI industry. Instructions given to data workers seldom provide details about the requester or the intended use of the data. Consequently, most data workers do not know the name and nature of the companies seeking their services, the products that will be trained on the datasets they generate, or the potential impacts of these technologies on individuals and communities. AI companies frequently rationalize the veil of secrecy as a means of safeguarding their competitive edge.

The fact that data workers are integrated into industrial structures designed to keep them uninformed and subject to surveillance, retaliation, and wage theft does not mean that they do not have ethical concerns about their work and the AI applications it supports. In fact, there have been instances where data workers have explicitly alerted consumers to privacy-related and other ethical issues associated with the data they generate. For example, in 2022, Venezuelan data workers reported anonymously that Roomba robot vacuum cleaners capture pictures of users at home, which are then viewed by human workers.

Amid the COVID-19 pandemic in 2021, I piloted a workshop series with fifteen data workers, this time located in Syria. The three-day event was designed to understand work practices and relationships in geographically distributed data-production contexts, creating a space for workers to discuss concerns. The workshop activities revealed that receiving information and having spaces to voice and discuss the ethical implications of the data they handle were of the utmost importance to the workers. They worried about the protection of data subjects’ privacy and advocated for a mandatory clause that would compel requesters to disclose the intended uses of the data. Additionally, the workers expressed concerns about the mental health implications of working with violent, offensive, or triggering data.

Data workers possess a unique vantage point that can play a crucial role in the early identification of ethical issues related to data and AI. Encouraging consumers and society at large to align with them in advocating for increased transparency in the AI data production pipeline is essential. Workers like Fatma and her colleagues could offer valuable insights into the utilization of satellite images for surveillance technologies, for instance. Similarly, the native speakers who contributed their voices to generate audio snippets for dialect recognition may shed light on the applications of such systems against asylum seekers in Germany.

Unfortunately, the challenge lies in the fact that the AI industry, for evident reasons, has structured its production processes for data workers to function more as silent tools than as whistleblowers.

▻https://untoldmag.org/i-hope-this-isnt-for-weapons-how-syrian-data-workers-train-ai
#travailleurs_de_données #entraînement #IA #AI #intelligence_artificielle #éthique #réfugiés #dublinés #camps_de_réfugiés #segmentation #travail #algorithmes #images_satellitaires #labeling #armes #armement #drones #voix #profiling #contrôles_frontaliers

3 Data Points from New DVS Board Members
▻https://nightingaledvs.com/3-data-points-2025

The start to 2025 saw the induction of four new #Data_Visualization Society board members. As they begin their respective duties to elevate DVS, we..

#Community #Data_Visualization_Society

3 Data Points from New DVS Board Members
▻https://nightingaledvs.com/3-data-points-from-new-dvs-board-members-2

The start to 2025 saw the induction of four new #Data_Visualization Society board members. As they begin their respective duties to elevate DVS, we..

#Community #Data_Visualization_Society

https://www.afnic.fr/wp-media/uploads/2025/03/Capture-decran-2025-03-05-143036-768x432.jpg

👷‍♀️ Le secteur du bâtiment ne néglige pas sa présence en ligne !

📊 79 % des entreprises du BTP françaises interrogées disposent d’un site web.

🌐 Découvrez tous les chiffres clés de la présence en ligne des professionnels du BTP dans notre nouvelle étude sectorielle Réussir avec le web ▻https://www.afnic.fr/observatoire-ressources/actualites/les-professionnels-du-btp-font-preuve-dune-grande-maturite-quant-a-leur-presen

#BTP #Batiment #Numérique #France #TransfoNum #Afnic #InternetMadeInFrance #data

Cosmograph: online tool and #javascript library for the visualization and analysis of extensive network #graphs and machine learning embeddings
▻https://github.com/cosmograph-org

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#dataviz #web

États-Unis : la pollution des data centers pèse sur la santé publique - Next
▻https://next.ink/173587/etats-unis-la-pollution-des-data-centers-pese-sur-la-sante-publique

Aux États-Unis, les data centers ont provoqué plus de 5,4 milliards de dollars de dépenses de santé publique de 2019 à 2024, selon une récente étude de quantification de l’impact de l’IA sur les émissions de carbone et la consommation d’eau.

