What if You Knew What You Were Missing on Social Media?

Curated on Posted on by Stefaan Verhulst

Article by Julia Angwin: “Social media can feel like a giant newsstand, with more choices than any newsstand ever. It contains news not only from journalism outlets, but also from your grandma, your friends, celebrities and people in countries you have never visited. It is a bountiful feast.

But so often you don’t get to pick from the buffet. On most social media platforms, algorithms use your behavior to narrow in on the posts you are shown. If you send a celebrity’s post to a friend but breeze past your grandma’s, it may display more posts like the celebrity’s in your feed. Even when you choose which accounts to follow, the algorithm still decides which posts to show you and which to bury.

There are a lot of problems with this model. There is the possibility of being trapped in filter bubbles, where we see only news that confirms our existing beliefs. There are rabbit holes, where algorithms can push people toward more extreme content. And there are engagement-driven algorithms that often reward content that is outrageous or horrifying.

Yet not one of those problems is as damaging as the problem of who controls the algorithms. Never has the power to control public discourse been so completely in the hands of a few profit-seeking corporations with no requirements to serve the public good.

Elon Musk’s takeover of Twitter, which he renamed X, has shown what can happen when an individual pushes a political agenda by controlling a social media company.

Since Mr. Musk bought the platform, he has repeatedly declared that he wants to defeat the “woke mind virus” — which he has struggled to define but largely seems to mean Democratic and progressive policies. He has reinstated accounts that were banned because of the white supremacist and antisemitic views they espoused. He has banned journalists and activists. He has promoted far-right figures such as Tucker Carlson and Andrew Tate, who were kicked off other platforms. He has changed the rules so that users can pay to have some posts boosted by the algorithm, and has purportedly changed the algorithm to boost his own posts. The result, as Charlie Warzel said in The Atlantic, is that the platform is now a “far-right social network” that “advances the interests, prejudices and conspiracy theories of the right wing of American politics.”

The Twitter takeover has been a public reckoning with algorithmic control, but any tech company could do something similar. To prevent those who would hijack algorithms for power, we need a pro-choice movement for algorithms. We, the users, should be able to decide what we read at the newsstand…(More)”.

Journalism Is a Public Good and Should Be Publicly Funded

Curated on Posted on by Stefaan Verhulst

Essay by Patrick Walters: “News deserts” have proliferated across the U.S. Half of the nation’s more than 3,140 counties now have only one newspaper—and nearly 200 of them have no paper at all. Of the publications that survive, researchers have found many are “ghosts” of their former selves.

Journalism has problems nationally: CNN announced hundreds of layoffs at the end of 2022, and National Geographic laid off the last of its staff writers this June. In the latter month the Los Angeles Times cut 13 percent of its newsroom staff. But the crisis is even more acute at the local level, with jobs in local news plunging from 71,000 in 2008 to 31,000 in 2020. Closures and cutbacks often leave people without reliable sources that can provide them with what the American Press Institute has described as “the information they need to make the best possible decisions about their daily lives.”

Americans need to understand that journalism is a vital public good—one that, like roads, bridges and schools, is worthy of taxpayer support. We are already seeing the disastrous effects of otherwise allowing news to disintegrate in the free market: namely, a steady supply of misinformation, often masquerading as legitimate news, and too many communities left without a quality source of local news. Former New York Times public editor Margaret Sullivan has a called this a “crisis of American democracy.”

The terms “crisis” and “collapse” have become nearly ubiquitous in the past decade when describing the state of American journalism, which has been based on a for-profit commercial model since the rise of the “penny press” in the 1830s. Now that commercial model has collapsed amid the near disappearance of print advertising. Digital ads have not come close to closing the gap because Google and other platforms have “hoovered up everything,” as Emily Bell, founding director of the Tow Center for Journalism at Columbia University, told the Nieman Journalism Lab in a 2018 interview. In June the newspaper chain Gannett sued Google’s parent company, alleging it has created an advertising monopoly that has devastated the news industry.

Other journalism models—including nonprofits such as MinnPost, collaborative efforts such Broke in Philly and citizen journalism—have had some success in fulfilling what Lewis Friedland of the University of Wisconsin–Madison called “critical community information needs” in a chapter of the 2016 book The Communication Crisis in America, and How to Fix It. Friedland classified those needs as falling in eight areas: emergencies and risks, health and welfare, education, transportation, economic opportunities, the environment, civic information and political information. Nevertheless, these models have proven incapable of fully filling the void, as shown by the dearth of quality information during the early years of the COVID pandemic. Scholar Michelle Ferrier and others have worked to bring attention to how news deserts leave many rural and urban areas “impoverished by the lack of fresh, daily local news and information,” as Ferrier wrote in a 2018 article. A recent study also found evidence that U.S. judicial districts with lower newspaper circulation were likely to see fewer public corruption prosecutions.

A growing chorus of voices is now calling for government-funded journalism, a model that many in the profession have long seen as problematic…(More)”.

