What 7 Creepy Patents Reveal About Facebook

Reading your relationships

One patent application discusses predicting whether you’re in a romantic relationship using information such as how many times you visit another user’s page, the number of people in your profile picture and the percentage of your friends of a different gender.

Classifying your personality

Another proposes using your posts and messages to infer personality traits. It describes judging your degree of extroversion, openness or emotional stability, then using those characteristics to select which news stories or ads to display.

Another proposes using your posts and messages to infer personality traits. It describes judging your degree of extroversion, openness or emotional stability, then using those characteristics to select which news stories or ads to display.

Predicting your future

This patent application describes using your posts and messages, in addition to your credit card transactions and location, to predict when a major life event, such as a birth, death or graduation, is likely to occur.

Identifying your camera

Another considers analyzing pictures to create a unique camera “signature” using faulty pixels or lens scratches. That signature could be used to figure out that you know someone who uploads pictures taken on your device, even if you weren’t previously connected. Or it might be used to guess the “affinity” between you and a friend based on how frequently you use the same camera.

Listening to your environment

This patent application explores using your phone microphone to identify the television shows you watched and whether ads were muted. It also proposes using the electrical interference pattern created by your television power cable to guess which show is playing.

This patent application explores using your phone microphone to identify the television shows you watched and whether ads were muted. It also proposes using the electrical interference pattern created by your television power cable to guess which show is playing.

Tracking your routine

Another patent application discusses tracking your weekly routine and sending notifications to other users of deviations from the routine. In addition, it describes using your phone’s location in the middle of the night to establish where you live.

Inferring your habits

This patent proposes correlating the location of your phone to locations of your friends’ phones to deduce whom you socialize with most often. It also proposes monitoring when your phone is stationary to track how many hours you sleep.

Trump’s top economist offers solution to unemployment: More government jobs

In the latest edition of the ‘POLITICO Money’ podcast, Council of Economic Advisers Chair Kevin Hassett discusses tax policy, drawing Americans back into the workforce and his ‘Dow 36,000’ prediction.

President Donald Trump’s top economist has an unusual idea for dealing with the problem of long-term unemployment: Just have the government hire people.

.. Kevin Hassett, the conservative chairman of the White House Council of Economic Advisers, believes some Americans are so disconnected from the workforce that the best idea to get them working again could be a federal jobs program that would ultimately lead to private-sector employment.

 .. To Hassett, long-term unemployment often leads to family breakdown and descent into addiction and other maladies. “People who have been unemployed for more than a year very often don’t ever reconnect to the labor force,” he said. “And very often they fall into sort of downward spirals of personal despair where they end up abusing substances and have a higher risk of divorce. Some of the literature in this area is just absolutely disturbing.”
.. Hassett remains convinced that the tax cut bill now emerging on Capitol Hill that would slice the top corporate rate from 35 percent to 20 percent will in fact add at least $4,000 in increased wages per household over the next several years
.. Hassett called the idea “iron-clad” based on studies of other countries cutting their corporate rate. And he said he believes the increase could be even greater.
.. He argues that a lower corporate rate and more immediate expensing of capital investments will lead to greater productivity among workers and thus higher wages without big inflationary pressure.
.. “If you have a supply-side stimulus precisely now, we can get capital deepening back to where it used to be, then you could add a percent to GDP growth,” he said. “And that will increase labor productivity and increase wages but not in a way that’s inflationary.”
.. Hassett, an affable economist with friends on both side of the partisan aisle, also spoke about his often-lampooned 1999 book with James Glassman, “Dow 36,000,” that predicted stocks would hit that mark by 2004. Instead, the dot-com bubble burst and stocks tanked.Hassett described the title of the book as a bit of a “youthful indiscretion” that was also somewhat unfairly maligned. “The point was that people who buy and hold stocks for the long run tend to do well, but that stocks go up and down a lot and it’s scary.”

‘Prediction professor’ who called Trump’s big win also made another forecast: Trump will be impeached

“I’m going to make another prediction,” he said. “This one is not based on a system; it’s just my gut. They don’t want Trump as president, because they can’t control him. He’s unpredictable. They’d love to have Pence — an absolutely down-the-line, conservative, controllable Republican. And I’m quite certain Trump will give someone grounds for impeachment, either by doing something that endangers national security or because it helps his pocketbook.”

Forecasting Tournaments: What We Discover When We Start Scoring Accuracy

If you were running a forecasting tournament over an extended period of time and you had, say, 500-plus questions and thousands of forecasters, and you have estimates of diversity and accuracy over long periods of time, you can work out algorithms that do a better job of distilling the wisdom of the crowd than, say, simple averaging. It sounds risky, but it’s an algorithm known as extremizing, and it works out pretty well.