Mais comment a-t-on pu laisser faire des études pareilles, qui coûtent chers et ne servent à rien d’autre qu’à décourager les entrepreneurs qui nourrissent la planète ?

Napoleon, Trump, and the Best Statistical Graphic Ever Drawn
▻https://nightingaledvs.com/napoleon-trump-best-statistical-graphic

Now that I have your attention, let me ask you three simple yes-or-no questions. Why you have seen Minard’s diagram of Napoleon’s invasion of RussiaWhen..

#Charts #Data_Visualization #Historic_Dataviz

Pilule qui rallonge la vie des chiens, fait projet aux humains.
▻http://www.argotheme.com/organecyberpresse/spip.php?article4731

Les animaux de compagnie occupent une place énorme dans la vie et le portefeuille de leurs propriétaires. Une enquête de 2023 du Pew Research Center a révélé que 62 % des Américains possèdent un animal de compagnie et que 97 % des propriétaires le considèrent comme faisant partie de leur famille. Alors, il est difficile de s’en séparer. High-tech / Sciences

/ Sciences & Savoir, #médecine,_sciences,_technologie,_ADN,_vaccin,_médicaments,_découvertes, #Data_-_Données, #arts,_culture,_littérature,_cinéma,_critique,_performances,_styles, #Ecologie,_environnement,_nature,_animaux

#High-tech_/_Sciences #Sciences_&_Savoir

#Data_rescue - Wikipedia
▻https://en.wikipedia.org/wiki/Data_rescue

Data rescue is a movement among scientists, researchers and others to preserve primarily government-hosted data sets, often scientific in nature, to ward off their removal from publicly available websites. While the concept of preserving federal data existed before, it gained new impetus with the election in 2016 of U.S. President Donald Trump.

The concept of harvesting and preserving federal web pages began as early as 2008, at the conclusion of President George W. Bush’s second term, under the name “End of Term Presidential Harvest.”[1]

Soon after #Trump's_election, #scientists, #librarians and others in the U.S. and Canada—fearing that the administration of Trump (who had denied the validity of the scientific consensus on the existence of climate change[2]) would act to remove scientific data from government websites[3]—began working to preserve those data.

Quickly, the concept of data rescue became a grassroots movement, with organized “#hackathon” events at cities across the U.S. and elsewhere, often hosted at universities and other institutions of higher education.

►https://www.datarescueproject.org

▻https://climatemirror.org

It’s easier than ever to scrub your #personal info from #google Search
▻https://arstechnica.com/google/2025/02/google-makes-it-easier-to-remove-your-personal-data-from-search

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#privacy #results #data #removal

Google gives up on data voids
▻https://www.platformer.news/google-data-voids-warning-banners-2024-election

https://www.platformer.news/content/images/size/w1200/2025/02/Screenshot-2025-02-24-at-5.40.58-PM.png

Google quietly stopped showing warning banners that alerted users to potentially unreliable search results in the weeks leading up to the 2024 US presidential election, despite no obvious improvement in the quality of those results, according to a new study from researchers at Stanford and Carnegie Mellon University.

The researchers collected their first data in October 2023 and March 2024. Initially, they were struck by how inconsistently Google showed its warnings. A deep learning model they built to analyze the queries suggested that the warnings should have appeared between 29 and 58 times as often as they did in practice. For motivated conspiracy peddlers, they were easy to evade: just adding quotation marks or a single letter to a query was typically enough to make the banner disappear

Google confirmed to Platformer that it had discontinued the banners after finding that unspecified improvements to its core search engine had caused the warnings to trigger less often.

“As the result of a ranking quality improvement last year, the specific notice mentioned in this paper was not meeting our thresholds for helpfulness — it was surfacing extremely infrequently and was triggering false positives at a high rate, so we turned it down,” a spokesman said in an email.