Wikipedia’s Moment of Truth

Curated on Posted on by Stefaan Verhulst

Article by Jon Gertner at the New York Times: “In early 2021, a Wikipedia editor peered into the future and saw what looked like a funnel cloud on the horizon: the rise of GPT-3, a precursor to the new chatbots from OpenAI. When this editor — a prolific Wikipedian who goes by the handle Barkeep49 on the site — gave the new technology a try, he could see that it was untrustworthy. The bot would readily mix fictional elements (a false name, a false academic citation) into otherwise factual and coherent answers. But he had no doubts about its potential. “I think A.I.’s day of writing a high-quality encyclopedia is coming sooner rather than later,” he wrote in “Death of Wikipedia,” an essay that he posted under his handle on Wikipedia itself. He speculated that a computerized model could, in time, displace his beloved website and its human editors, just as Wikipedia had supplanted the Encyclopaedia Britannica, which in 2012 announced it was discontinuing its print publication.

Recently, when I asked this editor — he asked me to withhold his name because Wikipedia editors can be the targets of abuse — if he still worried about his encyclopedia’s fate, he told me that the newer versions made him more convinced that ChatGPT was a threat. “It wouldn’t surprise me if things are fine for the next three years,” he said of Wikipedia, “and then, all of a sudden, in Year 4 or 5, things drop off a cliff.”..(More)”.

The Gutenberg Parenthesis: The Age of Print and Its Lessons for the Age of the Internet

Curated on Posted on by Stefaan Verhulst


Book by Jeff Jarvis: “The age of print is a grand exception in history. For five centuries it fostered what some call print culture – a worldview shaped by the completeness, permanence, and authority of the printed word. As a technology, print at its birth was as disruptive as the digital migration of today. Now, as the internet ushers us past print culture, journalist Jeff Jarvis offers important lessons from the era we leave behind.

To understand our transition out of the Gutenberg Age, Jarvis first examines the transition into it. Tracking Western industrialized print to its origins, he explores its invention, spread, and evolution, as well as the bureaucracy and censorship that followed. He also reveals how print gave rise to the idea of the mass – mass media, mass market, mass culture, mass politics, and so on – that came to dominate the public sphere.

What can we glean from the captivating, profound, and challenging history of our devotion to print? Could it be that we are returning to a time before mass media, to a society built on conversation, and that we are relearning how to hold that conversation with ourselves? Brimming with broader implications for today’s debates over communication, authorship, and ownership, Jarvis’ exploration of print on a grand scale is also a complex, compelling history of technology and power…(More)”

Shallowfakes

Curated on Posted on by Stefaan Verhulst

Essay by James R. Ostrowski: “…This dystopian fantasy, we are told, is what the average social media feed looks like today: a war zone of high-tech disinformation operations, vying for your attention, your support, your compliance. Journalist Joseph Bernstein, in his 2021 Harper’s piece “Bad News,” attributes this perception of social media to “Big Disinfo” — a cartel of think tanks, academic institutions, and prestige media outlets that spend their days spilling barrels of ink into op-eds about foreign powers’ newest disinformation tactics. The technology’s specific impact is always vague, yet somehow devastating. Democracy is dying, shot in the chest by artificial intelligence.

The problem with Big Disinfo isn’t that disinformation campaigns aren’t happening but that claims of mind-warping, AI-enabled propaganda go largely unscrutinized and often amount to mere speculation. There is little systematic public information about the scale at which foreign governments use deepfakes, bot armies, or generative text in influence ops. What little we know is gleaned through irregular investigations or leaked documents. In lieu of data, Big Disinfo squints into the fog, crying “Bigfoot!” at every oak tree.

Any machine learning researcher will admit that there is a critical disconnect between what’s possible in the lab and what’s happening in the field. Take deepfakes. When the technology was first developed, public discourse was saturated with proclamations that it would slacken society’s grip on reality. A 2019 New York Times op-ed, indicative of the general sentiment of this time, was titled “Deepfakes Are Coming. We Can No Longer Believe What We See.” That same week, Politico sounded the alarm in its article “‘Nightmarish’: Lawmakers brace for swarm of 2020 deepfakes.” A Forbes article asked us to imagine a deepfake video of President Trump announcing a nuclear weapons launch against North Korea. These stories, like others in the genre, gloss over questions of practicality…(More)”.

AI Is Tearing Wikipedia Apart

Curated on Posted on by Stefaan Verhulst

Article by Claire Woodcock: “As generative artificial intelligence continues to permeate all aspects of culture, the people who steward Wikipedia are divided on how best to proceed. 

During a recent community call, it became apparent that there is a community split over whether or not to use large language models to generate content. While some people expressed that tools like Open AI’s ChatGPT could help with generating and summarizing articles, others remained wary. 

The concern is that machine-generated content has to be balanced with a lot of human review and would overwhelm lesser-known wikis with bad content. While AI generators are useful for writing believable, human-like text, they are also prone to including erroneous information, and even citing sources and academic papers which don’t exist. This often results in text summaries which seem accurate, but on closer inspection are revealed to be completely fabricated. 

“The risk for Wikipedia is people could be lowering the quality by throwing in stuff that they haven’t checked,” Bruckman added. “I don’t think there’s anything wrong with using it as a first draft, but every point has to be verified.” 

