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Most Facebook users don’t know that it records a list of their interests, new study finds

Seventy-four percent of Facebook users are unaware that Facebook records a list of their interests for ad-targeting purposes, according to a new study from the Pew Institute.

Participants in the study were first pointed to Facebook’s ad preferences page, which lists out a person’s interests. Nearly 60 percent of participants admitted that Facebook’s lists of interests were very or somewhat accurate to their actual interests, and 51 percent said they were uncomfortable with Facebook creating the list.

Facebook has weathered serious questions about its collection of personal information in recent years. CEO Mark Zuckerberg testified before Congress last year acknowledging privacy concerns and touching upon the company’s collection of personal information. While Zuckerberg said Facebook users have complete control over the information they upload and the information Facebook uses to actively target ads at its users, it’s clear from the Pew study that most people are not aware of Facebook’s collection tactics.

The Pew study also demonstrates that, while Facebook offers a number of transparency and data control tools, most users are not aware of where they should be looking. Even when the relevant information is located, there are often multiple steps to go through to delete assigned interests.

Facebook Filed A Patent To Predict Your Household’s Demographics Based On Family Photos

Facebook has submitted a patent application for technology that would predict who your family and other household members are, based on images and captions posted to Facebook, as well as your device information, like shared IP addresses. The application, titled “Predicting household demographics based on image data,” was originally filed May 10, 2017, and made public today.

The system Facebook proposes in its patent application would use facial recognition and learning models trained to understand text to help Facebook better understand whom you live with and interact with most. The technology described in the patent looks for clues in your profile pictures on Facebook and Instagram, as well as photos of you that you or your friends post.

It would note the people identified in a photo, and how frequently the people are included in your pictures. Then, it would assess information from comments on the photos, captions, or tags (#family, #mom, #kids) — anything that indicates whether someone is a husband, daughter, cousin, etc. — to predict what your family/household actually looks like. According to the patent application, Facebook’s prediction models would also analyze “messaging history, past tagging history, [and] web browsing history” to see if multiple people share IP addresses (a unique identifier for every internet network).

Only 22% of Americans Now Trust Facebook’s Handling of Personal Info

Facebook is the least trustworthy of all major tech companies when it comes to safeguarding user data, according to a new national poll conducted for Fortune, highlighting the major challenges the company faces following a series of recent privacy blunders. Only 22% of Americans said that they trust Facebook with their personal information, far less than Amazon (49%), Google (41%), Microsoft (40%), and Apple (39%).

In question after question, respondents ranked the company last in terms of leadership, ethics, trust, and image… Public mistrust extended to Zuckerberg, Facebook’s public face during its privacy crisis and who once said that Facebook has “a responsibility to protect your information, If we can’t, we don’t deserve it.” The company subsequently fell victim to a hack but continued operating as usual, including debuting a video-conferencing device intended to be used in people’s living rooms or kitchens and that further extends Facebook’s reach into more areas outside of personal computers and smartphones. Only 59% of respondents said they were “at least somewhat confident” in Zuckerberg’s leadership in the ethical use of data and privacy information, ranking him last among four other tech CEOS…

As for Facebook, the social networking giant may have a difficult time regaining public trust because of its repeated problems. Consumers are more likely to forgive a company if they believe a problem was an aberration rather than a systemic failure by its leadership, Harris Poll CEO John Gerzema said.

The article concludes that “For now, the public isn’t in a forgiving mood when it comes to Facebook and Zuckerberg.”

EU Ruling: Self-Driving Car Data Will Be Copyrighted By the Manufacturer

Yesterday, at a routine vote on regulations for self-driving cars, members of the European Peoples’ Party voted down a clause that would protect a vehicle’s telemetry so that it couldn’t become someone’s property. The clause affirmed that “data generated by autonomous transport are automatically generated and are by nature not creative, thus making copyright protection or the right on data-bases inapplicable.” Boing Boing reports:

This is data that we will need to evaluate the safety of autonomous vehicles, to fine-tune their performance, to ensure that they are working as the manufacturer claims — data that will not be public domain (as copyright law dictates), but will instead be someone’s exclusive purview, to release or withhold as they see fit. Who will own this data? It’s unlikely that it will be the owners of the vehicles.