I asked Google if it could share what “improvements” had resulted in the warnings appearing less often. (It’s not clear to me that this is a “ranking” problem, exactly — by definition, data voids have very few results.) The company declined to do so.

The company also said that the queries studied by researchers represent a tiny fraction of searches and are not representative of how most people use Google.

As an alternative to the banners, the company suggested that people use the “about this result” feature on the search engine results page, which uses information from Wikipedia to highlight websites known for spreading conspiracy theories. (Click or tap the three vertical dots next to the URL to find it.)

I asked danah boyd, a co-author of the original 2019 report about data voids, what she made of Google’s retreat.

“The whole point of “data voids” is that these are parts of the search query spaces where there is simply too little meaningful content to return without scraping the bottom of the barrel,” she told me.

boyd noted that not all data voids are dangerous. But it’s important that platforms continue to take it seriously, she said.

“As with all security issues, there is no magical ‘fix’ — there is only a constantly evolving battle between a system’s owners and its adversaries,” boyd said. “So if Google is getting rid of some of its tools to combat this security issue, is the company effectively saying ‘game on’ to any and all manipulators? That seems like a bad strategy.”

#Google #Désinformation #Data_voids #Conspirationisme

How to Get a Job
▻https://nightingaledvs.com/how-to-get-a-job

This article was originally published in Nightingale Magazine Issue 5 as “How to #Get_Work”.Not many people know this, but I had a protracted search..

#Career #Data_Jobs #hiring #interview #job_interview #Work

Données personnelles : les échanges avec l’Europe menacés par les États-Unis - Next
▻https://next.ink/171767/donnees-personnelles-les-echanges-avec-leurope-menaces-par-les-etats-unis

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#DataPrivacyFramework #PCLOB #surveillance #vieprivée #politique #privacyshield #europe #US

Hydrogène vert en Algérie : étude de perspectives prometteuses.
▻http://www.argotheme.com/organecyberpresse/spip.php?article4724

L’Algérie dispose d’un potentiel remarquable pour la production d’électricité solaire, en utilisant des panneaux photovoltaïques monocristallins d’une puissance nominale de crête de 250 W et d’un rendement de 15,28 %. Ce qui encourage à fabriquer de l’hydrogène comme #énergie moins nocive pour la préservation de la planète et pour juguler la crise climatique. #Climat

/ économie , Maghreb, Algérie, Tunisie, Maroc, Libye, Africa, population, société , #Arabie_Saoudite,_Qatar,_Koweït,_EAU,_Moyen-Orient,_monarchies,_arabes,_musulmans, #Ecologie,_environnement,_nature,_animaux, Sciences & Savoir, énergie, #Data_-_Données, (...)

#économie_ #Maghreb,Algérie,_Tunisie,_Maroc,_Libye,_Africa,_population,_société #Sciences_&_Savoir #actus

What Does AI Understand About a Graph?
▻https://nightingaledvs.com/what-does-ai-understand-about-a-graph

A Conversation With a Chatbot About a Graph How much does AI know about understanding and producing graphs? I don’t mean mathematical graphs of nodes and edges. Rather, I mean common graphs..

#Data_Visualization #White_Paper

Data Rescue Project
►https://www.datarescueproject.org

https://www.datarescueproject.org/content/images/2025/02/drp-feature-preview-2.png

What is the Data Rescue Project?

The Data Rescue Project is a coordinated effort among a group of data organizations, including IASSIST, RDAP, and members of the Data Curation Network. Our goal is to serve as a clearinghouse for data rescue-related efforts and data access points for public US governmental data that are currently at risk.

How can I help?

Regardless of your background or level of comfort with data, there are a number of tasks and projects under way, all requiring different skills and expertise.

Examples of potential tasks:

Identifying data for download
Finding and confirming alternate locations of federal data
Downloading data from federal resources
Uploading data into Data Lumos
Research assistance or answering reference questions
Creating and updating inventories
Identifying potential Data Rescue Project collaborators
Troubleshooting technical issues
Data curation, metadata, and data documentation
And more!

