Summary of “Meet the US’s spy system of the future”

A product of the National Reconnaissance Office, Sentient is an omnivorous analysis tool, capable of devouring data of all sorts, making sense of the past and present, anticipating the future, and pointing satellites toward what it determines will be the most interesting parts of that future.
It’s not all dystopian: the documents released by the NRO also imply that Sentient can make satellites more efficient and productive.
Of the more than 150 US military satellites, the NRO operates around 50.
One of these, BlackSky, uses those satellites to feed into a system that’s essentially Sentient’s unclassified doppelgänger.
In the ideal version of that process, an automated system sucks in all sorts of data, synthesizes it into something sensible, cues the satellite symphony, reincorporates the satellites’ data back into the analysis loop, comes to a smarter conclusion, points the satellites or other sensors again, and repeats the entire process.
Here’s where Sentient reenters the picture: All the images from the NRO, the military, and these commercial satellite firms, combined with other geospatial intelligence – anything that has a time tag and a location tag – create a vast amount of information that’s far more than a literal army of people could comb through.
It could perhaps gather data on how often they fly and where, or even look at news to find out whether there’s any agitation or action around Aleysk: now the system knows exactly where they should point their real-time satellites to gather the information that their client needs.
Spy satellites, like the ones used by the NRO, are primarily meant to focus on the world beyond the United States’ borders.

The orginal article.

Summary of “The Selfish Dataome”

That burden challenges us to ask if we are manufacturing and protecting our dataome for our benefit alone, or, like the selfish gene, because the data makes us do this because that’s what ensures its propagation into the future.
Shakespeare, to be fair, contributed barely a drop to a vast ocean of data that is both ethereal yet actually extremely tangible in its effects upon us.
Data like these have outlived generation after generation of humans.
As time has gone by our production of data has accelerated.
In Perspective: The human genome fits on about two CDs. The human species produces about 20,000 CDs worth of data a second.
On the face of things, it seems pretty obvious that our capacity to carry so much data with us through time is a critical part of our success at spreading across the planet.
The proliferation of data of seemingly very low utility could actually be a sign of worrying dysfunction in our dataome.
Either through data credit schemes akin to domestic solar power feeding back to the grid, or making the loss of data a positive feature.

The orginal article.

Summary of “The First Thing Great Decision Makers Do”

As a statistician, I appreciate the quote by applied statistics pioneer W. Edwards Deming, “In God we trust. All others bring data.” But as a social scientist, I’m compelled to warn you that many decision-makers chase data with too much zeal, running from ignorance but never improving their decisions.
Is there a way to land in the sweet spot? There is, and it starts with one simple decision-making habit: Commit to your default decision up front.
The key to decision-making is framing the decision context before you seek data – a skill that unfortunately is not usually covered in data science courses.
Many decision-makers think they’re being data-driven when they look at a number, form an opinion, and execute their decision.
There were numbers near that decision somewhere, but those numbers didn’t drive the decision.
By leaving the decision criteria open, you’re free to interact with the data selectively to confirm the choice you’ve already made in your heart of hearts.
The first part of that process is determining what you’re planning to do in the absence of further data.
You ask yourself, “If I see no additional data beyond what I’ve already seen, what will I do?” Answering this takes strength of character  –  you can’t punt it to the data.

The orginal article.

Summary of “A new book says married women are miserable. Don’t believe it.”

Women should be wary of marriage – because while married women say they’re happy, they’re lying.
According to behavioral scientist Paul Dolan, promoting his recently released book Happy Every After, they’ll be much happier if they steer clear of marriage and children entirely.
Dolan had misinterpreted one of the categories in the survey, “Spouse absent,” which refers to married people whose partner is no longer living in their household, as meaning the spouse stepped out of the room.
An older article he cited earlier claims that unmarried women have 50% higher mortality rates than married women.
In May, author Naomi Wolf learned of a serious mistake in a live, on-air interview about her forthcoming book Outrages: Sex, Censorship and the Criminalization of Love.
Earlier this year, former New York Times editor Jill Abramson’s book Merchants of Truth was discovered to contain passages copied from other authors, and alleged to be full of simple factual errors as well.
Around the same time, I noticed that a statistic in the New York Times Magazine and in Clive Thompson’s upcoming book Coders was drawn from a study that doesn’t seem to really exist.
In response to the embarrassing retractions and failed replications associated with the replication crisis, more researchers are publishing their data and encouraging their colleagues to publish their data.

The orginal article.

Summary of “Why Technology Favors Tyranny”

At least for a few more decades, human intelligence is likely to far exceed computer intelligence in numerous fields.
Many of these new jobs will probably depend on cooperation rather than competition between humans and AI. Human-AI teams will likely prove superior not just to humans, but also to computers working on their own.
For several years after IBM’s computer Deep Blue defeated Garry Kasparov in 1997, human chess players still flourished; AI was used to train human prodigies, and teams composed of humans plus computers proved superior to computers playing alone.
Since AlphaZero had learned nothing from any human, many of its winning moves and strategies seemed unconventional to the human eye.
These potential advantages of connectivity and updatability are so huge that at least in some lines of work, it might make sense to replace all humans with computers, even if individually some humans still do a better job than the machines.
IV. The Transfer of Authority to Machines Even if some societies remain ostensibly democratic, the increasing efficiency of algorithms will still shift more and more authority from individual humans to networked machines.
If we invest too much in AI and too little in developing the human mind, the very sophisticated artificial intelligence of computers might serve only to empower the natural stupidity of humans, and to nurture our worst impulses, among them greed and hatred.
We are now creating tame humans who produce enormous amounts of data and function as efficient chips in a huge data-processing mechanism, but they hardly maximize their human potential.

