2745
A DSM for Achievement — Learning Machine Blog — Medium
Author visualizes a DSM-like system for cataloging abilities - and decoupling credentials from institutions so that employers know what skills they have. Article is based on lecture by Arthur Levine who founded the MIT organization that Justin works for. Interesting insight into what's driving MOOCs - the social imaginations.
moocs  higher_ed  public_discourse 
1 hour ago
Who's Responsible For the Euromess? | Mother Jones
Great piece from Drum on how core EU countries share blame for what happened to Greece and Spain and Portugal during the Great Recession
generalinterest  politics  europe 
yesterday
Society in the Loop Artificial Intelligence — Medium
Silicon Valley ideology of empowerment in action.

"Human-in-the-loop machine learning is work that is trying to create systems to either allow domain experts to do the training or at least be involved in the training by creating machines that learn through interactions with experts. At the heart of human-in-the-loop computation is the idea of building models not just from data, but also from the human perspective of the data. Karthik calls this process ‘lensing’, of extracting the human perspective or lens of a domain expert and fit it to algorithms that learn from both the data and the extracted lens, all during training time. We believe this has implications for making tools for probabilistic programming and for the democratization of machine learning.
At a recent meeting with philosophers, clergy and AI and technology experts, we discussed the possibility of machines taking over the job of judges. We have evidence that machines can make very accurate assessments of things that involve data and it’s quite reasonable to assume that decisions that judges make such as bail amounts or parole could be done much more accurately by machines than by humans. In addition, there is research that shows expert humans are not very good set setting bail or granting parole appropriately. Whether you get a hearing by the parole board before or after their lunch has a significant effect on the outcome, for instance.
In the discussion, some of us proposed the idea of replacing judges for certain kinds of decisions, bail and parole as examples, with machines. The philosopher and several clergy explained that while it might feel right from a utilitarian perspective, that for society, it was important that the judges were human — it was even more important than getting the “correct” answer. Putting aside the argument about whether we should be solving for utility or not, having the buy-in of the public would be important for the acceptance of any machine learning system and it would be essential to address this perspective.
There are two ways that we could address this concern. One way would be to put a “human in the loop” and use machines to assist or extend the capacity of the human judges. It is possible that this would work. On the other hand, experiences in several other fields such as medicine or flying airplanes have shown evidence that humans may overrule machines with the wrong decision enough that it would make sense to prevent humans from overruling machines in some cases. It’s also possible that a human would become complacent or conditioned to trust the results and just let the machine run the system.
The second way would be for the machine to be trained by the public — society in the loop — in a way that the people felt that that the machine reliability represented fairly their, mostly likely, diverse set of values. This isn’t unprecedented — in many ways, the ideal government would be one where the people felt sufficiently informed and engaged that they would allow the government to exercise power and believe that it represented them and that they were also ultimately responsible for the actions of the government. Maybe there is way to design a machine that could garner the support and the proxy of the public by being able to be trained by the public and being transparent enough that the public could trust it. Governments deal with competing and conflicting interests as will machines. There are obvious complex obstacles including the fact that unlike traditional software, where the code is like a series of rules, a machine learning model is more like a brain — it’s impossible to look at the bits and understand exactly what it does or would do. There would need to be a way for the public to test and audit the values and behavior of the machines."
machinelearning  moocs  platformization  siliconvalley 
3 days ago
A DSM for Achievement — Learning Machine Blog — Medium
Rather than degrees, certify competencies; take DSM as guide. See also Chris Petersen's response...
moocs  public_discourse  higher_ed 
3 days ago
On Story and Execution: Sebastian Thrun, Udacity, and The Future — Udacity Inc — Medium
Written by a udacity employee and has some choice quotes from Thrun

“We’re now at this place where we can make the evolution of academic content match the evolution of the world.”
udacity  moocs  public_discourse 
3 days ago
The Reductive Seduction of Other People’s Problems — The Development Set — Medium
et’s pretend, for a moment, that you are a 22-year-old college student in Kampala, Uganda. You’re sitting in class and discreetly scrolling through Facebook on your phone. You see that there has been another mass shooting in America, this time in a place called San Bernardino. You’ve never heard of it. You’ve never been to America. But you’ve certainly heard a lot about gun violence in the U.S. It seems like a new mass shooting happens every week.
You wonder if you could go there and get stricter gun legislation passed. You’d be a hero to the American people, a problem-solver, a lifesaver. How hard could it be? Maybe there’s a fellowship for high-minded people like you to go to America after college and train as social entrepreneurs. You could start the nonprofit organization that ends mass shootings, maybe even win a humanitarian award by the time you are 30.
research  technology  technologyvspolitics 
3 days ago
The worst thing I read this year, and what it taught me… or Can we design sociotechnical systems… — Medium
Am I advocating codesign of prisons with the currently incarcerated? Hell yeah, I am. And with ex-offenders, corrections officers, families of prisoners as well as the experts who design these facilities today. They’re likely to do a better job than smart Yale students, or technology commentators.
design  research  technology 
3 days ago
Giving Young People an Alternative to College - The New York Times
"As I traveled the country the last two years talking to employers of all sizes and in all sectors of the economy for my new book, “There Is Life After College,” what I heard most is the worry they have about filling so-called middle-skill positions in advanced manufacturing, health care and information technology.

