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"O'Neill recounts an exercise to improve service to homeless families in New York City, in which data-analysis was used to identify risk-factors for long-term homelessness. The problem, O'Neill describes, was that many of the factors in the existing data on homelessness were entangled with things like race (and its proxies, like ZIP codes, which map extensively to race in heavily segregated cities like New York). Using data that reflects racism in the system to train a machine-learning algorithm whose conclusions can't be readily understood runs the risk of embedding that racism in a new set of policies, these ones scrubbed clean of the appearance of bias with the application of objective-seeming mathematics. "

"Chinese consumers are increasingly standing up to Internet giants for their digital privacy in an unprecedented way. China is in the early stages of setting up a data protection regulatory system. The Cyber Security Law, effective Jun 1, 2017, included for the first time a set of data protection provisions in the form of national-level legislation. The 2018 e-Commerce Law incorporated data privacy protections for consumers such as the "right to be forgotten", similar to the EU's General Data Protection Regulation."

"The robust way to do that, the way that can't be set aside at the whim of a government, is to require systems to be built so as not to collect data about a person. The basic principle is that a system must be designed not to collect certain data, if its basic function can be carried out without that data."

"This text is the AI's mainsource of information about the world as it is being built, and it influences how it responds to users. If it aces the bar exam, for example, it's probably because its training data included thousands of LSAT practice sites. Tech companies have grown secretive about what they feed the AI. So The Washington Post set out to analyze one of these data sets to fully reveal the types of proprietary, personal, and often offensive websites that go into an AI's training data."

""Anonymised" data lies at the core of everything from modern medical research to personalised recommendations and modern AI techniques. Unfortunately, according to a paper, successfully anonymising data is practically impossible for any complex dataset."

"Creepy grabs all this geo-location data and puts pins on a map for you. Most of the time, you probably remember to get the privacy settings right. But if you get it wrong just once - maybe the first time you used a new app, maybe before your friend showed you how to change the settings - Creepy will find it, and your home is marked on a map"

Data visibility is an important aspect to achieve the highest potential of the healthcare system for all. Right now most countries are still stuck with a decentralised set of data or no digitalisation at all. This leads to harder distribution and stocking of resources, using supply-chains and making decisions, this also includes every form of system with a high population and research. There are 4 factors in achieving data visibility. Stakeholder commitment, road map to digitalisation, data capability and interoperability.

"Launched in April, the smartphone app Smittestopp ("infection stop") was set up to collect movement data to help authorities trace the spread of Covid-19, and inform users if they had been exposed to someone carrying the virus. On Friday, the data agency Datatilsynet issued a warning that it would stop the Norwegian Institute of Public Health from handling data collected via Smittestopp."

"The problem extends beyond the Pegasus project. Installed in Mexico City is one of the largest urban surveillance systems in the Americas: El Centro de Comando, Control, Cómputo, Comunicaciones y Contacto Ciudadano, better known as El C5. The network, connected to panic buttons and command centers, is spread over 1,485 kilometers with software designed to automatically detect license plates. On top of that, the number of installed cameras grew from 18 million to 65 million between 2018 and 2022, with stated plans to add at least an additional 16 million more. Despite its apparent pre-eminence, issues have arisen with the C5, from false identifications to mishandling of personal data. Technological malfunctions have also been shown to impact the outcomes of criminal cases because of the assumption of objectivity that video surveillance supposedly construes. The sprawling C5 system is dwarfed only by the Titan, an expansive intelligence and security database, both in terms of scale and threat to civil liberties. The software is used by several Mexican state governments to combine location data with other private information, including financial, government, and telecom data, to geolocate individuals across the country in real time. Governmental officials have been criticized for the controversial use of the database to target public figures, but, more problematically, access to Titan-enabled intel can be gained through an underground market, making it a further liability. The extent to which artificial intelligence has been incorporated into the C5 and Titan is still not clear, but the specter of surveillance remains large and is set to cause more worries with the addition of new smart technologies."

