The mystery behind a group of electoral maps — Crooked Timber
The maps appearing all over FB on how the US would look if only <some demographic category> voted are usually those that people have made using the interactive features on 538.
4 days ago
Addicted to Your iPhone? You’re Not Alone - The Atlantic
Look up some of the things in the article. Like the book mentioned and the design course at Stanford. I'm surprised they didn't mention Natasha's book.

There is arguably an element of hypocrisy to the enlightened image that Silicon Valley projects, especially with its recent embrace of “mindfulness.” Companies like Google and Facebook, which have offered mindfulness training and meditation spaces for their employees, position themselves as corporate leaders in this movement. Yet this emphasis on mindfulness and consciousness, which has extended far beyond the tech world, puts the burden on users to train their focus, without acknowledging that the devices in their hands are engineered to chip away at their concentration. It’s like telling people to get healthy by exercising more, then offering the choice between a Big Mac and a Quarter Pounder when they sit down for a meal.
design  technology  siliconvalley 
4 days ago
Donald Trump doesn’t need to broaden his appeal. The rise of cable TV explains why.
Narrowcasting and broadcasting - two terms I could use in my Facebook post.
8 days ago
The left vs. a carbon tax
Environmental groups are realigning -- the failures of 2010 have led them to a different strategy of opposing pipelines and creating broader coalitions. So now it turns out that environmental groups actually oppose a carbon tax measure in Oregon.
generalinterest  politics  research 
9 days ago
Taking Trump voters’ concerns seriously means listening to what they’re actually saying
Dylan Matthews says that Trump's voters are really concerned about changing demographics of America and that's where the question of how best to think about them should start. I agree but also disagree -- economic measures are still the best way to assuage the concerns of Trump voters.
generalinterest  america  politics 
12 days ago
The secret network of political tweeters making debate memes go viral - The Washington Post
Both initiatives employ similar methods, though their messages differ. After signing up on either Trump or Clinton’s website with a Twitter handle and an email address, the typical volunteer receives periodic emails from the campaign, asking them to retweet specific posts. Both campaigns also coordinate more closely with a select group of highly-followed “digital influencers”: the Clinton campaign through a closed Slack channel, and the Trump campaign via conference call.
research  platformization  politics  marketing  socialmedia 
13 days ago
How the Chris Hayes book Twilight of the Elites explains Trump's appeal
Hayes’s book suggests there are a lot of people who think that the system is broken, and that they can be politically mobilized. Donald Trump’s appeal is based on the claim that he is an anti-system politician. Unlike other politicians, he is prepared to tell it like it is, and to stick it to elites. Unsurprisingly, many elites, including elites within the Republican Party, are aghast. Senior Republicans are quietly rooting for Trump to lose. Core members of the intellectual wing of the party have publicly expressed their shock and abhorrence.

But does this actually explain support for Donald Trump? After all, it’s hardly rare for politicians to claim that they are running against Washington. There is some reason to believe that it does have explanatory power.

Students take an SAT prep class in Newton, Massachusetts John Nordell/Christian Science Monitor/Getty
Amenities like test prep classes give elites an advantage.
Hayes argues that the angriest voters are not going to be the people at the bottom, but the people in the middle, who used to expect that they and their kids could do well through enterprise and don’t believe that anymore. Experts have disagreed over whether Trump supporters are richer or poorer than the average. Yet emerging evidence is beginning to portray a more nuanced portrait of Trump's supporters than those earlier takes.

Jonathan Rothwell, a senior economist at Gallup, has used survey data on nearly 113,000 Americans to ask what really drives Trump support. He finds that support for the mogul turned politician is concentrated in the middle-income categories; in contrast, those who are relatively rich and those who are relatively poor are less likely to support him. Furthermore, economic insecurity is a huge factor – those who worry about their economic future are much more likely to vote for Trump. Rothwell builds on work by Raj Chetty and Nathaniel Hendren at Harvard to find that people in living in areas with weak mobility for kids from middle-class families are more likely to vote for Trump.