Nearly half of the American work force has these jobs today, but many of them are baby boomers who will soon be retiring. It’s expected that as many as 25 million of all new job openings in the next decade will be for middle-skills jobs.

What we need are job-training institutions on par with academic institutions as prestigious and rigorous as the Ivy League to attract students interested in pursuing skilled jobs critical for the economy that don’t necessarily require a four-year college degree.

The modern version of what an apprenticeship could look like for American students interested in alternatives to college is on display at The Apprentice School in Newport News, Va., where students choose from one of more than 20 occupational areas and are guaranteed a job with the military contractor that operates Newport News Shipbuilding."
higher_ed  public_discourse 
4 days ago
Bad Articles about Grad Student Unionization — Crooked Timber
Lots of arguments about faculty tenure, the no. of PHDs, and grad student unionization
moocs  higher_ed 
6 days ago
Sad! - The Huffington Post
Fascinating - if a bit self-serving. The most interesting part was the number of times I read the word "analytics" "measured" and others. Political consulting in the US today is clearly very data and analytics driven.
research  politics  platformization 
12 days ago
Teaching the teachers | The Economist
Those who do so embody six aspects of great teaching, as identified by Mr Coe. The first and second concern their motives and how they get on with their peers. The third and fourth involve using time well, fostering good behaviour and high expectations. Most important, though, are the fifth and sixth aspects, high-quality instruction and so-called “pedagogical content knowledge”—a blend of subject knowledge and teaching craft. Its essence is defined by Charles Chew, one of Singapore’s “principal master teachers”, an elite group that guides the island’s schools: “I don’t teach physics; I teach my pupils how to learn physics.”

Branches of the learning tree
Teachers like Mr Chew ask probing questions of all students. They assign short writing tasks that get children thinking and allow teachers to check for progress. Their classes are planned—with a clear sense of the goal and how to reach it—and teacher-led but interactive. They anticipate errors, such as the tendency to mix up remainders and decimals. They space out and vary ways in which children practise things, cognitive science having shown that this aids long-term retention.
moocs  public_discourse 
12 days ago
Same Time, Many Locations: Online Education Goes Back to Its Origins - The Chronicle of Higher Education
online education is going back to synchronous rather than asynchronous; let's see how that goes...
moocs  public_discourse 
12 days ago
Not-yetness and learnification | the red pincushion
Amy Collier talks about learnification - which is about the removal of teacher from the loop of teaching and learning.

She proposes a concept of "notyetness" to deal with learnification.

"We have to rethink our approaches to and views of education. I love this quote from George Siemens because it reiterates the point that we should make space for things that don’t fit into our tidy conceptions about education. Biesta would also argue that we should be looking into, inquiring into, the purpose of education and the relationships of educators and students, which have seemed to have been diminished in the intense focus on learning. When we embrace not-yetness, we should not just look at it in terms of process, but also not-yetness in the purposes of education. For example, we could probably name several purposes of education (jobs, citizenship, socialization) and sometimes those purposes could be at odds with each other. Not-yetness invites us to savor those tensions as fertile opportunities for better understanding education as a whole. Same with relationships with students. Biesta says that the focus on learning has decontextualized education from the teacher/student relationship. Not-yetness invites us to place more value on teacher/student relationships by embracing the messiness and under-determinedness of those relationships."
moocs  platformization  learning_research  stanford 
17 days ago
Understanding the Origins of Ed-Tech Snake Oil - The Chronicle of Higher Education
The problems with a certain kind of learning analytics research conducted by companies as reported by Feldstein and Hill.

"As you might have guessed, these statements are not hypothetical but historical facts. The product in question is called Course Signals, and the designers were staff members working for Purdue University at the time of the controversy. The author of the candy retention simulation is Alfred Essa, who now works at McGraw-Hill Education but whom I met when he was CIO at MIT’s Sloan School of Business. The root of the problem is not raw greed but a failure of the scientific peer-review process, amplified by the echo chamber of conventional and social media.

I can’t even say that amplification was caused by "marketing," at least in the conventional sense. The university was spreading the word among its peers about the findings of its institutional research. An earlier study of Course Signals conducted by the same research group, which showed that Course Signals helps students succeed within individual courses, was well received by the academic research community and has not been questioned. The researchers, one of whom I know fairly well, have good reputations. They probably just made a mistake in the experimental design of their second study. It happens. As now-former staff members, they are not at liberty to comment about institutional research. I honestly don’t know why Purdue itself failed to respond to its critics."
moocs  learning_analytics 
17 days ago
What is a Learning Platform? -e-Literate
irst, let’s look at the metaphor. A platform is typically defined in the generic sense as a raised surface of some type that supports other interacting objects. Within computer and software terminology, a platform can be defined as “A platform is any base of technologies on which other technologies or processes are built”. The idea is that the platform is not intended to stand on its own, as its definition includes the support of other technologies or applications.

Given this context, there is a rather extensive Wikipedia entry on learning platforms with some useful definitions included. I have excerpted several below.