"Surrendering our privacy to the government would be foolish enough. But what is more insidious is the Faustian bargain made with the marketing industry, which turns every location ping into currency as it is bought and sold in the marketplace of surveillance advertising. Now, one year later, we're in a very similar position. But it's far worse. A source has provided another data set, this time following the smartphones of thousands of Trump supporters, rioters and passers-by in Washington, D.C., on January 6, as Donald Trump's political rally turned into a violent insurrection. At least five people died because of the riot at the Capitol. Key to bringing the mob to justice has been the event's digital detritus: location data, geotagged photos, facial recognition, surveillance cameras and crowdsourcing."

"US and European fears about China exploiting TikTok's data harvest and promoting Beijing's worldview look set to inspire an urgent overhaul in data privacy laws"

""I consider 'bias' a euphemism," says Brandeis Marshall, PhD, data scientist and CEO of DataedX, an edtech and data science firm. "The words that are used are varied: There's fairness, there's responsibility, there's algorithmic bias, there's a number of terms… but really, it's dancing around the real topic… A dataset is inherently entrenched in systemic racism and sexism.""

"A newly released set of slides from the Snowden leaks reveals that the NSA is harvesting millions of facial images from the Web for use in facial recognition algorithms through a program called "Identity Intelligence." James Risen and Laura Poitras's NYT piece shows that the NSA is linking these facial images with other biometrics, identity data, and "behavioral" data including "travel, financial, behaviors, social network." "

"Wired recently started an anti-ad-blocking campaign that attempts to prevent ad-blocked users from reading articles unless they pay a monthly subscription fee. On the heels of this decision comes a roundup of the major ad-blockers, some of which are pretty dodgy indeed. Adblock Plus comes off the worst of the lot. The company charges publishers fees to allow their ads through its filters, based on criteria about size and placement. Ghostery blocks trackers, but by default gathers "anonymized" data about your browsing habits (it's very hard to conclusively describe any deep data set as anonymized). "

"The mapping information could ostensibly tell third-parties when the owners are most often home, the shape of rooms, the size of houses, and even the frequency of cleanings. Gizmodo imagines that a room's shape could be valuable to Amazon as information on the acoustics of a room containing an Alexa device, informing both volume and directional settings so that its broadcasting and microphone can work properly. "

"We need to look at the nose to tail production of artificial intelligence. The seeds of the data problem were planted in the 1980s, when it became common to use data sets without close knowledge of what was inside, or concern for privacy. It was just "raw" material, reused across thousands of projects."

"The researchers, Tero Karras, Samuli Laine, and Timo Aila, came up with a new way of constructing a generative adversarial network, or GAN. GANs employ two dueling neural networks to train a computer to learn the nature of a data set well enough to generate convincing fakes. When applied to images, this provides a way to generate often highly realistic fakery. The same Nvidia researchers have previously used the technique to create artificial celebrities (read our profile of the inventor of GANs, Ian Goodfellow)."

"The new feature, part of a wider set of tools covering "off-Facebook activity", will not delete anything from Facebook's servers, instead simply "disconnecting" data from an individual user's account."

"So when I discovered the pocket of Instagram where you can find out what it thinks you're interested in (on the app, you'll find it under Settings> Security> Access data > Ads), I obviously felt it my duty as a netizen to see what dark insights it had into my private soul. Here goes: jewellery; luxury goods; electronic music; love; emotions; fashion design; crafts. I mean: no offence, Kraftwerk (and loved ones) but I could not name eight things I am less interested in. Maybe oxbow lakes."

"If you use the default settings above, it would take millions of years to guess your master password using generally-available password-cracking technology. Your sensitive vault data, such as usernames and passwords, secure notes, attachments, and form-fill fields, remain safely encrypted based on LastPass' Zero Knowledge architecture. There are no recommended actions that you need to take at this time. "