These findings are only the start of what is likely to be a long debate. Nonetheless, they support Hayes’s argument. People seem to be more likely to support an anti-system candidate like Donald Trump when they have a middling income, when they feel economically insecure, and when they live in places where middle-class kids have worse prospects for getting ahead.
generalinterest  america  politics 
14 days ago
How One 19-Year-Old Illinois Man Is Distorting National Polling Averages - The New York Times
About half of the difference is attributable to the small demographic categories that lead the 19-year-old black Trump voter in Illinois to get huge weights. The other half of the difference is because of the past vote weight.

Of the two factors, it was probably inevitable that using “past vote” would create a problem. The potential biases of weighting by past vote are pretty well established.

But the costs of the U.S.C./LAT poll’s extensive weighting were not so inevitable.

Jill Darling, the survey director at the U.S.C. Center for Economic and Social Research, noted that they had decided not to “trim” the weights (that’s when a poll prevents one person from being weighted up by more than some amount, like five or 10) because the sample would otherwise underrepresent African-American and young voters.

This makes sense. Gallup got itself into trouble for this reason in 2012: It trimmed its weights, and nonwhite voters were underrepresented.

In general, the choice in “trimming” weights is between bias and variance in the results of the poll. If you trim the weights, your sample will be biased — it might not include enough of the voters who tend to be underrepresented. If you don’t trim the weights, a few heavily weighted respondents could have the power to sway the survey. The poll might be a little noisier, and the margin of error higher (note that the margin of error on the U.S.C./LAT poll for black voters surges every time the heavily weighted young black voter enters the survey).

But the U.S.C./LAT poll is a panel — which means it recontacts the same voters over and over — and so it wound up with the worst of both worlds.
politics  statistics  research 
14 days ago
Observations on film art : Slumdogged by the past
Various inspirations from slum dog millionaire
movies  india 
15 days ago
Benghazi Biopsy: A Comprehensive Guide to One of America’s Worst Political Outrages
Best thing I've read on Benghazi. Rings true because it is filled with righteous indignation.
politics  generalinterest  america 
16 days ago
Your Surgeon Is Probably a Republican, Your Psychiatrist Probably a Democrat - The New York Times
Clustering doctor specialties by political affiliation. No surprise, higher-earning specialties lean republican. Lots of other interesting stuff here, may be worth blogging about.
toblog  politics  america 
16 days ago
Computers still aren't close to replacing doctors for diagnosing disease - Vox
In the first such head-to-head study, researchers from Harvard Medical School and Brigham and Women’s Hospital in Boston decided to put humans and machines to the test, comparing the diagnostic accuracy of physicians with that of 23 different medical diagnostic software tools.

These tools, known as symptom checkers, can be found on apps or sites like WebMD; they allow users to type in their various symptoms and answer a series of questions, and then spit out a list of "probable" diagnoses generated by computer algorithms.
artificial_intelligence  machinelearning  algorithms  toblog 
16 days ago
How to get people to take hurricanes seriously, in one haunting sentence - Vox
Emergency managers have a series of practices to scare people into evacuating. The page links to a pdf with a list of these tactics. Useful reading!
research  generalinterest 
20 days ago
Is your doctor Republican or Democrat? The answer can impact your health.
Bit of an reductio ad absurdum here. Won't this mean that you have to know literally every single thing about your doctor?
23 days ago
What Were Blogs? | New Republic
To judge by Read’s account, both Gawker and blogging were victims of their own success, albeit in very different ways. Gawker got big enough to earn a frighteningly powerful enemy, a relentless and unforgiving man who deployed his vast resources and the legal system to crush the publication. Blogging got so popular that it caught the attention of the mainstream media, which bought up the best talent, and of Silicon Valley, which recast the writer’s medium from an intimate platform that was all about voice to a social network all about clicks and shares. Banks are lucky enough to be too big to fail; Gawker and blogging were too big to succeed.
platformization  journalism 
25 days ago
Taken - The New Yorker
Fascinating piece on civil forfeiture - the power of police to take away civil assets because they've been used for supposedly criminal things. The writer won a Macarthur genius grant recently.
25 days ago
algorithms in society – comments on a talk by jure leskovec | orgtheory.net
In the Q&A, I followed up and pointed out that race is highly correlated with charges. For example, in the Rehavi & Starr paper at the Yale Law Review, we know that a lot of the difference in time spent in jail is attributable to racial difference in charges. Using Federal arrest data, Blacks get charged with more serious crimes for the same actions. Statistically, this means that race is strongly correlated with the severity of the charge. In the Q&A, Jure said that adding race did not improve the model’s accuracy. But why would it if we know that race and charged are highly inter-correlated? That comment misses the point.