.. imagine another situation: President Obama is sitting down with friends and they’re relaxing and watching a March Madness basketball game. He’s a fan of March Madness. There is going to be a game between Duke University and Ohio State, and the people around him make estimates on the probability of Duke winning. The estimates are exactly like the estimates we got on Osama; they start around 35 percent, they go up to 95 percent with the center of gravity around 75 percent.

Do you think when his buddies offered these odds estimates, President Obama would have said, “Sounds like 50-50 to me”? Or would he have said something like, “Sounds like three-to-one favoring Duke”?

.. It’s an interesting fact that in very high stakes national security debates and in many other types of high stakes policy debates as well, people don’t think it’s possible to make very granular probability estimates. Sometimes they seem to act as though “things are going to happen,” and there’s “maybe” and “things aren’t going to happen.” Sometimes they act as though there will be only three levels of uncertainly. Sometimes they might act as if there are five or seven.

.. It’s fair to say that the vast majority of college-educated people believe that probability theory is useful in estimating the likelihood of a fair coin landing heads five times in a row. They think probability theory is useful if you’re playing poker and you’re drawing cards from a well-defined sampling universe. These are classic domains for frequent disk statistics. The question we’re confronting here is, what are the limits on the usefulness of probability? To what extent is it useful to elicit probability judgment for seemingly unique historical events? On this page, I list a number of situations in which people find it vexing to make probability judgments. The first one is, is there intelligent life elsewhere in the Milky Way?

.. One of his particularly insightful columns was one he wrote in late 2002 before the 2003 invasion of Iraq. He posed the question, is Iraq the way it is because Saddam is the way he is, or is Saddam the way he is because Iraq is the way it is?

..  If you make the mistake of missing something, missing a threat, make sure you don’t miss another one. And if you make the mistake of having a false positive on a threat, make sure you don’t make another false positive right away. Show, at least, that you’re responsive to the political blame game calculus.

.. It’s even possible to take a policy like, say, the invasion of Iraq, which almost everybody has bailed on, but you could construct a counterfactual that says, “Well, you know what? If you think things are bad now, you have no idea how bad they would have been if Saddam had stayed in power.” There were people who defended the Vietnam War or the Iraq War on those grounds even after most opinion had bailed out. But counterfactuals are a very interesting and integral part.

.. These narrative accounts that we give are not only always wrong, they’re always misleading because they’re so comforting and persuasive. We want to tell stories, we like to hear stories, and once we’ve heard the story, we now understand the situation and we’re done. It’s pathological, our love of stories in this sense of trying to be accurate about things that might happen, or trying to understand the levels of what’s going to. In biology, we encounter this all the time. There are so many simplistic stories relating to evolution, and you look a little deeper and it just isn’t that simple ever.

.. If you look at the failure of the intelligence community in the case of WMD, it was a failure of storytelling, not so much a failure of evidence interpretation. Retrospectively, you could tell a story of Saddam deliberately pretending like he had weapons of mass destruction, there’s a story about his generals lying to him; none of those stories were told beforehand.

Had those stories been told beforehand, the evidence could have been interpreted differently. The same evidence could have been interpreted differently.

.. I think Gordon Moore’s law, which, if you read the original paper, was based on five data points, one of which was null and four were just over a two-year period. He wrote this curve, he extrapolated it for ten years, and then the industry said, “Ah, that’s what’s going to happen,” and everyone worked that straight line for the next thirty or forty years. It completely transformed their world. It was exactly an example of a prediction changing the outcome, because without that I don’t think that Intel and all the other chipmakers would have known what to aim for. That told them what to aim for.

.. Foxes know many things but a hedgehog knows one big thing. The hedgehogs come in many flavors in expert political judgment. There are free market hedgehogs, there are socialist hedgehogs, there are boomster hedgehogs, there are doomster hedgehogs. They come in a variety of ideological complexions. This particular hedgehog was an ethnonationalist hedgehog.

.. Or Paul Krugman recently being interviewed by Fareed Zakaria about the recommendation he made to the Greek population about they should vote no on the loan referendum. Zakaria was asking him whether he had made a mistake, and Krugman said, “Yes, I think I did make a mistake. I think I overestimated the competence of the Greek government,” meaning he didn’t think they would be so dumb as not to have a backup plan if the European leaders didn’t move

.. And of course, academia encourages specialization.