A learning platform is an integrated set of interactive online services that provide teachers, learners, parents and others involved in education with information, tools and resources to support and enhance educational delivery and management.
platformization  moocs 
18 days ago
Chart of the Day: For-Profit Vocational Schools Are An Unholy Rip-Off
New study on earnings of for-profit graduates and dropouts. Answer: not good.
moocs  higher_ed 
26 days ago
What Presidents Talk About When They Talk About Hiroshima - The New Yorker
These critiques can seem shocking today, because they upset our understanding of how Hiroshima and Nagasaki map onto modern politics. We assume that Republicans, especially those in the military, are retrospectively pro-bomb, and that liberals see the attacks as something between a mistake and a war crime. But this interpretation removes the critiques from their historical context. Many commanders in both the European and Pacific theatres resented that the bomb got credit for ending the war. They saw their own strategic efforts, including the ruinous firebombing of at least sixty-seven Japanese cities, led by General Curtis LeMay, as being overshadowed by a scientific “gadget.” They feared that nuclear weapons would become an excuse to cut funding for conventional armed forces: if the bomb maintained the peace, who needed generals? (Their fears proved not entirely unfounded—Truman’s second Secretary of Defense, Louis A. Johnson, did try to slash military budgets—but they eventually learned to love the bomb.) When these leaders proposed that the attacks on Hiroshima and Nagasaki were unnecessary, they meant that they were unnecessary because Japan had already been bombed to dust. It was not a peacenik argument.
research  nuclear 
4 weeks ago
Robocalls have triumphed over the Do Not Call list. Whose fault is it?
The same voice over internet protocol technology that eliminated the long-distance telephone surcharge also revolutionized telemarketing. Companies could set up shop outside the United States—and outside the reach of regulatory authorities—where for pennies they could blast consumers with prerecorded, autodialed calls. They could also use spoofing technology to disguise where their calls were coming from. A call claiming to be from Microsoft, for instance, might show a 425 area code. That’s Redmond, Washington, where Microsoft is headquartered. And the IRS scam? A 202 number for Washington, D.C., would show up on caller ID.
research  regulation 
4 weeks ago
Tinder Has an In-House Sociologist and Her Job Is to Figure Out What You Want - Los Angeles Magazine
Puff piece - all it does is show that Tinder employs a "sociologist"-researcher but could be useful with names, etc.
tinder  platformization  dating 
4 weeks ago
Donald Trump's horrifying gullibility, as revealed in his energy speech - Vox
This is a wonderful observation:

"The second is that Trump was encountering his own speech, if not for the first time, then something close to it. The difference in tone and affect between the parts he read and the parts he freestyled was almost comical. He would squint at the teleprompter for a moment, read a fully formed English sentence with correct grammar and multisyllabic words ... and then grin, look out at the audience, and fire off a few hortatory exclamations.

What made this effect particularly disconcerting is that many of Trump's spontaneous interjections were reactions to his own speech.

[squint] "American energy dominance will be declared a strategic, economic, and foreign policy goal of the United States." [grin] "About time!"

It happened again and again. He'd read some statistic about the Environmental Protection Agency and then interject, "Wow, can you believe that?"

It was as though he was discovering Donald Trump's energy policies alongside his audience, and he liked what he saw. Oh, look here, Donald Trump is going to cancel the Paris climate accord, that's great!

It was amusingly Trumpian — Donald Trump often expresses admiration for things Donald Trump does or owns — but it was also revealing of some of his less commented-upon but more unsettling qualities."
generalinterest  politics  america 
4 weeks ago
California’s Upward-Mobility Machine - The New York Times
David Leonhardt on the colleges with the most economic diversity and how it is achieved. California leads, esp. by recruiting students from community colleges through their transfer program.
moocs  public_discourse  higher_ed 
4 weeks ago
Stanford teams up with edX
Mitchell compared the Stanford/edX effort to the evolution of Webkit, an Internet browser software package developed by Apple to compete with Microsoft’s Internet Explorer. Apple used Webkit to create the Safari browser – which comes installed on every Mac, iPad and iPhone – but kept the underlying Webkit software open source. Google eventually used Webkit to create its own browser, Chrome.
So that leaves the question, if edX is Apple and Stanford is Google, who is their Microsoft?
Asked that question during a conference call, Agarwal laughed. Mitchell immediately praised the "great arrangement" Stanford has with Coursera.
He also said Stanford, which has a unique startup-based culture, has no aversion to for-profit companies. But, he said, Stanford does want to leave its options open.
“There are certainly some choices if we have access to the code and the ability to modify it if we like, and also the ability to brand our site as we like, to partner with other organizations as we like,” he said.  
Mitchell said Stanford faculty members will continue to post material on Apple’s iTunes U, on Google’s YouTube and on Coursera, and to also generally allow faculty to pick among different platforms.
“We will work on a case-by-case basis with individual faculty,” Mitchell said.
And, even though it is nonprofit, edX will also eventually need to make money. MIT and Harvard both chipped in $30 million apiece to get edX off the ground.
moocs  public_discourse  stanford  edx  openedx  opensource 
4 weeks ago
American kids are getting too smart for the Spelling Bee
Comparing the spelling bees to the IIT JEE - I wouldn't be surprised if some of these Indian kids didn't have IITian parents.
toblog 
4 weeks ago
How well online dating works, according to someone who has been studying it for years - The Washington Post
One of the most interesting questions about the Internet as a sort of social intermediary is whether it brings different kinds of people together more than would have been brought together before. If you think about the traditional technology of family, which was the marriage broker of the past, the family was very selective in terms of its reliance on introducing you to people of the same race, religion and class as potential partners. What’s more, if you were marrying young — at the age of 20 or younger — you really could only marry people from within your close network, from your neighborhood. These were the only people you knew, and they were probably very much like you.

