Can We Develop Herd Immunity to Internet Propaganda?
Internet propaganda is becoming an industrialized commodity, warns Phil Howard, the director of the Oxford Internet Institute and author of many books on disinformation. In an interview, he calls for greater transparency and regulation of the industry.
Platforms like Parler, TheDonald, Breitbart and Anon are like petri dishes for testing out ideas, to see what sticks. If extremist influencers see that something gets traction, they ramp it up. In the language of disease, you would say these platforms act as a vector, like a germ that carries a disease into other, more public forums.
at some point a major influencer takes a new meme from one of these extremist forums and puts it out before a wider audience. It works like a vector-borne disease like malaria, where the mosquitoes do the transmission. So, maybe a Hollywood actor or an influencer who knows nothing about politics will take this idea and post it on the bigger, better known platform. From there, these memes escalate as they move from Parler to maybe Reddit and from there to Twitter, Facebook, Instagram and YouTube. We call this “cascades of misinformation.“
Sometimes the cascades of misinformation bounce from country to country between the U.S., Canada and the UK for example. So, it echoes back and forth.
Within Europe, two reservoirs for disinformation stick out: Poland and Hungary.
Our 2020 report shows that cyber troop activity continues to increase around the world. This year, we found evidence of 81 countries using social media to spread computational propaganda and disinformation about politics. This has increased from last years’ report, where we identified 70 countries with cyber troop activity.
identified 63 new instances of private firms working with governments or political parties to spread disinformation about elections or other important political issues. We identified 21 such cases in 2017-2018, yet only 15 in the period between 2009 and 2016.
Why would well-funded Russian agencies buy disinformation services from a newcomer like Nigeria?
(1) Russian actors have found a lab in Nigeria that can provide services at competitive prices. (2) But countries like China and Russia seem to be developing an interest in political influence in many African countries, so it is possible that there is a service industry for disinformation in Nigeria for that part of the world.
Each social media company should provide some kind of accounting statement about how it deals with misuse, with reporting hate speech, with fact checking and jury systems and so on. This system of transparency and accountability works for the stock markets, why shouldn’t it work in the social media realm?
We clearly need a digital civics curriculum. The 12 to 16 year olds are developing their media attitudes now, they will be voting soon. There is very good media education in Canada or the Netherlands for example, and that is an excellent long-term strategy.
Thirty-nine percent of principals and district leaders say their district has converted snow days to remote learning days, according to a recent EdWeek Research Center survey.
How is your school handling snow days during virtual instruction? 📸: iStock/Getty pic.twitter.com/66EomberWf
Jack of all trades. LinkedIn had — and still has — multiple branded apps: Job Search, SlideShare, Learning, Recruiter, Sales Navigator and something call ‘Elevate”
Bad at integration and scaling. LinkedIn acquired many companies to introduce various services, but wasn’t so good at making them work.
Ads were expensive and user-unfriendly. Natalie Halimi, a marketer with 10 years of experience, wrote about LinkedIn ads back in July 2014. She used the headers “high CPC, poor dashboard, poor analysis” and concluded “ LinkedIn need to reassess their pricing strategy to provide better ROI for advertisers”.
Overvalued, full stop. Just before the plunge, LinkedIn shares were trading at 50x forward earnings. Twitter was at 30x, Facebook 34x and Google 21x. It was one of the most expensive stocks in tech.
When Microsoft introduced Office 365, it was to battle Google’s G Suite which appealed to smaller businesses with its cheaper pricing and cloud-based subscription model.
It is succeeding. According to a 2018 Bitglass survey, Office 365’s global market share has gone up to 56.3% from 7.7% in just four years. G Suite has stayed at about 25% since 2016.
LinkedIn’s employees were actually using G suite — the whole bag: Gmail, Calendar, Drive, Hangouts, Docs, Sheets… — before the Microsoft acquisition.
But more technology doesn’t always mean better results. Within K-12 learning environments, the digital divide means that students in low-income and rural households have less access to reliable internet and fewer connected deviceson which to complete the online portions of their homework. And while Pearson’s initiative applies only to textbooks in higher ed, the shift to digital has implications at the collegiate level as well.
