Summary of “Find out the environmental impact of your Google searches and internet usage”

“Data is very polluting,” says Joana Moll, an artist-researcher whose work investigates the physicality of the internet.
“Almost nobody recalls that the internet is made up of interconnected physical infrastructures which consume natural resources,” Moll writes as an introduction to the project.
CO2GLE uses 2015 internet traffic data, Moll says, and is based on the assumption that Google.com “Processes an approximate average of 47,000 requests every second, which represents an estimated amount of 500 kg of CO2 emissions per second.” That would be about 0.01 kg per request.
One estimate from British environmental consultancy Carbonfootprint puts it between 1g and 10g of CO2 per Google search.
Speaking at the Internet Media Age conference in Barcelona last week, Moll showed another visualization, which she calls “DEFOOOOOOOOOOOOOOOOOOOOOREST,” to drive home the point.
Moll’s research focused on Google because of its scale, but other websites also contribute to the internet’s carbon footprint.
“What I’m really trying to do is to trigger thoughts and reflections on the materiality of data and materiality of our direct usage of the internet,” Moll says.
“To calculate the CO2 of the internet is really complicated. It’s the biggest infrastructure ever been built by humanity and it involves too many actors. numbers that can serve to raise awareness.”

The orginal article.

Summary of “I am a data factory”

Am I a data mine, or am I a data factory? Is data extracted from me, or is data produced by me? Both metaphors are ugly, but the distinction between them is crucial.
If I am a data mine, then I am essentially a chunk of real estate, and control over my data becomes a matter of ownership.
Who owns me, and what happens to the economic value of the data extracted from me? Should I be my own owner – the sole proprietor of my data mine and its wealth? Should I be nationalized, my little mine becoming part of some sort of public collective? Or should ownership rights be transferred to a set of corporations that can efficiently aggregate the raw material from my mine and transform it into products and services that are useful to me? The questions raised here are questions of politics and economics.
Thinking of the platform companies as being in the extraction business, with personal data being analogous to a natural resource like iron or petroleum, brings a neatness and clarity to discussions of a new and complicated type of company.
We can use the recent data controversies to articulate a truly decentralised, emancipatory politics, whereby the institutions of the state will be deployed to recognise, create, and foster the creation of social rights to data.
When I upload a photo, I produce not only behavioral data but data that is itself a product.
I am, in other words, much more like a data factory than a data mine.
Beyond control of my data, the companies seek control of my actions, which to them are production processes, in order to optimize the efficiency, quality, and value of my data output.

The orginal article.

Summary of “Cambridge Analytica: how did it turn clicks into votes?”

How do 87m records scraped from Facebook become an advertising campaign that could help swing an election? What does gathering that much data actually involve? And what does that data tell us about ourselves?
For those 87 million people probably wondering what was actually done with their data, I went back to Christopher Wylie, the ex-Cambridge Analytica employee who blew the whistle on the company’s problematic operations in the Observer.
According to Wylie, all you need to know is a little bit about data science, a little bit about bored rich women, and a little bit about human psychology…. Step one, he says, over the phone as he scrambles to catch a train: “When you’re building an algorithm, you first need to create a training set.” That is: no matter what you want to use fancy data science to discover, you first need to gather the old-fashioned way.
The “Training set” refers to that data in its entirety: the Facebook likes, the personality tests, and everything else you want to learn from.
Facebook data, which lies at the heart of the Cambridge Analytica story, is a fairly plentiful resource in the data science world – and certainly was back in 2014, when Wylie first started working in this area.
In order to be paid for their survey, users were required to log in to the site, and approve access to the survey app developed by Dr Aleksandr Kogan, the Cambridge University academic whose research into personality profiling using Facebook likes provided the perfect access for the Robert Mercer-funded Cambridge Analytica to quickly get in on the field.
Where the psychological profile is the target variable, the Facebook data is the “Feature set”: the information a data scientist has on everyone else, which they need to use in order to accurately predict the features they really want to know.
How Cambridge Analytica turned Facebook likes into votes.