The question about Internet dating specifically is whether it undermines the tendency we have to marry people from similar backgrounds. The data suggests that online dating has almost as much a pattern of same-race preference as offline dating, which is a little surprising because the offline world has constraints of racial segregation that the online world was supposed to not have. But it turns out online dating sites show that there’s a strong preference for same-race dating. There’s pretty much the same pattern of people partnering with folks of the same race.

What’s unclear is how much of this tendency online is really a result of preference and how much is due to the websites feeding you potential partners that are of the same race as you. These websites use algorithms to try to figure out who you like. And if they assume you’re going to prefer people of your own race, they might feed you a steady diet of potential matches of the same race. Since the algorithms tend to be proprietary — they don’t share them — we don’t know whether this is skewing the data.

There are other aspects in which online dating leads to different results than offline dating. One is that people are more likely to date someone of another religion. I think that’s because you can’t tell what someone’s religion is from their picture. On online dating, the picture marks you with gender and race pretty clearly, but religion is something that you have to dig through to figure out.

The other big difference is that same-sex couples are much more likely to meet their partner online. In my data, about 22 percent of straight couples met online. For gay couples, it’s about 67 percent. Online is tremendously more efficient for gays and lesbians. And that’s because it’s much harder for them to identify potential partners offline.
dating  platformization 
4 weeks ago
Karl Polanyi for President | Dissent Magazine
Nicely written - although the comparison of Sanders and Clinton at the end that shows that they differ on their ideology just strikes me as a little forced. Just saying that Sanders thinks health-care is a right while Clinton thinks affordable health care is a right is perhaps putting too much emphasis on words. Even if you think healthcare is a right, someone's going to pay for it, and that is going to have distributional consequences. And it's the distributional consequences that one should focus on, rather than the words themselves. No?
capitalism  economics  polanyi  generalinterest  toblog 
4 weeks ago
In Service Sector, No Rest for the Working - The New York Times
About how computerized scheduling is reducing gaps between shifts and making it harder for service sector employees to manage their lives
labor  computing 
4 weeks ago
Distance Ed’s Second Act - The Chronicle of Higher Education
ow that the MOOC hype has died down and almost no one is arguing that those free online courses will upend the traditional university, are we instead entering a period where online education is having a real impact on the core of higher education? Not just for the for-profit outliers and not just for distance-education titans like Rio Salado College and Liberty University, but for the mainstream? While I would not argue that fundamental change has already occurred, there are some signs of a turning point.

About This Series

This commentary is part of a series by the authors of the ed-tech blog e-Literate, Michael Feldstein and Phil Hill.

The Babson Survey Research Group, which has tracked online college enrollment for the past 12 years, reports growth from 9 percent of U.S. students taking at least one course online in the fall of 2002 to more than 28 percent in the fall of 2014. The overall growth has slowed recently, but the drastic decrease in for-profit enrollment masks two very interesting numbers:

Sixty-seven percent of students taking online courses do so at public institutions.
The number of students at public and private nonprofit colleges who took at least one online course rose by 26 percent in just two years (2012-2014).
moocs  public_discourse 
4 weeks ago
The thriving Russian black market in dissertations—and the crusaders fighting to expose the country’s fake Ph.D.s.
Fascinating. There's a market for PhDs in Russia which means many plagiarized dissertations. And this group is trying to find them by creating automatic plagiarism detectors.
toblog  research 
4 weeks ago
Fraudulent claims made by IBM about Watson and AI | Roger Schank
Roger Shank goes ballistic about IBM Watson...

Of course, what upsets me most is not Watson but what IBM actually says. From the quote above:

Unlike traditionally programmed computers, cognitive systems such as Watson understand, reason and learn.

Ann Rubin, IBM's vp of branded content and global creative, told Adweek that the commercials were needed to help people understand the new world of cognitive computing.
I wrote a book called The Cognitive Computer in 1984:

I started a company called Cognitive Systems in 1981. The things I was talking about then clearly have not been read by IBM (although they seem to like the words I used.) Watson is not reasoning. You can only reason if you have goals, plans, and ways of attaining them, and a comprehension of the beliefs that others may have and a knowledge of past experiences to reason from. A point f view helps too. What is Watson’s view on ISIS for example?

Dumb question? Actual thinking entities have a point of view about ISIS. Dog’s don’s but Watson isn't as smart as a dog either. (The dog knows how to get my attention for example.)