These two comments can be summarized as “society changes algorithms and algorithms change society.” Ideally, Jure (and myself!) would love to see better decisions. We want algorithms to improve society. At the same time, we have to understand that (a) algorithms depend on society for data so we have to understand how the data is created (i.e., charge and race are tied together) and (b) algorithms create incentives to come up with ways to influence the algorithm.
machinelearning  sociology  data_science  algorithms 
25 days ago
stratification in the sharing economy: how oreo truffles snuff out egalitarianism | orgtheory.net
Sharing economy - a paper about a food swapping network and how they use distinctions there about what constitutes food appropriate for swapping
sharing_economy  platformization 
25 days ago
Lower Ed, A Series: Part II | tressiemc
If an organization works — and extracting billions of dollars in federal student aid money suggests ITT worked for a long time — then who it most frequently and efficiently works best for is one way to understand the organization.

Sociologist Dorothy Smith called this “textually-mediated social organization” or institutional ethnography.

I did that by assembling a database of financial texts – or SEC, marketing and investor relations documents — as well as regulatory documents (consumer and state legal actions) as well as interviews and participant observation. ITT was one of my field sites.

Here’s some of what we know from that:

ITT actually had a more diverse student population that was more male and non-white than the typical for profit college.
Because of number 1, ITT should have been able to weather some of the poor reception to for-profit students that plagues other schools.
Number 2 was true and probably kept ITT afloat far longer than some would have predicted, myself included.
What ITT did poorly or well, depending on your perspective, was highly aggressive structured recruitment. This probably increased student conversions but in so doing over-enrolled among the under-motivated or differently motivated students.
ITT was one of those institutions that economist cite as pegging tuition to the maximum allowable amount a student could borrow from federal student aid. That means the risk of failure at ITT was very high.
The aggressive recruiting did not extend to aggressive retainment and debt management. Other for-profit colleges invested in employees to track student debt, manage their repayment and their completion to keep defaults down and student satisfaction up. ITT did not.
ITT extended early and often into higher levels of degrees — bachelors and graduate degrees. But these degrees may be more sensitive to prestige than applied associates or credential degrees. And ITT’s aggressive enrollment strategies undermined that prestige and misread labor market changes in local and regional markets.
Finally, the disastrous PEAKS loan deal that ITT bungled speaks to an institutional culture that was willing to routinely subvert the spirit and letter of regulation. That did not bode well for any part of the organizational machine.
Overall, ITT spent a lot of money recruiting at scale, not enough money on retaining or managing student debt, and mis-read or failed to read the labor market for different degree types.
moocs  higher_ed 
25 days ago
Facebook is going to block clickbait headlines. It should rewrite them instead. - Vox
More on the Facebook trending controversy. Facebook's contradictory effort to make journalism more social.
facebook  platformization 
25 days ago
How Many Stolen Lives? - Occupy the Social
Some good data on the organizations that reported police killings. Could be useful to think about how data is used. And about black lives matter.
data_science  law  lawenforcement  politics 
25 days ago
Mission Impossible: African-Americans & analytics
Read this and then also the responses at orgtheory collected by Brayden King. Might be an interesting exercise to give to students.
bigdata  analytics  machinelearning 
25 days ago
You Too Can Become a Machine Learning Rock Star! No PhD Necessary.
But Hammond saw a flaw in this thinking. Let’s say we found that master algorithm, he thought to himself as his 18-month-old son dozed in his arms. Who would implement it in the countless use cases that would arise? Currently, only adepts in machine learning are capable of wielding such tools. And there are far too many uses for the meager number of those people to address. We need a system, he concluded, that would lower the bar so that your garden-variety software developer could use those tools. This system wouldn’t require highly specialized computer scientists to train neural nets, but would allow programmers to teach systems how to produce the desired effect.