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Summary of “You Can’t Opt Out Of Sharing Your Data, Even If You Didn’t Opt In”

We’re used to thinking about privacy breaches as what happens when we give data about ourselves to a third party, and that data is then stolen from or abused by that third party.
“One of the fascinating things we’ve now walked ourselves into is that companies are valued by the market on the basis of how much user data they have,” said Daniel Kahn Gillmor, senior staff technologist with the ACLU’s Speech, Privacy and Technology Project.
The privacy of the commons is how the 270,000 Facebook users who actually downloaded the “Thisisyourdigitallife” app turned into as many as 87 million users whose data ended up in the hands of a political marketing firm.
Even if you do your searches from a specialized browser, tape over all your webcams and monitor your privacy settings without fail, your personal data has probably still been collected, stored and used in ways you didn’t intend – and don’t even know about.
The information collected every time they scan that loyalty card adds up to something like a medical history, which could later be sold to data brokers or combined with data bought from brokers to paint a fuller picture of a person who never consented to any of this.
The privacy of the commons means that, in some cases, your data is collected in ways you cannot reasonably prevent, no matter how carefully you or anyone you know behaves.
Our digital commons is set up to encourage companies and governments to violate your privacy.
Almost all of our privacy law and policy is framed around the idea of privacy as a personal choice, Cohen said.

The orginal article.

Summary of “Who should hold the keys to our data?”

Within 48 hours, the data had been turned from a pile of figures into a resource that could save lives and that could help people to pressure government to deal with black spots.
There is big data, personal data, open data, aggregate data and anonymised data.
The single thing that every citizen and every corporate decision-maker needs to understand is that the enormous data stores that government, government agencies, corporations, trusts and individuals hold are as much a key part of national and international infrastructure as the road network.
Several companies have practical designs that offer each individual their own data account, on a cloud independent of any agency or commercial organisation.
The data would be unreadable as a whole to anyone other than the individual owner, who would allow other people access to selected parts of it, at their own discretion.
There are real gains to be made if citizens hold their own data and huge organisations don’t.
Yes, yes, the spooks and cops want to keep their own files about terrorists and not discuss the morals of data retention much with the lucky names on the list, and we are perfectly happy with that.
The central requirement is that, if you own a car, that fact and details of your car must be in your data store, whether you like it or not; authorised agencies must be able to look simultaneously at everyone’s store, to find a car they are interested in and must be able to do it without you knowing.

The orginal article.

Summary of “How Do You Control 1.4 Billion People?”

While outside observers agree that the situation likely bodes ill for many unwitting citizens, few have considered how vulnerable the system is to the corruption, con artistry, and incompetence that plagues much of Chinese society.
Who will have access to the data, and how will they be able to use or abuse it? Will it be shared between ministries and departments, or jealously guarded? Can it be manipulated, altered, faked-or stolen?
Sesame Credit requires highly sensitive personal information, such as degree certificates and title deeds, to be uploaded to its cloud to enhance users’ credit scores-cybersecurity experts say such a centralized digital database would be a treasure trove for hackers.
“Sesame Credit… is still unable to control the quality of the data reported by partner lenders,” observed a Caixin article.
It’s not just businesses and crooks looking to game the latest gimmick: Already accustomed to having their data mined and lives surveilled, tech-savvy Chinese are wondering how they can rig their scores-and entrepreneurial hackers will be more than willing to oblige.
What’s that? Sesame scores are connected to the frequency you use your credit cards? Simple-my company will help swipe and repay your card for a year, then charge you for how many points your score accumulates.
Marbridge’s Natkin acknowledges some dangers and drawbacks, but suggests social credit ratings “Will also create a greater disincentive to engage in anti-social behavior, like a landlord capriciously deciding not to return a security deposit, or a shared-bike user parking in the middle of the street.” These are everyday grievances in China’s scofflaw society that many will be glad to see gone, or at least punished.
To work effectively, social credit requires Chinese citizens to place complete trust in both their unaccountable government and vast cartel-like corporations.

The orginal article.

Summary of “Open, Closed, and Privacy – Stratechery by Ben Thompson”

The ongoing debate about data and privacy is directly related to the question of encryption in some important ways, as Mossberg’s tweet notes: messaging content is data that users would like to keep private, and encryption accomplishes that.
That gets at the more important way that the relationship between open/closed and encryption is relevant to data and privacy: just as encryption at scale is only possible with a closed service, so it is with privacy.
Just as a closed garden makes the user experience challenge of encryption manageable, so does the centralization of data make privacy – of a certain sort – a viable business model.
One does wonder how much that allegation drives the outrage about the fact that Facebook shared that data to begin with, but leaving that aside, what is noteworthy is that the outrage stems from the sharing of the data, not its collection.
The implication is quite far-reaching: being open, at least to the extent that openness involved user data of any sort, is increasingly unacceptable; that new companies and user benefits might result from that data no longer matters, a fate that all-too-often befalls the not-yet-created.
Most of their competitors for digital advertising, on the other hand, are modular: some companies collect data, and other collect ads; such a model, in a society demanding ever more privacy, will be increasingly untenable.
Brussels wants its new General Data Protection Regulation, or GDPR, to stop tech giants and their partners from pressuring consumers to relinquish control of their data in exchange for services.
Specifically, if an emphasis on privacy and the non-leakage of data is a priority, it follows that the platforms that already exist will be increasingly entrenched.