Just as traditional software has a thriving open source community, textbooks have Open Educational Resources, complete textbooks that typically come free of charge digitally, or for a small fee—enough to cover the printing—in hard copy. And while it’s not an entirely new concept, OER has gained momentum in recent years, particularly as support has picked up at an institutional level, rather than on a course by course basis. According to a 2018 Babson College survey, faculty awareness of OER jumped from 34 percent to 46 percent since 2015.
One of OER’s leading proponents is OpenStax, a nonprofit based out of Rice University that offers a few dozen free textbooks, covering everything from AP Biology to Principles of Accounting. In the 2019–2020 academic year, 2.7 million students across 6,600 institutions used an OpenStax product instead of a for-profit equivalent.
The knock against OER is that, well, you get what you pay for. “One faculty member told me only half-jokingly, that OER is like a puppy that’s free. You get the free puppy, but then you have to do all the work,” says Cengage’s Hansen, who argues that traditional publishers provide critical supporting materials, like assessment questions, that OER often lacks, and can push more regular updates.
By virtue of being free, OER materials also heavily skew toward digital, with hardcover as a secondary option. (Or you can download the PDF and print it out yourself.) The same caveats about efficacy apply. But at least OER doesn’t lock you into one digital platform, the way the major publishers do. OpenStax alone counts around 50 ecosystem partners to provide homework and testing support.
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Or you could always split the difference.
That’s the territory Cengage wants to stake out. Late last summer, the educational publishing behemoth—it announced a planned merger with McGraw Hill in May; the combined company would surpass all but Pearson in market capitalization—rolled out Cengage Unlimited, a “Netflix for Textbooks” model that rolls all textbook rentals and digital platform access into a single rate: $120 for a semester, $180 for a full year, or $240 for two years. Almost a year in, the US-only program has a million subscribers.
Facebook’s board works more like an advisory committee than an overseer, because Mark controls around 60 percent of voting shares. Mark alone can decide how to configure Facebook’s algorithms to determine what people see in their News Feeds, what privacy settings they can use and even which messages get delivered. He sets the rules for how to distinguish violent and incendiary speech from the merely offensive, and he can choose to shut down a competitor by acquiring, blocking or copying it.
We are a nation with a tradition of reining in monopolies, no matter how well intentioned the leaders of these companies may be. Mark’s power is unprecedented and un-American.
It is time to break up Facebook.
America was built on the idea that power should not be concentrated in any one person, because we are all fallible. That’s why the founders created a system of checks and balances.
More legislation followed in the 20th century, creating legal and regulatory structures to promote competition and hold the biggest companies accountable.
Starting in the 1970s, a small but dedicated group of economists, lawyers and policymakers sowed the seeds of our cynicism. Over the next 40 years, they financed a network of think tanks, journals, social clubs, academic centers and media outlets to teach an emerging generation that private interests should take precedence over public ones. Their gospel was simple: “Free” markets are dynamic and productive, while government is bureaucratic and ineffective.
From our earliest days, Mark used the word “domination” to describe our ambitions, with no hint of irony or humility.
Facebook’s monopoly is also visible in its usage statistics.About 70 percent of American adults use social media, and a vast majority are on Facebook products. Over two-thirds use the core site, a third use Instagram, and a fifth use WhatsApp. By contrast, fewer than a third report using Pinterest, LinkedIn or Snapchat. What started out as lighthearted entertainment has become the primary way that people of all ages communicate online.
The F.T.C.’s biggest mistake was to allow Facebook to acquire Instagram and WhatsApp. In 2012, the newer platforms were nipping at Facebook’s heels because they had been built for the smartphone, where Facebook was still struggling to gain traction. Mark responded by buying them, and the F.T.C. approved.
The News Feed algorithm reportedly prioritized videos created through Facebook over videos from competitors, like YouTube and Vimeo. In 2012, Twitter introduced a video network called Vine that featured six-second videos. That same day, Facebook blocked Vine from hosting a tool that let its users search for their Facebook friends while on the new network.The decision hobbled Vine, which shut down four years later.
unlike Vine, Snapchat wasn’t interfacing with the Facebook ecosystem; there was no obvious way to handicap the company or shut it out. So Facebook simply copied it. (opyright law does not extend to the abstract concept itself.)