I invented a field called Case Based Reasoning in the 80’s which was meant to enable computers to compare new situations to old ones and then modify what the computer knew as a result. We were able to build some useful systems. And we learned a lot about human learning. Did I think we had created computers that were now going to outthink people or soon become conscious? Of course not. I thought we had begun to create computers that would be more useful to people.

It would be nice if IBM would tone down the hype and let people know what Watson can actually do can and stop making up nonsense about love fading and out thinking cancer. IBM is simply lying now and they need to stop.
artificial_intelligence  machinelearning 
4 weeks ago
How Factory Farms Play Chicken With Antibiotics | Mother Jones
Turns out I'm not the only one asking. Dr. Bob Lawrence, the director of the Center for a Livable Future at Johns Hopkins, which has generated reams of research on the dangers of routine anti­biotic use on farms, ran into ceo Jim Perdue at a conference recently. Lawrence asked Perdue what had driven the company's flight from antibiotics. "I was hoping he would say, 'The research coming out of your center,'" Lawrence says. Instead, Perdue credited worried consumers.
research 
5 weeks ago
How presidential campaigns are building the perfect website | Fusion
Campaigns using Optimizely to A/B test. I don't know how Fusion got access to it though unless they were reverse engineering it.
abtesting  platformization  politics 
5 weeks ago
Demon Core: The Strange Death of Louis Slotin - The New Yorker
Slotin was one of only two people to die from radiation exposure at Los Alamos while the laboratory was under military control. In those early years, from 1943 to 1946, there were about two dozen other deaths—truck and tractor accidents, inadvertent weapons discharges, a suicide, a drowning, a fall from a horse. Four of the fatalities were just bad luck, involving a group of janitors who shared muscatel wine that was laced with antifreeze. But only Slotin and his co-worker Harry Daghlian, Jr., succumbed to the special hazards of the Manhattan Project. Three months to the day before Slotin’s accident, Daghlian had been working with the very same plutonium core, performing a different criticality experiment that used tungsten-carbide blocks instead of the beryllium tamper. He dropped one of the blocks, and the core briefly went critical. Daghlian took nearly a month to die.
generalinterest 
5 weeks ago
A Trump campaign will only increase the Democrats’ advantage in data and analytics - The Washington Post
The absence of investments in data and analytics by the Trump campaign will only deepen the Republican Party’s disadvantage when it comes to political data. In 2004, practitioners in both parties believed that the reelection campaign of George W. Bush had better voter data and more robust systems for collecting, managing and analyzing it, more sophisticated field efforts and better technologies that supported voter contact. As I have chronicled, the Democrats then invested in new infrastructure, including a voter database and interface system called VoteBuilder, that underpins nearly every Democratic campaign to this day.

While the Democrats were developing this party infrastructure, a degree of complacency set in within the Republican Party. Sen. John McCain’s 2008 presidential bid, hamstrung in part by its reliance on public financing, hired just 15 staffers in the areas of technology, digital, data or analytics over the course of the campaign.

In contrast, the comparatively flush 2008 Obama campaign, which eschewed public financing, hired 131 staffers in technology, digital, data and analytics. The Obama campaign gave resources to many vendors — most notably Blue State Digital and Voter Activation Network (now NGP-VAN) — which helped them build capacity. The Obama campaign also provided the party with an extraordinary pool of small donors, millions of voter contacts generated by its expansive field operation, and staffers with specialized expertise and presidential campaign experience.

This paid dividends for the 2012 cycle, and Democrats are still reaping its benefits today. In an interview with me early in 2012, one former Republican Party staffer summed up the differences between the two parties like this: “where they maybe could have 500 or 1,000 people that could manipulate state level voter data, and we had 50, maybe.”

This meant that Republican presidential nominee Mitt Romney was already behind Obama at the start of the 2012 campaign. That disadvantage was significantly compounded by the fact that Romney faced a protracted primary and Obama enjoyed what I call a “technical advantage of incumbency.”

The Obama campaign had a year and a half and comparably greater resources to start putting together its data and analytics teams, coordinate with the Democratic Party and develop its technology “products.” According to FEC data, Obama’s campaign had $250 million more than Romney’s, which for Romney translated into fewer in-house staffers, technology projects, field infrastructure and political data. (Candidate spending is the most important with respect to political data because campaigns make investments in field infrastructure, data and analytics, while outside groups primarily engage in broadcast advertising.)

For example, of the Obama reelection bid’s 342 staffers in technology, digital, data and analytics, 58 had primary work experience in commercial industry, and 48 came to the campaign with primary work backgrounds for technology or data/analytics firms. By comparison, the Romney campaign hired 87 staffers in technology, digital, data and analytics, 34 with primary backgrounds in commercial industry and seven in technology or data/analytics. These differences are important because these staffers often go on to work for other campaigns, such as Democratic front-runner Hillary Clinton’s, or found new ventures that carry political knowledge and technologies across cycles.