The orginal article.

Summary of “I left the ad industry because our use of data tracking terrified me”

The rest of the ad industry, which depends on their data to compete, has no choice but to go along with whatever whims and changes come their way.
These companies have been extracting our personal data without permission and making fortunes with it.
First, people must have a real choice about what data they share.
If you don’t want to share personal data with a company, you shouldn’t have to.
Third, we must require technology companies to disclose device end points-in other words, to tell us what data they’re collecting, where it’s going, and how it’s getting there.
In 2018, Microsoft voluntarily disclosed its end points for Windows 10, giving users a granular understanding of what data Windows is collecting, where it’s going, and how it’s getting there.
That’s a great start, but more should follow Microsoft’s lead. Finally, there is some data that companies should never be allowed to collect, because of the significant risk of abuse.
To its credit, Apple has started to clamp down on apps requesting location data that they don’t need to provide functionality-this should be standard practice across platforms.

The orginal article.

Summary of “How to block ad tracking on your iPhone”

A recent article in The Washington Post by Geoffrey Fowler described the author’s shock when he discovered just how many of his iPhone apps were collecting and uploading information about his usage while he slept.
If you use a phone, laptop, or any type of computing device, you’re paying for your apps by contributing marketing and other info to the companies that supply them.
There are some simple ways to minimize the amount of tracking that app vendors can do and the amount of data they can access.
Turn off Background App Refresh According to Apple, the reason to have Background App Refresh turned on is to allow suspended apps to “Check for updates and new content.” According to Disconnect, the privacy app company that Geoffrey Fowler cites in his article, it also allows apps to collect marketable tracking data and transmit that data even when you’re not using the app.
Interestingly, iPhones ship with Background App Refresh turned on, but it’s not terribly hard to turn off.
Find “Background App Refresh” at the top of the page, and tap on it.
You may want to be selective about which apps can work in the background.
If you wish, leave “Background App Refresh” on, and then choose which specific apps you want to toggle off.

The orginal article.

Summary of “Did Cellphones Bring Down Crime Rates in the ’90s?”

“It is not inconceivable that their theory was a contributing factor, but 20-30 percent seems like a lot,” said Inimai Chettiar, the director of the Brennan Center’s Justice Program, which did a large-scale review of the crime decline several years ago.
The University of Leeds criminologist Graham Farrell, who is closely associated with the hypothesis that better security technology is the primary cause of the crime decline, also took issue with some of the paper’s data analysis.
“At first glance, it seems to be that antenna [density] increased mostly after homicide already declined,” he wrote to me in an email.
The data that the economists presented don’t match the chronology of the decline of homicides, especially considering that their proxy variable-how many antennas were up-would almost certainly precede cellphone usage by some period of time.
The data don’t hold up across time, across cities, or across countries.
While most of the researchers above have focused narrowly on the 1990s crime decline, Tcherni-Buzzeo has a different temporal perspective.
In her review paper, she showed a broader pattern of centuries of declining human violence.
“Maybe we should be trying to figure out what contributed to the temporary increase, because the decline seems to be the underlying trend,” she said.

The orginal article.

Summary of “Hollywood is quietly using AI to help decide which movies to make”

The company licenses historical data about movie performances over the years, then cross-references it with information about films’ themes and key talent, using machine learning to tease out hidden patterns in the data.
Cinelytic isn’t the only company hoping to apply AI to the business of film.
Last November, 20th Century Fox explained how it used AI to detect objects and scenes within a trailer and then predict which “Micro-segment” of an audience would find the film most appealing.
An academic paper published on this topic in 2016 similarly claimed that reliable predictions about a movie’s profitability can be made using basic information like a film’s themes and stars.
You don’t need a sophisticated and expensive AI software to tell you that a star like Leonardo DiCaprio or Tom Cruise will improve the chances of your film being a hit, for example.
Because AI learns from past data, it can’t predict future cultural shifts Zhao offers a more benign example of algorithmic shortsightedness: the 2016 action fantasy film Warcraft, which was based on the MMORPG World of Warcraft.
Scarso says that using AI to play around with a film’s blueprint – swapping out actors, upping the budget, and seeing how that affects a film’s performance – “Opens up a conversation about different approaches,” but it’s never the final arbiter.
Hollywood is unlikely to accept AI having the final say anytime soon Some in the business push back against the claim that Hollywood is embracing AI to vet potential films, at least when it comes to actually approving or rejecting a pitch.

The orginal article.

Summary of “Apple promises privacy, but iPhone apps share your data with trackers, ad companies and research firms”

On a recent Monday night, a dozen marketing companies, research firms and other personal data guzzlers got reports from my iPhone.
Your iPhone doesn’t only feed data trackers while you sleep.
According to privacy firm Disconnect, which helped test my iPhone, those unwanted trackers would have spewed out 1.5 gigabytes of data over the span of a month.
To him, any third party that collects and retains our data is suspect unless it also has pro-consumer privacy policies like limiting data retention time and anonymizing data.
Apple offers a privacy setting called “Limit Ad Tracking” which makes it a little bit harder for companies to track you across apps, by way of a unique identifier for every iPhone.
Apple turns more of a blind eye to what apps do with data we provide them or they generate about us – witness the sorts of tracking I found by looking under the covers for a few days.
“For the data and services that apps create on their own, our App Store Guidelines require developers to have clearly posted privacy policies and to ask users for permission to collect data before doing so. When we learn that apps have not followed our Guidelines in these areas, we either make apps change their practice or keep those apps from being on the store,” Apple says.
Very few apps I found using third-party trackers disclosed the names of those companies or how they protect my data.

The orginal article.