The orginal article.

Summary of “Cambridge Analytica Data Scientist Aleksandr Kogan Wants You To Know He’s Not A Russian Spy”

At the hearing, Kogan, who’s been accused of being a foreign agent, an unscrupulous scholar, and a mind manipulator, hopes to dispel the myths about himself and the data he collected from millions of Facebook users and handed to Cambridge Analytica’s parent company, SCL Elections.
Kogan also disputes other aspects of the established narrative: that he’s a spy, for one, but also that Cambridge Analytica was capable of predicting individual behavior, that his relationship with Facebook was brief and casual, and that whistleblower Christopher Wylie had extensive knowledge about the data.
“Folks are only concerned right now about the story because they think it could have swung the elections or that they can be mind controlled, and that’s not a real worry,” Kogan said, labeling claims that Cambridge Analytica had effective behavior prediction models as “Nonsense.” The real story, he noted, is that “Folks have woken up” to privacy concerns and their data being and spread without their informed consent.
Facebook, which Kogan said he is currently considering suing for defamation, suggested to the New York Times that he had acted unethically, using an app to collect Facebook user data he claimed was for academic purposes, but later gave to Cambridge Analytica.
Beyond the personal attacks, Kogan said Wylie, who is quoted as having created “Steve Bannon’s psychological warfare tool” has had similar issues standing up claims that he’s made about Cambridge Analytica and its supposed efficacy in swaying voters.
Kogan disputed the notion that his former colleague had any knowledge of data, laughing at the notion that he’d be called a data scientist, and referred to him as someone who was involved in business development and provided legal expertise.
“Chris is as much a data scientist as I am a fashion icon,” Kogan said.
Kogan hopes to illustrate that to parliament on Tuesday, the notion that the Cambridge Analytica scandal is one about privacy and not one about a manipulated election.

The orginal article.

Summary of “How Google Plans To Use AI To Reinvent The $3 Trillion US Healthcare Industry”

“So tomorrow, if AI can shape healthcare, it has to work through the regulations of healthcare In fact, I see that as one of the biggest areas is where the benefits will play out for the next 10 – 20 years.” – Sundar Pichai, CEO of Google.
TABLE OF CONTENTS Google’s structure & AI advantage GOOGLE PRIORITIZES AI. As Google enters healthcare, it’s leaning heavily on its expertise in AI. Health data is getting digitized and structured, from a new electronic record standard to imaging to DNA sequencing.
Below, we’ll largely focus on healthcare initiatives at each of these subsidiaries, but will also discuss how other Google assets – such as Google Cloud, which sits outside of these key organizations – are being leveraged for healthcare.
PUSHING GOOGLE CLOUD. Google has been pushing its Google Cloud platform aggressively in the last few years, especially after hiring ex-VMware CEO Diane Greene to lead the division.
As more researchers build on top of the Google Cloud product suite, Google Cloud becomes more valuable to that team, and Google becomes a more ingrained part of the healthcare infrastructure.
The organization is reportedly looking at working to do this with Oscar in Rhode Island, and recently Verily invested in Oscar’s latest fundraise alongside another Google investing subsidiary, capitalG. HOW WILL GOOGLE MAKE MONEY OFF ITS HEALTHCARE INITIATIVES?
Google has begun selling its own lines of AI-differentiated hardware including Google Home, Google Pixel, and more.
As Google makes a bigger push with its Google Cloud offering and competes with other tech giants, healthcare is an attractive area to sell their storage and services due to the massive amount of data and computing power healthcare – especially data-driven healthcare – requires.

The orginal article.

Summary of “Tesla vs Waymo: who’s winning the race for self-driving cars”

Tesla is taking advantage of the hundreds of thousands of cars it has on the road by collecting real-world data about how those vehicles perform with Autopilot, its current semi-autonomous system.
Tesla is developing towards autonomy by using customer-owned cars to gather that all-important data.
As Tesla sells more cars, the amount of data that can be collected increases exponentially.
Tesla cars can log instances where the Autopilot software would have taken an action, and that data eventually gets uploaded back to Tesla.
Tesla has over 300,000 vehicles on the road around the world, and those cars are navigating far more diverse settings than Waymo – which is currently only in Texas, California, Michigan, Arizona, and Georgia.
Tesla has likely passed that mark by now in real-world miles, and yet its cars still aren’t able to fully drive themselves.
“Why has no one put sensors on their customer cars that collect data like Tesla has?”.
How will the company prove that it’s safe? Tesla does have its own small fleet of test cars registered with the California DMV, but they drove zero miles in 2017.

The orginal article.