As markets become more concentrated, the number of new start-up businesses declines. This holds true in other high-tech areas dominated by single companies, like search (controlled by Google) and e-commerce (taken over by Amazon). Meanwhile, there has been plenty of innovation in areas where there is no monopolistic domination, such as in workplace productivity (Slack, Trello, Asana), urban transportation (Lyft, Uber, Lime, Bird) and cryptocurrency exchanges (Ripple, Coinbase, Circle).
The choice is mine, but it doesn’t feel like a choice. Facebook seeps into every corner of our lives to capture as much of our attention and data as possible and, without any alternative, we make the trade.
Just last month, Facebook seemingly tried to bury news that it had stored tens of millions of user passwords in plain text format, which thousands of Facebook employees could see. Competition alone wouldn’t necessarily spur privacy protection — regulation is required to ensure accountability — but Facebook’s lock on the market guarantees that users can’t protest by moving to alternative platforms.
Mark used to insist that Facebook was just a “social utility,” a neutral platform for people to communicate what they wished. Now he recognizes that Facebook is both a platform and a publisher and that it is inevitably making decisions about values. The company’s own lawyers have argued in court that Facebook is a publisher and thus entitled to First Amendment protection.
As if Facebook’s opaque algorithms weren’t enough, last year we learned that Facebook executives had permanently deleted their own messages from the platform, erasing them from the inboxes of recipients; the justification was corporate security concerns.
Mark may never have a boss, but he needs to have some check on his power. The American government needs to do two things: break up Facebook’s monopoly and regulate the company to make it more accountable to the American people.
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We Don’t Need Social Media
The push to regulate or break up Facebook ignores the fact that its services do more harm than good
Hughes joins a growing chorus of former Silicon Valley unicorn riders who’ve recently had second thoughts about the utility or benefit of the surveillance-attention economy their products and platforms have helped create. He is also not the first to suggest that government might need to step in to clean up the mess they made
Nick Srnicek, author of the book Platform Capitalismand a lecturer in digital economy at King’s College London, wrotelast month, “[I]t’s competition — not size — that demands more data, more attention, more engagement and more profits at all costs
guide (available as PDF here and Google Doc here) to offer some explanations of how to avoid copyright infringement by using media that you can legally re-use for classroom projects including blog posts, web pages, videos, slideshows, and podcasts. The guide also includes 21 places to find media to use in classroom projects.
FOR MORE INFO ON COPYRIGHT AND RELATED (fair use, Creative Commons etc.): contact Rachel Wexelbaum, rwexelabum@stcloudstate.edu
Evelyn Berezin, a computer scientist who designed the world’s first word processor, has died at the age of 93.
as she explained in an oral history interview, she was having trouble finding work in the physics field, so she started asking about computers — having barely even heard of them.
It wasn’t easy being a woman in the industry. In 1960, Berezin says she was offered a job at the New York Stock Exchange, as a vice president managing the computer system that handled their communications. But then the offer was retracted by the board of directors.
In 2006, Berezin was inducted into the Long Island Technology Hall of Fame, and she joined the Women In Technology Hall of Fame in 2011. In 2015, she became a fellow at the Computer History Museum.
One of the issues dividing the two main parliamentary blocs is whether there should be a cap on profit margins for publicly funded private schools.
The Swedish school system has received considerable internationalattention in recent years due to alarming test scores in the OECD’s international PISA study
Segregation is one of the most serious social problems facing Sweden and many other wealthy nations.
A recent report (the English title would be “A Nation Divided – School Choice and Segregation in Sweden”) that I have co-authored for the Stockholm based think tank Arena Idé shows that well-educated and Swedish-born families increasingly opt out of schools where the children have parents with lower educational attainments and an immigrant background. We also show that this “white flight” in Swedish municipalities throughout the country is increased by school choice and other reforms introduced in the early 1990s, whereby publicly financed private schools are allowed to compete with municipal schools for school vouchers allotted to each individual student.
The results in our study should be viewed in light of two recent reports: one from the OECDand another from UNICEF, both highlighting the inequality in the Swedish school system.