It’s already the case that most auto manufacturers use license agreements and DRM to lock up your car so that you can’t fix it yourself or take it to an independent service center. The aggregated data from millions of self-driving cars across the EU aren’t just useful to public safety analysts, consumer rights advocates, security researchers and reviewers (who would benefit from this data living in the public domain) — it is also a potential gold-mine for car manufacturers who could sell it to insurers, market researchers and other deep-pocketed corporate interests who can profit by hiding that data from the public who generate it and who must share their cities and streets with high-speed killer robots.

Instagram is testing the ability to share your precise location history with Facebook

Revealed just weeks after Instagram’s co-founders left the company, Instagram is currently testing a feature that would allow it to share your location data with Facebook, even when you’re not using the app.

Instagram is not the only service that Facebook has sought to share data between. Back in 2016 the company announced that it would be sharing user data between WhatsApp and Facebook in order to offer better friend suggestions. The practice was later halted in the European Union thanks to its GDPR legislation, although WhatsApp’s CEO and co-founder later left over data privacy concerns.

Facebook is also reportedly testing a map view to see friend’s locations, similar to what’s already offered by Snapchat. Instagram’s data sharing could provide additional data points to power this functionality, while providing Facebook with more data to better target its ads.

Proposed Toronto development from Google’s Sidewalk Labs sparks concerns over data

Heated streets will melt ice and snow on contact. Sensors will monitor traffic and protect pedestrians. Driverless shuttles will carry people to their doors.

A unit of Google’s parent company Alphabet is proposing to turn a rundown part of Toronto’s waterfront into what may be the most wired community in history — to “fundamentally refine what urban life can be.”

Dan Doctoroff, the CEO of Sidewalk Labs, envisions features like pavement that lights up to warn pedestrians of approaching streetcars. Flexible heated enclosures — described as “raincoats” for buildings — will be deployed based on weather data during Toronto’s bitter winters. Robotic waste-sorting systems will detect when a garbage bin is full and remove it before raccoons descend.

“Those are great uses of data that can improve the quality of life of people,′ he said. “That’s what we want to do.”

But some Canadians are rethinking the privacy implications of giving one of the most data-hungry companies on the planet the means to wire up everything from street lights to pavement.

The concerns have intensified following a series of privacy scandals at Facebook and Google. A recent Associated Press investigation found that many Google services on iPhones and Android devices store location-tracking data even if you use privacy settings that are supposed to turn them off.

Adam Vaughan, the federal lawmaker whose district includes the development, said debate about big data and urban infrastructure is coming to cities across the world and he would rather have Toronto at the forefront of discussion.

“Google is ahead of governments globally and locally. That’s a cause for concern but it’s also an opportunity,” Vaughan said.

Facebook, Google, and Microsoft Use Design to Trick You Into Handing Over Your Data, New Report Warns

A study from the Norwegian Consumer Council dug into the underhanded tactics used by Microsoft, Facebook, and Google to collect user data. “The findings include privacy intrusive default settings, misleading wording, giving users an illusion of control, hiding away privacy-friendly choices, take-it-or-leave-it choices, and choice architectures where choosing the privacy friendly option requires more effort for the users,” states the report, which includes images and examples of confusing design choices and strangely worded statements involving the collection and use of personal data.

Google makes opting out of personalized ads more of a chore than it needs to be and uses multiple pages of text, unclear design language, and, as described by the report, “hidden defaults” to push users toward the company’s desired action. “If the user tried to turn the setting off, a popup window appeared explaining what happens if Ads Personalization is turned off, and asked users to reaffirm their choice,” the report explained. “There was no explanation about the possible benefits of turning off Ads Personalization, or negative sides of leaving it turned on.” Those who wish to completely avoid personalized ads must traverse multiple menus, making that “I agree” option seem like the lesser of two evils.

In Windows 10, if a user wants to opt out of “tailored experiences with diagnostic data,” they have to click a dimmed lightbulb, while the symbol for opting in is a brightly shining bulb, says the report.