As Hammond refined his concept, he developed an analogy to the history of computer programming. Originally, computer jockeys had to painstakingly write code that directly addressed the raw hardware. Then coders adopted standard instruction sets, called assembly language, that sped the process up — but you still had to be a pretty hardcore programmer to master assembly language. The breakthrough came when engineers created the compiler—a translator that converted what were called easier-to-use “higher-level” languages (ranging from BASIC to LISP to current ones like Python and C) into assembly language. Only then could programming be broadened to allow relative novices to create powerful applications. Hammond argues that with tools like Google’s TensorFlow, AI is now in the assembly language era, which makes it easier for the scientists building neural nets, but still limits the field to those who really understand how those nets work. His idea was to provide the equivalent of a compiler, to really open things up.
He shared the idea with Keen Browne, a former Microsoft colleague who had recently sold his gaming startup to a Chinese internet company. The concept resonated with Browne, who had been frustrated trying to do deep learning using the popular tools available. “I’m a pretty smart guy,” he says. “I went to China and learned to speak the language. I programmed at Microsoft. But doing this was ridiculous.” He signed on to co-found Bonsai. (The name was chosen because those artfully stunted Japanese trees balance both the natural and the artificial. A bonus came when new internet domains let the fledgling company register the address bons.ai.)
Bonsai isn’t alone in addressing the scarcity of skilled AI scientists. Some of the bigger companies have figured that they will do training in-house to boost their everyday coders into masters of neural nets: Google has developed a host of internal programs, and Apple looks for traits in programmers that indicate they can pick up those skills without much difficulty. As mentioned before, Google also has publicly released TensorFlow, the software it uses to help its own scientists build neural networks. Other AI toolkits are also available in open source, and more will undoubtedly follow, some of them requiring less expertise than others.
machinelearning  artificial_intelligence 
25 days ago
HKS Research Administration Office
Paper that looks at the effectiveness of access provided by Gatech's new online masters program. File in the data folder.
25 days ago
An Online Education Breakthrough? A Master’s Degree for a Mere $7,000 - The New York Times
The combination of a prestigious department, traditional degree and drastically lower price was something new in American higher education. Joshua Goodman, an economist at Harvard, decided to study the program, along with Julia Melkers from Georgia Tech and Amanda Pallais from Harvard. They were interested in whether Georgia Tech was simply recruiting students who would have enrolled elsewhere — or if the program was creating something new.

Fortunately, a quirk in the program created a kind of natural experiment. In the first year, Mr. Isbell and his colleagues didn’t want to be overwhelmed by students while working out the inevitable kinks. So they ranked the applicants by their undergraduate grade point average and cut off admission at 3.26, yielding 500 students. Mr. Goodman and his colleagues compared the students just below the cutoff with those just above. Using a national database of college enrollment, they investigated where the rejected students enrolled instead.

Overwhelmingly, the answer was nowhere.

Barely 10 percent chose a different program. The vast majority simply didn’t pursue a master’s degree at all. The demographic profile of the online students shows why. The traditional on-campus students in the Georgia Tech master’s program tend be young and just out college, with an average age of 24. The average age of the online students was 35. A sizable number were 45, 50 and older. Ninety percent were currently employed.
moocs  udacity  public_discourse  higher_ed 
25 days ago
Send Us the Political Ads You See on Facebook - The New York Times
The NYTimes has an experiment out. They ask you to download and install a browser plugin that superimposes Facebook ads with a button - and if the ad is political, you can report it to them; they take screenshots and look at the position of the ad. This is a good way to understand ads. One thign I noticed immediately after installing it is that the extension picks up ads but it doesn't mark as ads things that I get from the entities I "liked". e.g. edX things that appear in my feed are not picked up as ads.
facebook  platformization  advertising  politics  journalism 
26 days ago
How an Upstart Company Might Profit From Free Courses - The Chronicle of Higher Education
Article lists funding models for Coursera proposed in its deal with Michigan -- among other things most important being charging learners per course, there's also university buying/licensing it from Coursera, selling it to community colleges, etc.