The Wikimedia Foundation, the nonprofit organization behind the website, is looking into building tools to make it easier for volunteers to identify bot-generated content. Meanwhile, Wikipedia is working to draft a policy that lays out the limits to how volunteers can use large language models to create content.

The current draft policy notes that anyone unfamiliar with the risks of large language models should avoid using them to create Wikipedia content, because it can open the Wikimedia Foundation up to libel suits and copyright violations—both of which the nonprofit gets protections from but the Wikipedia volunteers do not. These large language models also contain implicit biases, which often result in content skewed against marginalized and underrepresented groups of people. 

The community is also divided on whether large language models should be allowed to train on Wikipedia content. While open access is a cornerstone of Wikipedia’s design principles, some worry the unrestricted scraping of internet data allows AI companies like OpenAI to exploit the open web to create closed commercial datasets for their models. This is especially a problem if the Wikipedia content itself is AI-generated, creating a feedback loop of potentially biased information, if left unchecked…(More)”.

DMA: rules for digital gatekeepers to ensure open markets start to apply

Curated on Posted on by Stefaan Verhulst

Press Release: “The EU Digital Markets Act (DMA) applies from today. Now that the DMA applies, potential gatekeepers that meet the quantitative thresholds established have until 3 July to notify their core platform services to the Commission. ..

The DMA aims to ensure contestable and fair markets in the digital sector. It defines gatekeepers as those large online platforms that provide an important gateway between business users and consumers, whose position can grant them the power to act as a private rule maker, and thus create a bottleneck in the digital economy. To address these issues, the DMA defines a series of specific obligations that gatekeepers will need to respect, including prohibiting them from engaging in certain behaviours in a list of do’s and don’ts. More information is available in the dedicated Q&A…(More)”.

Gaming Public Opinion

Curated on Posted on by Stefaan Verhulst

Article by Albert Zhang , Tilla Hoja & Jasmine Latimore: “The Chinese Communist Party’s (CCP’s) embrace of large-scale online influence operations and spreading of disinformation on Western social-media platforms has escalated since the first major attribution from Silicon Valley companies in 2019. While Chinese public diplomacy may have shifted to a softer tone in 2023 after many years of wolf-warrior online rhetoric, the Chinese Government continues to conduct global covert cyber-enabled influence operations. Those operations are now more frequent, increasingly sophisticated and increasingly effective in supporting the CCP’s strategic goals. They focus on disrupting the domestic, foreign, security and defence policies of foreign countries, and most of all they target democracies.

Currently—in targeted democracies—most political leaders, policymakers, businesses, civil society groups and publics have little understanding of how the CCP currently engages in clandestine activities online in their countries, even though this activity is escalating and evolving quickly. The stakes are high for democracies, given the indispensability of the internet and their reliance on open online spaces, free from interference. Despite years of monitoring covert CCP cyber-enabled influence operations by social-media platforms, governments, and research institutes such as ASPI, definitive public attribution of the actors driving these activities is rare. Covert online operations, by design, are difficult to detect and attribute to state actors. 

Social-media platforms and governments struggle to devote adequate resources to identifying, preventing and deterring increasing levels of malicious activity, and sometimes they don’t want to name and shame the Chinese Government for political, economic and/or commercial reasons…(More)”.

The Synchronized Society: Time and Control From Broadcasting to the Internet

Curated on Posted on by Stefaan Verhulst

Book by Randall Patnode: “…traces the history of the synchronous broadcast experience of the twentieth century and the transition to the asynchronous media that dominate today. Broadcasting grew out of the latent desire by nineteenth-century industrialists, political thinkers, and social reformers to tame an unruly society by controlling how people used their time. The idea manifested itself in the form of the broadcast schedule, a managed flow of information and entertainment that required audiences to be in a particular place – usually the home – at a particular time and helped to create “water cooler” moments, as audiences reflected on their shared media texts. Audiences began disconnecting from the broadcast schedule at the end of the twentieth century, but promoters of social media and television services still kept audiences under control, replacing the schedule with surveillance of media use. Author Randall Patnode offers compelling new insights into the intermingled roles of broadcasting and industrial/post-industrial work and how Americans spend their time…(More)”.

Exploring data journalism practices in Africa: data politics, media ecosystems and newsroom infrastructures

Curated on Posted on by Stefaan Verhulst

Paper by Sarah Chiumbu and Allen Munoriyarwa: “Extant research on data journalism in Africa has focused on newsroom factors and the predilections of individual journalists as determinants of the uptake of data journalism on the continent. This article diverts from this literature by examining the slow uptake of data journalism in sub- Saharan Africa through the prisms of non-newsroom factors. Drawing on in-depth interviews with prominent investigative journalists sampled from several African countries, we argue that to understand the slow uptake of data journalism on the continent; there is a need to critique the role of data politics, which encompasses state, market and existing media ecosystems across the continent. Therefore, it is necessary to move beyond newsroom-centric factors that have dominated the contemporary understanding of data journalism practices. A broader, non-newsroom conceptualisation beyond individual journalistic predilections and newsroom resources provides productive clarity on data journalism’s slow uptake on the continent. These arguments are made through the conceptual prisms of materiality, performativity and reflexivity…(More)”.