Another example has to do with Facebook. The social media site makes the “Agree and continue” option much more appealing and less intimidating than the grey “Manage Data Settings” option. The report says the company-suggested option is the easiest to use. “This ‘easy road’ consisted of four clicks to get through the process, which entailed accepting personalized ads from third parties and the use of face recognition. In contrast, users who wanted to limit data collection and use had to go through 13 clicks.”

Facebook gave firms broad access to data on users, friends

Facebook reportedly formed data-sharing partnerships with dozens of device makers, including Apple and Samsung, giving them access to information on users, as well as on users’ friends.

The New York Times revealed the extent of the partnerships on Sunday, shedding new light on the social media giant’s behavior related to customer data following a scandal involving the political consulting firm Cambridge Analytica.

The Times found that the company made at least 60 such deals over the past decade, many of which are still in effect, allowing the other companies access to personal data of Facebook users and their friends.

The partnerships may have also violated a 2011 Federal Trade Commission (FTC) consent decree, according to the Times, which Facebook officials denied.

The report comes as Facebook is under scrutiny for its handling of private data after it was revealed that Cambridge Analytica accessed millions of users’ private information.

The partnerships allowed companies like Apple, Blackberry and Amazon to offer users Facebook features, like the ability to post photos, directly from a device without using the Facebook app.

The Times found that the partnerships allowed outside companies to access personal user data like relationship status, religious and political affiliations, work history and birthdays, as well as the information of users’ Facebook friends, even if the friends had blocked Facebook from sharing their information with third parties.

Facebook officials told the Times in interviews that the data-sharing partnerships were different from app developers’ access to Facebook users, and that the device makers are considered “extensions” of the social network.

But security experts and former Facebook engineers expressed concerns that the partnerships offered companies practically unfettered access to hundreds of thousands of Facebook users without their knowledge.

“It’s like having door locks installed, only to find out that the locksmith also gave keys to all of his friends so they can come in and rifle through your stuff without having to ask you for permission,” said Ashkan Soltani, a former FTC chief technologist, according to the Times.

Facebook began ending the partnerships in recent months, but the Times reported that many are still in effect.

How the “Math Men” Overthrew the “Mad Men”

Once, Mad Men ruled advertising. They’ve now been eclipsed by Math Men — the engineers and data scientists whose province is machines, algorithms, pureed data, and artificial intelligence. Yet Math Men are beleaguered, as Mark Zuckerberg demonstrated when he humbled himself before Congress, in April. Math Men’s adoration of data — coupled with their truculence and an arrogant conviction that their ‘science’ is nearly flawless — has aroused government anger, much as Microsoft did two decades ago.

The power of Math Men is awesome. Google and Facebook each has a market value exceeding the combined value of the six largest advertising and marketing holding companies. Together, they claim six out of every ten dollars spent on digital advertising, and nine out of ten new digital ad dollars. They have become more dominant in what is estimated to be an up to two-trillion-dollar annual global advertising and marketing business. Facebook alone generates more ad dollars than all of America’s newspapers, and Google has twice the ad revenues of Facebook.

Why the Facebook ‘scandal’ impacts you more than you think

It’s not just the data you choose to share.

By now we all know the story: Facebook allowed apps on its social media platform which enabled a shady outfit called Cambridge Analytica to scrape the profiles of 87 million users, in order to serve up targeted ads to benefit the Trump election campaign in 2016.  More than 300,000 Australian users of Facebook were caught up in the data harvesting.

But serving up ads in a foreign election campaign is not the whole story.  Facebook, and other companies involved in data mining, are invading our privacy and harming us economically and socially, in ways that are only just starting to become clear.

And it’s not just the data you choose to share. The information you post is not the whole story.  It’s only the tip of the iceberg of data that Facebook has collected about you.

Every time you go online you leave a trail of digital breadcrumbs.  Facebook has been busily sweeping up those breadcrumbs, and using them to categorise and profile you.  Facebook obviously knows when you click on a Facebook ‘like’ button; but also, unless a web developer has gone out of their way to find tools to block them (as we have done for our Salinger Privacy blog), Facebook knows every time you simply look at a website that has a Facebook ‘like’ button somewhere on it.