[The real story about how the Obama and Romney campaigns used Twitter]

One example is Civis Analytics, a data and analytics firm founded by Obama 2012 veteran Dan Wagner that was staffed by about one-third of the Obama 2012 analytics department. Several former Civis staffers are now working with Clinton’s campaign. Civis is one of 19 new organizations founded by Obama 2012 staffers, compared with three founded by veterans of Romney’s run.
politics  platformization  digitalSTS 
5 weeks ago
What can I do right now to get into NIPS? : MachineLearning
There's a conference called NIPS and I just saw their website https://nips.cc/ and it says the deadline is in less than 20 hours. I realize that it's cutting it a bit close, but the website says it only has to be 8 pages which doesn't seem like that much. I want to submit a paper, but I can't think of a topic. Can someone help me? What can I do that will get my paper into NIPS? I saw that not all papers get accepted so I only want good ideas. I don't know much about Machine Learning, but I just read the wiki page on it and it seems really interesting.
Edit: Serious replies only PLEASE
machinelearning  artificial_intelligence 
5 weeks ago
Online School Enriches Affiliated Companies if Not Its Students - The New York Times
Dropout is clearly a major problem with online learning.

"Mr. Lager declined requests for an interview. In an emailed statement on Tuesday, he did not respond to questions about his affiliated companies but said the Electronic Classroom’s graduation rate did not accurately measure the school’s performance.

In the statement, he said many students arrived at the school already off-track and have trouble making up the course credits in time to graduate.

“Holding a school accountable for such students is like charging a relief pitcher with a loss when they enter a game three runs behind and wiping out the record of the starting pitcher,” his statement said.

The statement added that the school “should be judged based on an accountability system that successfully controls for the academic effects of demographic factors such as poverty, special needs and mobility.”

Continue reading the main story

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In an interview, Rick Teeters, the superintendent of the Electronic Classroom, said many of the students were older than was typical for their grade, while others faced serious life challenges, including pregnancy or poverty."
moocs  public_discourse 
5 weeks ago
How the U.S. Could Regulate Facebook - The Atlantic
JZ on how Facebook might be regulated.

"But even if Thune and other Republicans wanted to regulate Facebook, it’s not clear how they would do it.

“It’s all tricky, because it’s all speech,” says Jonathan Zittrain, a law and computer-science professor at Harvard University and a co-founder of the school’s Berkman Center for Internet and Society. At the end of the day, Facebook makes an editorial product, and like any editorial product it is protected under the First Amendment. But federal regulators or entrepreneurial legislators would still have several options.

First, the Federal Trade Commission could require that Facebook choose a slightly less objective-seeming word than “Trending” for its feature.

“They could call it ‘Special Topics’ or ‘Highlighted Topics’ instead of ‘Trending Topics,’” Zittrain told me. “But if you change the label, we’re back to where we started. And the sloppiness in labeling may represent a sensibility that says, ‘it’s really not our responsibility what goes on in the minds of our users insofar as it garners us more clicks,’” he said.

Congress could also insist that certain standards had to be upheld during curation. In the early 1990s, Congress began requiring cable companies to offer a broadcast station (like the local ABC or NBC affiliate) if the signal from that station’s antenna reached a cable subscriber’s home. The courts eventually upheld this “must carry” provision because it was “content neutral”—it regulated speech without abridging the meaning or political view.

But Zittrain said there may be an even more promising way to keep Facebook from acting against its users’ interest. In an unpublished paper that he is writing with Jack Balkin, a Constitutional law professor at Yale Law School, Zittrain recommends that certain massive repositories of user data—like Apple, Facebook, and Google—be offered a chance to declare themselves “information fiduciaries.” An information fiduciary would owe certain protections to its users, closing the “disconnect between the level of trust we place in [online services] and the level of trust in fact owed to us,” according to the paper.

The key to this idea? Facebook might opt into this regulation itself."
facebook  algorithms  regulation 
5 weeks ago
When Websites Won’t Take No for an Answer - The New York Times
"To help companies gauge where their techniques fall along the persuasive-to-manipulative spectrum, Chris Nodder, a user-experience consultant in Seattle, has developed guidelines for ethical conduct. Systems that nudge people to act in the public interest are “charitable,” he told me, while products like Fitbit, which may help people develop better habits, are “motivational.”

“If the company benefits more than the consumer, I would call it ‘evil design,’” said Mr. Nodder, who wrote a book on the topic called “Evil by Design.” If an approach benefits the company and the customer equally, he added, “you are probably in the realm of ‘commercial design.’"
platformization  nudging 
5 weeks ago
Innovation for What? The Politics of Inequality in Higher Education | Dissent Magazine
Review of Christensen's The Innovative University. I like the review but the whole prologue on innovation might be misguided -- there is a whole criticism of the innovation that universities are trying to do in their labs by partnering with corporations; but what Christensen is saying is how the university can innovate mainly in its teaching function. That can be criticized on a number of levels, esp. that universities are not a business and they're fundamentally an agent of citizen production and equality. So yes. And also no.
higher_ed  moocs 
6 weeks ago
The Entrepreneurship Racket | Jacobin
"toyotist" models of production anyone? I wonder how one writes an article to basically say that genuine creativity is declining because academia follows corporations in deciding what the truly innovative ideas or innovations are.


"In other words, US patent law was radically altered to encourage universities to claim intellectual ownership of potentially profitable research, to license it, and to develop, build, and market inventions for the sake of profit.