The results make it painfully clear that the Swedish school system effectively works against the very idea that schools should level the playing field for students from all backgrounds and give every child equal opportunity. Even after the rise of right-wing populism in Sweden, our established political parties have proven themselves unable, or unwilling, to rein in the highly unregulated Swedish school market.
Sejnowski, T. J. (2018). The Deep Learning Revolution. Cambridge, MA: The MIT Press.
How deep learning―from Google Translate to driverless cars to personal cognitive assistants―is changing our lives and transforming every sector of the economy.
The deep learning revolution has brought us driverless cars, the greatly improved Google Translate, fluent conversations with Siri and Alexa, and enormous profits from automated trading on the New York Stock Exchange. Deep learning networks can play poker better than professional poker players and defeat a world champion at Go. In this book, Terry Sejnowski explains how deep learning went from being an arcane academic field to a disruptive technology in the information economy.
Sejnowski played an important role in the founding of deep learning, as one of a small group of researchers in the 1980s who challenged the prevailing logic-and-symbol based version of AI. The new version of AI Sejnowski and others developed, which became deep learning, is fueled instead by data. Deep networks learn from data in the same way that babies experience the world, starting with fresh eyes and gradually acquiring the skills needed to navigate novel environments. Learning algorithms extract information from raw data; information can be used to create knowledge; knowledge underlies understanding; understanding leads to wisdom. Someday a driverless car will know the road better than you do and drive with more skill; a deep learning network will diagnose your illness; a personal cognitive assistant will augment your puny human brain. It took nature many millions of years to evolve human intelligence; AI is on a trajectory measured in decades. Sejnowski prepares us for a deep learning future.
Buzzwords like “deep learning” and “neural networks” are everywhere, but so much of the popular understanding is misguided, says Terrence Sejnowski, a computational neuroscientist at the Salk Institute for Biological Studies.
Sejnowski, a pioneer in the study of learning algorithms, is the author of The Deep Learning Revolution(out next week from MIT Press). He argues that the hype about killer AI or robots making us obsolete ignores exciting possibilities happening in the fields of computer science and neuroscience, and what can happen when artificial intelligence meets human intelligence.
Machine learning is a very large field and goes way back. Originally, people were calling it “pattern recognition,” but the algorithms became much broader and much more sophisticated mathematically. Within machine learning are neural networks inspired by the brain, and then deep learning. Deep learning algorithms have a particular architecture with many layers that flow through the network. So basically, deep learning is one part of machine learning and machine learning is one part of AI.
December 2012 at the NIPS meeting, which is the biggest AI conference. There, [computer scientist] Geoff Hinton and two of his graduate students showed you could take a very large dataset called ImageNet, with 10,000 categories and 10 million images, and reduce the classification error by 20 percent using deep learning.Traditionally on that dataset, error decreases by less than 1 percent in one year. In one year, 20 years of research was bypassed. That really opened the floodgates.
The inspiration for deep learning really comes from neuroscience.
AlphaGo, the program that beat the Go champion included not just a model of the cortex, but also a model of a part of the brain called the basal ganglia, which is important for making a sequence of decisions to meet a goal. There’s an algorithm there called temporal differences, developed back in the ‘80s by Richard Sutton, that, when coupled with deep learning, is capable of very sophisticated plays that no human has ever seen before.
there’s a convergence occurring between AI and human intelligence. As we learn more and more about how the brain works, that’s going to reflect back in AI. But at the same time, they’re actually creating a whole theory of learning that can be applied to understanding the brain and allowing us to analyze the thousands of neurons and how their activities are coming out. So there’s this feedback loop between neuroscience and AI
Library of Congress launched the National Screening Room. The National Screening Room currently offers about 300 videos. The videos are digital copies of films made in the 19th and 20th centuries. You can browse the collection by date, location of the filming, and subject. You can also search for videos that are parts of other LOC collections. All of the videos in the National Screening Room can be viewed online and or downloaded as MP4 files.
Pixabay has been one of my go-to sites for public domain images for years. Pixabay also offers public domain video clips that you can download for free.
The Public Domain Review is a website that features collections of images, books, essays, audio recordings, and films that are in the public domain