So if you only post or ‘like’ stories about inspirational mountain climbers and funny cat videos, but also do things online that you don’t share with your family, friends or work colleagues (like looking at stories about abortion or dealing with infidelity, Googling how to manage anxiety or erectile dysfunction, whingeing about your employer in a chatroom, or spending hours reviewing dating profiles, gambling or shopping obsessively for shoes)  — Facebook has you pegged anyway.

Plus, Facebook obtains data from other sources which know about your offline purchases, to build an even richer picture of who you really are.  And of course, Facebook may have access to your address book, your location history, the contents of your private messages, and depending on your brand of phone, possibly even a history of your phone calls and text messages.

All that information is used to draw inferences and assumptions about your preferences, and predict your likely behaviour.  The results are then used to categorise, profile and ultimately target you, in a process usually described as ‘online behavioural advertising’.

It’s not ‘just ads’

The objective of online behavioural advertising is to predict your purchasing interests and drive a purchase decision.  So far, the same as any other advertising.  But online, the implications for us as individuals are much greater.

Facebook’s promise to advertisers is that it can show their ad to exactly who the advertiser wants, and exclude everybody else.

However, by allowing exclusion, the platform also allows discrimination.  Facebook has been caught allowing advertisers to target — and exclude — people on the basis of their ‘ethnic affinity’, amongst other social, demographic, racial and religious characteristics.  So a landlord with an ad for rental housing could prevent people profiled as ‘single mothers’ from ever seeing their ad.  An employer could prevent people identifying as Jewish from seeing a job ad.  A bank could prevent people categorised as African Americans from seeing an ad for a home loan.

Existing patterns of social exclusion, economic inequality and discrimination are further entrenched by micro-targeted advertising, which is hidden from public view and regulatory scrutiny.

Data boy. Mark Zuckerberg testifies in Washington. Image: Getty.

Predictive analytics can narrow or alter your life choices

Once we move beyond straight-up advertising and into predictive analytics, the impact on individual autonomy becomes more acute.  Big Data feeds machine learning, which finds patterns in the data, from which new rules (algorithms) are designed.  Algorithms predict how a person will behave, and suggest how they should be treated.

Algorithms can lead to price discrimination, like surge pricing based on Uber knowing how much phone battery life you have left.  Or market exclusion, like Woolworths only offering car insurance to customers it has decided are low risk, based on an assessment of the groceries they buy.

Banks have been predicting the risk of a borrower defaulting on a loan for decades, but now algorithms are also used to determine who to hire, predict when a customer is pregnant, and deliver targeted search results to influence how you vote.

Algorithms are also being used to predict the students at risk of failure, the prisoners at risk of re-offending, and who is at risk of suicide and then launching interventions accordingly.  However, even leaving aside the accuracy of those predictions, interventions are not necessarily well-intentioned.  It was revealed last year that Australian Facebook executives were touting to advertisers their ability to target psychologically vulnerable teenagers. 

Automated decision-making diminishes our autonomy, by narrowing or altering our market and life choices, in ways that are not clear to us.  People already in a position of economic or social disadvantage face the additional challenge of trying to disprove or beat an invisible algorithm.

In a predictive and pre-emptive world, empathy, forgiveness, rehabilitation, redemption, individual dignity, autonomy and free will are programmed out of our society.

Fiddling with users’ privacy settings on Facebook won’t fix anything.  If we want our lives to be ruled by human values and individual dignity, instead of by machines fed on questionable data, we need robust, enforced and globally effective privacy laws.

A new European privacy law commences later this month.  The obligations include that businesses and governments must offer understandable explanations of how their algorithms work, and allow people to seek human review of automated decision-making.  This is a step in the right direction, which Australia, the US and the rest of the world should follow.

Google hasn’t stopped reading your e-mails

If you’re a Gmail user, your messages and emails likely aren’t as private as you’d think. Google reads each and every one (even if you definitely don’t), scanning your painfully long email chains and vacation responders in order to collect more data on you. Google uses the data gleaned from your messages in order to inform a whole host of other products and services, NBC News reported Thursday.