Since then, at many research universities the model for teaching and research faculty has shifted to something more closely resembling a Toyotist, or just-in-time structure. The university now communicates and coordinates in near–real time with science, tech, and venture capital markets through its centers and executives. Universities actively respond to the flow of industry demand, in the same way that an assembly line is programmed to respond to real-time demand for parts, adapting to industry’s shifting preferences for the kinds of innovation it desires.

Michael Hardt argues that Toyotist models of production are “not simply a more rapid feedback loop . . . but an inversion of the Fordist relationship.” In the entrepreneurial university, this means that the decision to pursue a particular line of research (or to prototype a particular widget) actually comes after and in reaction to a market decision that has already been made. Even pedagogy must change in response to fluctuating market “interests,” oftentimes with consequences for campus culture and resource allocation."
moocs  higher_ed  platformization  toblog 
6 weeks ago
My sabbatical research pivot | Bits and Behavior
After I stepped down as AnswerDash CTO and begin my post-tenure sabbatical, it became clear I had to pivot my research focus. No more developer tools. No more studies of productivity. I’m now much less interested in accelerating developers’ work, and much more interested shaping how developers (and developers-in-training) learn and shape their behavior.

This pivot from productivity to learning has already had profound consequences to my research career. For a long time, I’ve published in software engineering venues that are much more concerned with productivity than learning. That might mean I have less to say to that community, or that I start contributing discoveries that they’re not used to reading about, evaluating, or prioritizing. It means that I’ll be publishing more in computing education conferences (like ACM’s International Computing Education Research conference). It means I’ll be looking for students that are less interested in designing tools that help them code faster, and more interested in designing tools to help developers of all skill levels code better. And it means that my measures of success will no longer be about the time it takes to code, but how long it takes to learn to code and how well someone codes.

This pivot wasn’t an easy choice. Computing education research is a much smaller, much less mature, and much less prestigious research community in computing research. There’s less funding, fewer students, and honestly, the research is much more difficult than HCI and software engineering research, because measuring learning and shaping how people think and behave is more difficult than creating tools. Making this pivot means making real sacrifices in my own professional productivity. It means seeing the friends I made in the software engineering research community less often. It means tackling much trickier, more nuanced problems, and having to educate my doctoral students in a broader range of disciplines (computer science, social science, and learning science).

But here’s the upside: I believe my work will be vastly more important and impactful in the arc of my career. I won’t just be making an engineer at Google ship product faster, I’ll be inventing learning technologies and techniques that make the next 10,000 Google engineers more effective at their job. I’ll be helping to eliminate the hundreds of thousands of horrific experiences that people have learning to code into more fulfilling and empowering experiences, potentially giving the world an order of magnitude more capable engineers. Creating a massive increase in the supply of well-educated engineers might even slow down some of the unsustainable growth of software engineering salaries, which are at least part of the unsustainable gentrification of many of our great American cities. And most importantly, I’ll be helping to give everyone that learns to code the belief that they can succeed at learning something that is shaping the foundational infrastructures of our societies.

I’ll continue to be part of the software engineering research community. But don’t be surprised if my work begins to focus on making helping better developers write better code than simply writing code faster. I’ll continue to be part of the HCI research community, but you’ll see my work focus on interactive learning technologies that accelerate learning, promote transfer, and shape identity. And for now, you’ll see me invest much more in building the nascent community of computing education researchers, helping it blossom into the field it needs to become to transform society’s ability to use and reason about code as it weaves itself deeper into our world.
moocs  platformization  learning_research  computer_science 
6 weeks ago
Impact of Social Sciences – What are the most-cited publications in the social sciences (according to Google Scholar)?
Note that Situated Learning by Lave and Wenger is in the top 10 as is Wenger's Communities of Practice. I should quote this.
moocs  learning_research 
6 weeks ago
Ben Rhodes and the Tough Sell of Obama's Foreign Policy - POLITICO Magazine
The Ben Rhoades profile and its uproar is interesting because it tells us how "messaging" works - including how Twitter is used but also how different visions of the national interest try to message. Pieces worth browsing might be the original piece, Jeffrey Goldberg's response, Fred Kaplan's response, Yglesias' response, also Noah Millman's interesting piece on it etc.

"In general, though, Rhodes and Obama wish the media focused less on the Middle East and the related issue of terrorism. That’s not just because they believe the danger of terrorism is consistently overhyped, although they do believe that. It’s not just because they believe threat inflation helps terrorists spread fear, although they believe that as well. Rhodes worries that the hype cycle ratchets up demand for misguided Iraq War-style responses, and Obama apparently shares that concern."
toblog  journalism 
6 weeks ago
The inside story of Facebook’s biggest setback | Rahul Bhatia | Technology | The Guardian
I wish people wouldn't make statements like: India is not Tanzania.