…

Contre la purge « sans précédent » des sites ordonnée par trump, les archivistes du numérique à l’offensive
Des décrets signés par le nouveau présipotent des Etats-Unis ont entraîné la disparition de milliers de pages, liées notamment au changement climatique ou aux politiques d’égalité. Plusieurs initiatives coordonnées cherchent à les préserver.

Les déchets inondent un Monde à plus large expansion économique.
▻http://www.argotheme.com/organecyberpresse/spip.php?article4722

Une fois collectés, les déchets sont ensuite transportés vers des sites pour être mis en décharge, recyclés, compostés, récupérés et même des fois expédiés à l’étranger, vers certains pays d’Asie et d’Afrique. Les volumes continuent de croître, inondant le recyclage qui s’est amélioré pour subir le flux. Alors que la mise en stock ou en fouissement n’est pas élimination et est encore la réception la plus courante dans le monde. #Climat

/ économie , #Data_-_Données, diplomatie, sécurité, commerce, #économie_mondiale, #crise,_capitalisme,_économie,_justice,_Bourse, #calamités_naturelles, #Ecologie,_environnement,_nature,_animaux, #Réchauffement_climatique, Sciences & (...)

#diplomatie,_sécurité,_commerce,_économie_mondiale #Sciences_&_Savoir

#Good_Morning_Data #9 | The Error Message Longing
▻https://nightingaledvs.com/good-morning-data-9-the-error-message-longing

The Error Message Longing or “How we should always treasure our mistakes“The conversation was loud and happy, scattered with high-pitched laughs that were probably annoying..

#Career #Data_Visualization

Siri visé par une plainte en France : le long combat d’un lanceur d’alerte
▻https://www.telerama.fr/debats-reportages/siri-vise-par-une-plainte-en-france-le-long-combat-d-un-lanceur-d-alerte-70

https://focus.telerama.fr/2025/02/14/374/0/1701/1134/1200/800/60/0/cee6944_sirius-fs-upload-1-xecgtj6578ma-1739536055829-jj108437.jpg

Il y a quatre ans, Télérama avait rencontré ce jeune Français, recruté à la sortie de l’université comme sous-traitant de l’entreprise à la pomme. En 2019, répondant à une offre d’emploi mystérieuse et bardée de clauses de confidentialité, il ne connaît alors pas l’identité de son employeur final. Tout juste sait-il qu’il devra « contrôler la qualité de la donnée ». Il accepte, s’envole pour Cork, à deux heures de Dublin, haut lieu de l’optimisation fiscale. Là-bas, salarié par une société du nom de GlobeTech, il est chargé d’écouter et de retranscrire mille trois cents enregistrements, « parfois très intimes ou violents », par jour. Objectif, bien avant la hype autour de ChatGPT : entraîner l’intelligence artificielle de Siri, embarqué dans les iPhone depuis 2011. Au bout de quelques semaines, il prend la tangente. « Ce boulot rend tellement mou que j’ai craqué à retardement », nous expliquait-il alors, décrivant des conditions de travail éprouvantes, soumises au secret.

Watergate domestique

Des universitaires, comme la sociologue américaine Sarah T. Roberts, pointent de longue date les risques psychosociaux, et même de stress post-traumatique, de ces métiers invisibles du numérique ; mais ils restent indispensables à la bonne marche du capitalisme extractiviste des plateformes. Thomas Le Bonniec décide alors de dénoncer ce Watergate domestique, convaincu qu’il s’agit « d’un système d’écoute à grande échelle ». Il alerte la presse anglo-saxonne dès l’été 2019, ce qui pousse Apple à suspendre momentanément son programme d’évaluation de Siri. De son côté, GlobeTech annonce le licenciement de trois cents salariés. En réalité, ils sont mis au chômage technique pendant six semaines, le temps pour la Californie de dépêcher une équipe en urgence, afin de relancer la machine. Enfreignant sa clause de confidentialité, le jeune homme sort même de l’anonymat et saisit les agences de protection des données européennes. Las, la Cnil irlandaise a classé sans suite son signalement à l’été 2022. Sans jamais ouvrir d’enquête. D’où cette nouvelle offensive sur le front judiciaire français.