Though Google announced that it would stop using consumer Gmail content for ad personalization last July, the language permitting it to do so is still included in its current privacy policy, and it without a doubt still scans users emails for other purposes. Aaron Stein, a Google spokesperson, told NBC that Google also automatically extracts keyword data from users’ Gmail accounts, which is then fed into machine learning programs and other products within the Google family. Stein told NBC that Google also “may analyze [email] content to customize search results, better detect spam and malware,” a practice the company first announced back in 2012.

“We collect information about the services that you use and how you use them…” says Google’s privacy policy. “This includes information like your usage data and preferences, Gmail messages, G+ profile, photos, videos, browsing history, map searches, docs, or other Google-hosted content. Our automated systems analyze this information as it is sent and received and when it is stored.”

While Google doesn’t sell this information to third parties, has used it to power its own advertising network and inform search results, among other things. And this is far from a closely guarded secret. The company has included disclosures relating to these practices in its privacy policy since at least 2012: “When you share information with us, for example by creating a Google Account, we can make those services even better – to show you more relevant search results and ads…,” says Google’s March 2012 privacy policy.

Facebook silently enables facial recognition abilities for users outside EU and Canada

Facebook is now informing users around the world that it’s rolling out facial recognition features. In December, we reported the features would be coming to the platform; that roll out finally appears to have begun. It should be noted that users in the European Union and Canada will not be notified because laws restrict this type of activity in those areas.

With the new tools, you’ll be able to find photos that you’re in but haven’t been tagged in; they’ll help you protect yourself against strangers using your photo; and Facebook will be able to tell people with visual impairments who’s in their photos and videos. By default, Facebook warns that this feature is enabled but can be switched off at any time; additionally, the firm says it may add new capabilities at any time.

While Facebook may want its users to “feel confident” uploading pictures online, it will likely give many other users the heebie-jeebies when they think of the colossal database of faces that Facebook has and what it could do with all that data. Even non-users should be cautious which photos they include themselves in if they don’t want to be caught up in Facebook’s web of data.

How Do You Vote? 50 Million Google Images Give a Clue

What vehicle is most strongly associated with Republican voting districts? Extended-cab pickup trucks. For Democratic districts? Sedans.

Those conclusions may not be particularly surprising. After all, market researchers and political analysts have studied such things for decades.

But what is surprising is how researchers working on an ambitious project based at Stanford University reached those conclusions: by analyzing 50 million images and location data from Google Street View, the street-scene feature of the online giant’s mapping service.

For the first time, helped by recent advances in artificial intelligence, researchers are able to analyze large quantities of images, pulling out data that can be sorted and mined to predict things like income, political leanings and buying habits. In the Stanford study, computers collected details about cars in the millions of images it processed, including makes and models.

Identifying so many car images in such detail was a technical feat. But it was linking that new data set to public collections of socioeconomic and environmental information, and then tweaking the software to spot patterns and correlations, that makes the Stanford project part of what computer scientists see as the broader application of image data.

Google and Facebook are watching our every move online

You may know that hidden trackers lurk on most websites you visit, soaking up your personal information. What you may not realize, though, is 76 percent of websites now contain hidden Google trackers, and 24 percent have hidden Facebook trackers, according to the Princeton Web Transparency & Accountability Project. The next highest is Twitter with 12 percent. It is likely that Google or Facebook are watching you on many sites you visit, in addition to tracking you when using their products. As a result, these two companies have amassed huge data profiles on each person, which can include your interests, purchases, search, browsing and location history, and much more. They then make your sensitive data profile available for invasive targeted advertising that can follow you around the Internet.

So how do we move forward from here? Don’t be fooled by claims of self-regulation, as any useful long-term reforms of Google and Facebook’s data privacy practices fundamentally oppose their core business models: hyper-targeted advertising based on more and more intrusive personal surveillance. Change must come from the outside. Unfortunately, we’ve seen relatively little from Washington. Congress and federal agencies need to take a fresh look at what can be done to curb these data monopolies. They first need to demand more algorithmic and privacy policy transparency, so people can truly understand the extent of how their personal information is being collected, processed and used by these companies. Only then can informed consent be possible. They also need to legislate that people own their own data, enabling real opt-outs. Finally, they need to restrict how data can be combined including being more aggressive at blocking acquisitions that further consolidate data power, which will pave the way for more competition in digital advertising. Until we see such meaningful changes, consumers should vote with their feet.