These are the revenue models that I took verbatim from another article: http://jime.open.ac.uk/articles/10.5334/2012-18/.
Certification (students pay for a badge or certificate)
Secure assessments (students pay to have their examinations invigilated (proctored))
Employee recruitment (companies pay for access to student performance records)
Applicant screening (employers/universities pay for access to records to screen applicants)
Human tutoring or assignment marking (for which students pay)
Selling the MOOC platform to enterprises to use in their own training courses
Sponsorships (3rd party sponsors of courses)
Tuition fees.
moocs  public_discourse  coursera 
4 weeks ago
A statement on online course content and accessibility | Berkeley News
UC Berkeley has long been committed to ensuring equal access to students, faculty and staff with disabilities. Despite the absence of clear regulatory guidance, we have attempted to maximize the accessibility of free, online content that we have made available to the public. Nevertheless, the Department of Justice has recently asserted that the University is in violation of the Americans with Disabilities Act because, in its view, not all of the free course and lecture content UC Berkeley makes available on certain online platforms is fully accessible to individuals with hearing, visual or manual disabilities.

The department’s findings do not implicate the accessibility of educational opportunities provided to our enrolled students.

In response, the university has moved swiftly to engage our campus experts to evaluate the best course of action. We look forward to continued dialog with the Department of Justice regarding the requirements of the ADA and options for compliance. Yet we do so with the realization that, due to our current financial constraints, we might not be able to continue to provide free public content under the conditions laid out by the Department of Justice to the extent we have in the past.
moocs  berkeley  public_discourse 
5 weeks ago
mooc - gsiemens on Diigo
This is where George Siemens collects articles about MOOCs
moocs  public_discourse 
5 weeks ago
How technology disrupted the truth | Katharine Viner | Media | The Guardian
Useful as a foil for research. It's true that the influence of prestige journalists as gatekeepers has waned, but it's good to historicize this and show that this particular prestige itself was a function of the post-war media landscape with its huge networks basically sharing all the market between them. Still - the loss of objectivity is worrying because we do want something that both produces good content and helps hold institutions accountable.
journalism  media  research  public_discourse 
5 weeks ago
History, Myths, and Opportunities: Welfare at 20 - Council on Contemporary Families
Nice piece by Stephanie Coontz on TANF. Cites several studies of poverty and the impact of the act.
5 weeks ago
Clippy and the History of the Future of Educational Chatbots
Basically she's saying bots are not *really* intelligent and people *really* prefer humans. But the tech industry doesn't listen. And oh, bots are really old and not a new thing at all.
5 weeks ago
No Driver? Bring It On. How Pittsburgh Became Uber’s Testing Ground - The New York Times
What a quote!

“It’s not our role to throw up regulations or limit companies like Uber,” said Bill Peduto, Pittsburgh’s mayor, who said that Uber planned to use about 100 modified Volvo sport utility vehicles for the passenger trials. The vehicles will also have a human monitor behind the wheel. “You can either put up red tape or roll out the red carpet. If you want to be a 21st-century laboratory for technology, you put out the carpet.”
uber  platformization 
6 weeks ago
Facebook Removes Iconic 'Napalm Girl' Photo From Its Site : All Tech Considered : NPR
Facebook did not reveal details of its internal decision-making process. NPR scraped LinkedIn for the resumes of a few hundred employees and contractors in the "community operations" teams, the self-described "safety specialists" in charge.

In Wake Of Shootings, Facebook Struggles To Define Hate Speech
The team members are scattered around the world — in California, Ireland, India. Many are recent college grads with questionable training on what would be considered, in legacy newsrooms, very tough decisions that only veteran editors can make.

And the volume of work is extraordinary. While Bickert would not say how many posts Facebook removes on average, her colleague Osofsky shared in his non-apology: "It's hard to screen millions of posts on a case-by-case basis every week."