Hasard – ou non – du calendrier, la justice californienne doit valider ce vendredi une procédure à l’amiable dans une affaire similaire, qui concerne aussi #Siri : visé par un recours collectif d’utilisateurs américains, Apple, qui a toujours réfuté les accusations de #surveillance, a accepté de payer 95 millions de dollars pour mettre fin aux poursuites. De quoi entacher la réputation de la première capitalisation boursière de la planète, qui met en avant son respect scrupuleux de la vie privée, mais goûte peu qu’on regarde de trop près l’arrière-boutique. En 2023, une autre lanceuse d’alerte, l’Américaine Ashley Gjøvik, nous racontait comment #Apple utilisait ses propres salariés comme cobayes, les obligeant à utiliser des applications clandestines pour entraîner son logiciel de #reconnaissance_faciale, et multipliant les expérimentations pour collecter des #informations_biométriques et améliorer les produits de la marque : scan des conduits auditifs, mesure du sommeil, pression artérielle et même surveillance du cycle menstruel.

#IA

Cinque nuovi #data_center in programma a Torino
▻https://radioblackout.org/2025/02/cinque-nuovi-data-center-in-programma-a-torino

In questi giorni è uscita la notizia di ben cinque progetti di “data center” nella città di Torino e nella cintura. A cosa servono i data center è un primo aspetto che va indagato: per l’archiviazione, l’elaborazione e l’accesso di dati. Un secondo fattore da tenere in considerazione riguarda le proprietà degli investimenti che stanno […]

#L'informazione_di_Blackout #consumo_di_suolo #consumo_idrico #intelligenza_artificiale #leonardo
▻https://cdn.radioblackout.org/wp-content/uploads/2025/02/Data-center-to-2025_02_13_2025.02.13-09.00.00-escopost.mp3

Sur l’App Store et Google Play, les mensonges des applications sur leur usage des données personnelles
▻https://www.lemonde.fr/pixels/article/2025/02/12/sur-l-app-store-et-google-play-les-mensonges-des-applications-sur-leur-usage

Nos recherches se sont focalisées sur un vaste fichier, obtenu par nos partenaires de netzpolitik.org, qui agglomère des informations (notamment des coordonnées géolocalisées) sur plus de 47 millions d’utilisateurs de #téléphones_mobiles. Ces éléments, commercialisés par le courtier en données américain #Datastream_Group, ont été récoltés par l’entremise d’une myriade d’applications mobiles : Le Bon Coin, Candy Crush, Vinted, Grindr… Les différentes personnes que Le Monde et ses partenaires ont pu identifier dans ce fichier ont, d’une même voix, exprimé leur surprise lorsque nous les avons contactées. Aucune d’entre elles ne soupçonnait que leurs #applications préférées pouvaient se transformer en mouchard.

Que les données aient été obtenues de manière licite ou non, ce décalage est frappant. Il s’explique en partie par l’information souvent confuse, complexe ou mensongère livrée aux mobinautes lorsqu’ils ouvrent une nouvelle application après l’avoir téléchargée, au moment de recueillir leur consentement en vue d’utiliser leurs données à des fins commerciales. Mais il plonge aussi ses racines dans ce qui se passe avant, lorsque les utilisateurs de smartphones parcourent le catalogue de l’App Store et du Play Store : c’est là que les applications sont tenues de renseigner des fiches d’informations, censées guider les internautes dans leur choix.

Des notices d’informations peu fiables, en particulier chez Google

Nos recherches montrent à quel point ces notices renseignées par les applications peuvent être peu fiables. Prenons par exemple Flightradar24, qui permet de suivre l’itinéraire d’avions en direct. Sur le store, l’application déclare ne pas collecter ni revendre de données personnelles. Pourtant, le fichier de Datastream comporte des #coordonnées_GPS reliées à 34 572 identifiants publicitaires, déclarées comme issues de Flightradar24.

▻https://justpaste.it/e77fy

#data #data_mining