How Facebook’s Political Unit Enables the Dark Art of Digital Propaganda

Under fire for Facebook Inc.’s role as a platform for political propaganda, co-founder Mark Zuckerberg has punched back, saying his mission is above partisanship. “We hope to give all people a voice and create a platform for all ideas,” Zuckerberg wrote in September after President Donald Trump accused Facebook of bias. Zuckerberg’s social network is a politically agnostic tool for its more than 2 billion users, he has said. But Facebook, it turns out, is no bystander in global politics. What he hasn’t said is that his company actively works with political parties and leaders including those who use the platform to stifle opposition — sometimes with the aid of “troll armies” that spread misinformation and extremist ideologies.

The initiative is run by a little-known Facebook global government and politics team that’s neutral in that it works with nearly anyone seeking or securing power. The unit is led from Washington by Katie Harbath, a former Republican digital strategist who worked on former New York Mayor Rudy Giuliani’s 2008 presidential campaign. Since Facebook hired Harbath three years later, her team has traveled the globe helping political clients use the company’s powerful digital tools. In some of the world’s biggest democracies — from India and Brazil to Germany and the U.K. — the unit’s employees have become de facto campaign workers. And once a candidate is elected, the company in some instances goes on to train government employees or provide technical assistance for live streams at official state events.

How Facebook Figures Out Everyone You’ve Ever Met

From Slashdot:

“I deleted Facebook after it recommended as People You May Know a man who was defense counsel on one of my cases. We had only communicated through my work email, which is not connected to my Facebook, which convinced me Facebook was scanning my work email,” an attorney told Gizmodo. Kashmir Hill, a reporter at the news outlet, who recently documented how Facebook figured out a connection between her and a family member she did not know existed, shares several more instances others have reported and explains how Facebook gathers information. She reports:

Behind the Facebook profile you’ve built for yourself is another one, a shadow profile, built from the inboxes and smartphones of other Facebook users. Contact information you’ve never given the network gets associated with your account, making it easier for Facebook to more completely map your social connections. Because shadow-profile connections happen inside Facebook’s algorithmic black box, people can’t see how deep the data-mining of their lives truly is, until an uncanny recommendation pops up. Facebook isn’t scanning the work email of the attorney above. But it likely has her work email address on file, even if she never gave it to Facebook herself. If anyone who has the lawyer’s address in their contacts has chosen to share it with Facebook, the company can link her to anyone else who has it, such as the defense counsel in one of her cases. Facebook will not confirm how it makes specific People You May Know connections, and a Facebook spokesperson suggested that there could be other plausible explanations for most of those examples — “mutual friendships,” or people being “in the same city/network.” The spokesperson did say that of the stories on the list, the lawyer was the likeliest case for a shadow-profile connection. Handing over address books is one of the first steps Facebook asks people to take when they initially sign up, so that they can “Find Friends.”

The problem with all this, Hill writes, is that Facebook doesn’t explicitly say the scale at which it would be using the contact information it gleans from a user’s address book. Furthermore, most people are not aware that Facebook is using contact information taken from their phones for these purposes.”

The Video Game That Could Shape the Future of War

“As far as video games go, Operation Overmatch is rather unremarkable. Players command military vehicles in eight-on-eight matches against the backdrop of rendered cityscapes — a common setup of games that sometimes have the added advantage of hundreds of millions of dollars in development budgets. Overmatch does have something unique, though: its mission. The game’s developers believe it will change how the U.S. Army fights wars. Overmatch’s players are nearly all soldiers in real life. As they develop tactics around futuristic weapons and use them in digital battle against peers, the game monitors their actions.

Each shot fired and decision made, in addition to messages the players write in private forums, is a bit of information soaked up with a frequency not found in actual combat, or even in high-powered simulations without a wide network of players. The data is logged, sorted, and then analyzed, using insights from sports and commercial video games. Overmatch’s team hopes this data will inform the Army’s decisions about which technologies to purchase and how to develop tactics using them, all with the aim of building a more forward-thinking, prepared force… While the game currently has about 1,000 players recruited by word of mouth and outreach from the Overmatch team, the developers eventually want to involve tens of thousands of soldiers. This milestone would allow for millions of hours of game play per year, according to project estimates, enough to generate rigorous data sets and test hypotheses.”