Repeat: millions. That would make the unit an editorial sweatshop.
facebook  platformization 
6 weeks ago
How algorithms rule our working lives | Cathy O’Neil | Science | The Guardian
She frames it all as algorithms but the more appropriate frame here might be metrics and standardization.
algorithms  politics  platformization 
6 weeks ago
Computing the Social Value of Uber. (It's High.) - Bloomberg View
How much would be lost if Uber simply went away? That's actually happened in Austin, Texas, and the service has faced legal troubles in France, Spain, Germany and parts of India.

The Sharing Economy

How much is really at stake? A new paper by Peter Cohen, Robert Hahn, Jonathan Hall, Steven Levitt (of “Freakonomics” fame) and Robert Metcalfe comes up with a pretty good, dollars-and-cents measure of how much UberX, the main Uber service, is improving the lives of its users.

Based on their study, here are a few ways of framing the value of Uber ride services to Americans:

For a typical dollar spent by consumers on UberX, they receive $1.60 worth of gain. 
uber  platformization 
6 weeks ago
U.S. Open Quieted Those Calling for a Roof. Now It Faces a Louder Problem. - The New York Times
Putting a cover on top of Ashe Stadium was an architectural and engineering challenge because the stadium sits on marshy land. But after years of deflecting pressure to build a roof that would prevent the almost inevitable rain delays, the United States Tennis Association relented.

But the solution to one problem has made another one more acute.

With a capacity of 23,771, Ashe Stadium can hold nearly 9,000 more people than two other showcase courts with retractable roofs: Centre Court at Wimbledon and Rod Laver Arena at the Australian Open. And the concretelike hardcourts at the U.S. Open only magnify the problem.

At most stadium sporting events, loudness is welcome, or even encouraged. At basketball arenas, football stadiums and baseball parks, video boards frequently implore, “Let’s make some noise!” In tennis, cheering is acceptable after points, but fans are expected to be quiet in the moments leading up to the action and the time during play.
tennis  research 
7 weeks ago
problem xblock that uses adaptive hint - Google Groups
Hi all,

I'm fairly new to xblock. Not sure what is the right approach here.

I want to have a problem that insert HTML content based on student's submission. I need the HTML inserted in the same component as the problem instead of creating another HTML component. In other word, I want to change the content of the problem after student submit their answer.

Is it possible for me to create such xblock based on the adaptive hint problem? I want the problem be able to give students adaptive hint but also be able to change its content.

How can I altered the original adaptive hint problem to allow change of problem content?

Please help.

Thank you,

xblock  moocs  edx  openedx  forums 
7 weeks ago
Chase Sapphire Reserve: Deal-Seeking Obsessives Have a New Favorite Credit Card - Bloomberg
Credit card churners! Oh my! A research topic!

Indeed, as credit-card reward programs have grown more generous, online forums and bloggers have become fonts of ingenious ways to exploit them for free travel or cash. To accrue sign-up bonuses, for example, some credit-card churners end up cycling through dozens of credit cards.
Banks, hotels and airlines don't necessarily condone such strategies. But the online buzz among churners and other points-obsessed customers has become a roar that's also reached card offers' broader intended audience: affluent people who travel frequently.
On Reddit's increasingly popular "churning" forum—which has shot up from 42,000 to 53,000 subscribers in just the last four months—a megathread about the Chase Sapphire Reserve card has attracted 10,000 comments.
"I've never seen hype for a card like I saw with this," said Shawn Coomer, a travel blogger in Las Vegas who has been credit-card churning for more than five years.
The card is "magical," said Frank Leppar, a resident of Weirton, West Virginia, who already has his new card. "The sign-up bonus is amazing. It's one of the better, if not the best, card out right now."
What is drawing so many churners, travelers and others to the Sapphire Reserve card are its perks: Cardholders who spend $4,000 in the first three months get a sign-up bonus of 100,000 points, worth $1,500 in travel through Chase's website—and potentially more, some bloggers point out, when transferred to Chase travel partner sites. The card also gives three points for every $1 spent on dining and travel, and its definition of travel—which includes ride-share services like Uber and home-rental services like Airbnb—is broader than other cards'. It also offers a $300 annual credit to reimburse cardholders for travel expenses.