But this quote is nice:

When I asked the Facebook executive why the company had failed to heed the growing protests and carried on fighting so hard for Free Basics, he pointed to Zuckerberg’s intense belief in Facebook’s mission. “This happens every time Facebook pushes out a new change,” he said. “New privacy settings? People protest, Facebook changes it just a little, and people get used to it. The same thing probably happened here. Mark would have thought people would get used to it.”
facebook  india  platformization  regulation 
6 weeks ago
In conclusion, Game of Thrones is a franchise of contrasts. — Medium
For the television series, it’s more complicated. The crucial question is this: How do you take a story that’s written as a deliberate repudiation of 1990s fantasy norms and make it work, twenty years later, with an audience that didn’t necessarily grow up with Terry Brooks and Robert Jordan novels? The story is generally strong enough that it’s managed to survive and thrive; the failures of the Starks are not just reversals of fantasy convention but overall storytelling convention. But the longer the series goes, the less able it is to draw upon such clear subversions.
television 
6 weeks ago
The Genetics of Staying in School - The Atlantic
Genes for education but not education genes. These genes correlate with staying in school
learning_research  moocs 
6 weeks ago
This Mongolian Teenager Aced a MOOC. Now He Wants to Widen Their Impact. - The Chronicle of Higher Education
Uff so many problematics with this -- esp. Rafael Reif saying that the developing world and poor people need entrepreneurship classes! Please!
moocs  public_discourse 
6 weeks ago
The Fearful and the Frustrated - The New Yorker
Most people, in Johnson’s view, are animated by other parts of Trump’s pitch—“that he’s going to get in and make the tough deals, and nobody’s going to screw with him, because he’ll drop bombs.” That coalition—the fearful and the frustrated—is powerful. “That’s how you begin to get to eighteen per cent,” Johnson said.
generalinterest  politics 
6 weeks ago
What Nicholas Kristof gets wrong (and right) about conservatives in academia
Why doesn't Gross say something like: yes, if more conservatives applied, we'd do our best to make sure that they weren't turned away for their politics? Why does he end by saying we need people to do good empirical work and show how the world is? Hmmmm..
toblog 
6 weeks ago
I'm an obesity doctor. I've seen long-term weight loss work. Here's how.
This is something I've witnessed regularly in my own practice. Looking to my experiences working with thousands of patients over the course of the past dozen years, it's clear that liking the life you're living while you're losing weight is the key to keeping it off.

Liking the life you're living while you're losing looks different to each individual. There is no one "best" diet. While different diet gurus and their acolytes will try to tell you that their diet is the best and only diet, there is definitely no clear winner in the medical literature.

Moreover, even if there were a clear winner on paper, if the key to your success is actually liking the life and diet you're living with while you're losing, one person's best diet, if not enjoyed, would be another person's worst.
generalinterest  health 
6 weeks ago
Facebook Trending: It’s made of people!! (but we should have already known that) | Social Media Collective
But the plain fact of information algorithms like the ones used to identify “trends” is that they do not work alone, they cannot work alone — in so many ways that we must simply discard the fantasy that they do, or ever will. In fact, algorithms do surprisingly little, they just do it really quickly and with a whole lot of data. Here’s some of what they can’t do:

Traditional news organizations face analogous problems and must make analogous choices, and can make analogous missteps. And they do. But two countervailing forces work against this, keep them more honest than not, more on target than not: a palpable and institutionalized commitment to news itself, and competition. I have no desire to glorify the current news landscape, which in many ways produces news that is disheartening less than what journalism should be. But there is at least a public, shared, institutionally rehearsed, and historical sense of purpose and mission, or at least there’s one available. Journalism schools teach their students about not just how to determine and deliver the news, but why. They offer up professional guidelines and heroic narratives that position the journalist as a provider of political truths and public insight. They provide journalists with frames that help them identify the way news can suffer when it overlaps with public relations, spin, infotainment, and advertising. There are buffers in place to protect journalists from the pressures that can come from the upper management, advertisers, or newsmakers themselves, because of a belief that independence is an important foundation for newsgathering. Journalists recognize that their choices have consequences, and they discuss those choices. And there are stakeholders for regularly checking these efforts for possible bias and self-interest: public editors and ombudspeople, newswatch organizations and public critics, all trying to keep the process honest. Most of all, there are competitors who would gleefully point out a news organization’s mistakes and failures, which gives editors and managers real incentive to work against the temptations to produce news that is self-serving, politically slanted, or commercially craven.
Facebook seemed to have thought of absolutely none of these. Based on the revelations in the two Gizmodo articles, it’s clear that they hired a shoestring team, lashed them to the algorithm, offered little guidance for what it meant to make curatorial choices, provided no ongoing oversight as the project progressed, imposed self-interested guidelines to protect the company, and kept the entire process inscrutable to the public, cloaked in the promise of an algorithm doing its algorithm thing
facebook  siliconvalley  algorithms  platformization 
6 weeks ago
Colloquium Details | Computer Science & Engineering
John Markoff's talk at UW on machines and humans and automation
automation  artificial_intelligence 
7 weeks ago
At Death's Door | Part 2 - Justice Delayed
Death penalty in India. Lower courts sentence people to death on flimsy grounds that high courts overturn; that accounts for why people are sentenced to death but not executed. but along the way, there's a lot of police torture, forced confessions and all-round chaos.
india  generalinterest 
7 weeks ago
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