Brian Vogt, a lieutenant colonel in the Army Capabilities Integration Center who oversees Overmatch’s development, says:

“Right after World War I, we had technologies like aircraft carriers we knew were going to play an important role,” he said. “We just didn’t know how to use them. That’s where we are and what we’re trying to do for robots.”

Facebook has mapped populations in 23 countries as it explores satellites to expand internet

“Facebook doesn’t only know what its 2 billion users “Like.” It now knows where millions of humans live, everywhere on Earth, to within 15 feet. The company has created a data map of the human population by combining government census numbers with information it’s obtained from space satellites, according to Janna Lewis, Facebook’s head of strategic innovation partnerships and sourcing. A Facebook representative later told CNBC that this map currently covers 23 countries, up from 20 countries mentioned in this blog post from February 2016.

The mapping technology, which Facebook says it developed itself, can pinpoint any man-made structures in any country on Earth to a resolution of five meters. Facebook is using the data to understand the precise distribution of humans around the planet. That will help the company determine what types of internet service — based either on land, in the air or in space — it can use to reach consumers who now have no (or very low quality) internet connections.”

“Are you happy now? The uncertain future of emotion analytics”

Elise Thomas writes at Hopes & Fears:

“Right now, in a handful of computing labs scattered across the world, new software is being developed which has the potential to completely change our relationship with technology. Affective computing is about creating technology which recognizes and responds to your emotions. Using webcams, microphones or biometric sensors, the software uses a person’s physical reactions to analyze their emotional state, generating data which can then be used to monitor, mimic or manipulate that person’s emotions.”

Corporations spend billions each year trying to build “authentic” emotional connections to their target audiences. Marketing research is one of the most prolific research fields around, conducting thousands of studies on how to more effectively manipulate consumers’ decision-making. Advertisers are extremely interested in affective computing and particularly in a branch known as emotion analytics, which offers unprecedented real-time access to consumers’ emotional reactions and the ability to program alternative responses depending on how the content is being received.

For example, if two people watch an advertisement with a joke and only one person laughs, the software can be programmed to show more of the same kind of advertising to the person who laughs while trying different sorts of advertising on the person who did not laugh to see if it’s more effective. In essence, affective computing could enable advertisers to create individually-tailored advertising en masse.”

“Say 15 years from now a particular brand of weight loss supplements obtains a particular girl’s information and locks on. When she scrolls through her Facebook, she sees pictures of rail-thin celebrities, carefully calibrated to capture her attention. When she turns on the TV, it automatically starts on an episode of “The Biggest Loser,” tracking her facial expressions to find the optimal moment for a supplement commercial. When she sets her music on shuffle, it “randomly” plays through a selection of the songs which make her sad. This goes on for weeks.

Now let’s add another layer. This girl is 14, and struggling with depression. She’s being bullied in school. Having become the target of a deliberate and persistent campaign by her technology to undermine her body image and sense of self-worth, she’s at risk of making some drastic choices.”

Facebook built an AI system that learned to lie to get what it wants

“Facebook researchers used a game to help the bot learn how to haggle over books, hats, and basketballs. Each object had a point value, and they needed to be split between each bot negotiator via text. From the human conversations (gathered via Amazon Mechanical Turk), and testing its skills against itself, the AI system didn’t only learn how to state its demands, but negotiation tactics as well — specifically, lying. Instead of outright saying what it wanted, sometimes the AI would feign interest in a worthless object, only to later concede it for something that it really wanted. Facebook isn’t sure whether it learned from the human hagglers or whether it stumbled upon the trick accidentally, but either way when the tactic worked, it was rewarded.

It’s no surprise that Facebook is working on ways to improve how its bot can interact with others—the company is highly invested in building bots that can negotiate on behalf of users and businesses for its Messenger platform, where it envisions the future of customer service.