"Once people started finding out about this stuff, it started going crazy" online, Coomer said.
Though both he and his wife applied, he warned against getting too caught up in the enthusiasm online, saying the card might not be right for everyone. Its $450 annual fee raises the stakes for cardholders: That $1,500 in travel rewards isn't the same as $1,500 in cash, and you don't want to pay a hefty annual fee just for travel points you'll never be able to use.
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Credit-card companies use generous perks to lure customers who travel frequently and spend freely, but they're wary of churners aiming mainly for free trips and other goodies. The companies are increasingly cracking down on the most hardcore churners, who take out card after card for their sign-up bonuses. Chase's new card application explicitly warns them away: "You will not be approved for this card if you have opened 5 or more bank cards in the last 24 months."
7 weeks ago
Koller is leaving Coursera
A New Challenge

Dear Friends,

This week marks the fifth anniversary of the official start of the MOOC movement: on August 16, 2011, a group of us at Stanford University announced our intent to offer the first three MOOCs. In a matter of weeks, to our surprise, each of these courses had an enrollment of 100,000 learners or more - many more than the number of students any of us could teach in an entire career as a professor. And it wasn’t just the numbers: unlike our Stanford students, these online learners came from every age group, every country, and every walk of life.

It was clear that we had an amazing opportunity to help millions of people around the world get access to a great education. This was not an opportunity that we could walk away from. So I put my research on hold and set off, together with my colleague and co-founder Andrew Ng and a small but amazing team, to form Coursera.

The last five years have been a remarkable validation of this vision. Over 145 of the world’s best learning institutions now offer over 1300 courses on our platform, reaching over 20 million registered learners. As we recently showed, tens or even hundreds of thousands of learners have benefited from these courses by getting a better, higher-paying job, or by starting their own business.

With this important initiative well on its way to success, it is time for me to turn to another critical challenge - the development of machine learning and its application to improving human health. This field has been a passion of mine since 2001, when I first started working on it at Stanford. Machine learning is now in the midst of an important transformation, as a variety of high-throughput technologies developed over the past decade are providing unprecedented amounts of data that, when combined with the right analytic methods, can enable novel insights and the development of new therapies for human disease.

I feel compelled to contribute to this important effort, which leverages my background and experience both at Stanford and at Coursera. Therefore, starting next week, I will be joining Calico as their Chief Computing Officer. Calico, an Alphabet company, is focused on understanding the process of aging and on developing interventions that enable people to live longer, healthier lives. At Calico, I will work on the development of new computational methods for analyzing biological data sets, to help move to achieving these important scientific and societal goals.

As I turn the bulk of my attention to this new challenge, I can do so knowing that Coursera has matured into a robust company with amazing forward momentum. Over the last three years, we have put in place a strong leadership team that includes Rick Levin, Tom Willerer, Lila Ibrahim, Kurt Apen, David Liu, Amber Tennant, Julia Stiglitz, and, most recently, Leah Belsky, Nikhil Sinha, and Deanna Raineri. We have also hired a diverse, vibrant, and incredibly talented group of employees, and together, we’ve made great strides toward optimizing our product experience, strengthening our university and industry partnerships, and much more.
coursera  moocs 
8 weeks ago
SWAYAM, India's MOOC Platform, Launches In Beta — It's Off To A Rocky Start — Class Central
In our deep dive on SWAYAM, we mentioned that we were concerned about the technology side of the new platform. Unfortunately, some of our concerns have come true.

The design of the website looks somewhat dated — it doesn’t feel like it was created in 2016.

Furthermore, we weren’t able to create a new account on SWAYAM, because the CAPTCHA image was broken and so we couldn’t move on to step #2 of the registration process.
india  moocs  openedx 
8 weeks ago
I Spent 5 Years With Some of Trump's Biggest Fans. Here's What They Won't Tell You. | Mother Jones
Arlie Hotschild's new book on the tea party. Look also for the review of this book by Sean MccCann in the LA Review of Books. Both worth reading.

What the people I interviewed were drawn to was not necessarily the particulars of these theories. It was the deep story underlying them—an account of life as it feels to them. Some such account underlies all beliefs, right or left, I think. The deep story of the right goes like this:

You are patiently standing in the middle of a long line stretching toward the horizon, where the American Dream awaits. But as you wait, you see people cutting in line ahead of you. Many of these line-cutters are black—beneficiaries of affirmative action or welfare. Some are career-driven women pushing into jobs they never had before. Then you see immigrants, Mexicans, Somalis, the Syrian refugees yet to come. As you wait in this unmoving line, you're being asked to feel sorry for them all. You have a good heart. But who is deciding who you should feel compassion for? Then you see President Barack Hussein Obama waving the line-cutters forward. He's on their side. In fact, isn't he a line-cutter too? How did this fatherless black guy pay for Harvard? As you wait your turn, Obama is using the money in your pocket to help the line-cutters. He and his liberal backers have removed the shame from taking. The government has become an instrument for redistributing your money to the undeserving. It's not your government anymore; it's theirs.
politics  america  generalinterest 
8 weeks ago
The BBC test card: inside a cult YouTube obsession
Test cards - what networks used to show in the deadtime between midnight and dawn before the day of 24 hour television. Might be a fun project for students to do.
generalinterest  research 
8 weeks ago
What’s the Matter with Cancer Alley? Arlie Russell Hochschild’s Anatomy of Trumpism - Los Angeles Review of Books
"Why is that? In good part, Hochschild tells us, it is because the people she meets value loyalty and take pride in their ability to endure hard trials. They are, Hochschild says, “victims without a language of victimhood.” But, as she further explains, that remarkable stoicism cannot be separated from their harsh suspicion of the less fortunate. They are repelled by dependency and resentful of liberals who seek, as they believe, to compel them to sympathize with the undeserving poor. One woman, an industrious accountant who escaped poverty by working her way through college, makes this attitude especially clear. Knowing that what she says will sound shocking to her listener, this woman complains to Hochschild about “people who refuse to work.” “[W]e should let them starve,” she declares. “Let them be homeless.”
In short, the people Hochschild comes to know are reluctant to pity themselves, but they still more stubbornly refuse sympathy to the less fortunate. Hence their one, very strongly expressed, political desire. They do not want government to restrain corporate power, nor expect that it will be able to do so. (Indeed, unlike the media outlets they favor, Hochschild’s informants don’t seem to view the state as tyrannically powerful. They see it rather as feckless and manipulative. By contrast to corporate power, government sins not out of strength but weakness.) They seethe with resentment, however, at the thought that liberal politicians extend advantages to people less deserving than themselves, and they yearn to see those advantages stripped away.
This, Hochschild says, is the “deep story” shared by the people she meets. In the quest for the wealth and security promised by the American dream, they believe that some people have been permitted to cut the line in front of them. They take pride in the work that allowed them to rise as far as they have. But now, as they perceive their world slipping away, they resent the unfair assistance that they think liberal government gives to the less deserving — to people who, as one man complains in a particularly transparent moment, “lazed around days and partied at night.” They view those undeserving people not as economic competitors but rather as threats to a fragile sense of “cultural honor.” What matters most to the conservatives she meets, Hochschild suggests, is the embattled feeling of pride they take from the conviction that they themselves do not belong among the weak and needy. Indeed, Hochschild reports that nearly all of her subjects have benefitted in direct ways from “a major government service.” Many of them, she adds, are “ashamed and asked me to dissociate their identity from such an act.”
It is among the great strengths of Hochschild’s book to suggest, concisely yet forcefully, how indebted that sense of cultural honor remains to a long history of racial hierarchy. The people Hochschild depicts are reluctant even to discuss questions of racial justice. They are confident, as Mike Schaff suggests of himself, that, because they no longer casually use the word “nigger,” racism has become largely a thing of the past."
generalinterest  politics  america 
8 weeks ago
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