Should You Accept Internet Cookies? BU Researchers Say the Open Web Could Suffer Without Them

By Andrew Thurston, The Brink, Boston University

New study finds ad revenue that supports digital publishers and content creators tumbles when cookies are removed.

Image: Vyshnavi Bisani - unsplash

It’s a choice you may face multiple times a day—and, at this point, your reaction is probably reflexive. Are you going to accept those internet cookies, reject them, or spend a little time customizing your settings?

Increasingly, internet users are pushing back against cookies—the digital crumbs used by websites and advertisers to spot returning customers—by choosing privacy-enhancing browsers or clicking that reject button. But ditching the cookies may have big implications for the free web. If digital companies, content creators, and advertisers aren’t making money from our surfing, the quality and usefulness of the products they offer might suffer too.

In a new study, Boston University researchers highlight the potential impact the loss of cookies has on advertisers and how alternative systems designed to balance privacy and revenue fail to recoup the costs.

They analyzed 200 million ad impressions—or views—worldwide and found that removing cookies cut website publishers’ revenue by more than a third. They also discovered that privacy-enhanced alternatives, notably a major Google project called Privacy Sandbox, only clawed back a small portion of that lost revenue. The findings were published in PNAS, the National Academy of Sciences’ flagship journal.

“Internet cookies—especially third-party cookies—have been central to how online advertising works,” says Garrett Johnson, a BU Questrom School of Business associate professor of marketing. Third-party cookies are those placed by an organization, like an advertiser, not connected to the site you’re on. “In our study, removing third-party cookies reduced publisher ad revenue by about 35 percent—and about 66 percent in the European Union—showing that cookies still play a major economic role in supporting the open web.” The European Union has tougher online privacy rules than much of the rest of the world.

According to Zhengrong Gu, a Questrom PhD candidate, because cookies help advertisers spot users around the web, they can better target and measure their ads. That makes advertisers’ spending more efficient, putting more ad money in the pockets of content creators and publishers. “If more users decline cookies, it would likely reduce the effectiveness of digital advertising and the revenue that supports much of the open web,” says Gu (Questrom’26).

The downside of cookies: no one really likes being followed. “Website cookies are online surveillance tools,” wrote Wayne State University researcher Elizabeth Stoycheff in a Conversation article, “and the commercial and government entities that use them would prefer people not read those notifications too closely.”

There have been a couple of different responses to the decline in cookie use. One is the implementation of paywalls and subscriptions to keep the cash flowing; another is requiring customers to use log-ins that work across multiple sites. Tech companies are also experimenting with privacy-enhancing technologies (PETs) that try to balance advertising needs with user privacy concerns. One of the best known PETs is Privacy Sandbox, Google’s now-defunct six-year experiment in cookie alternatives, which included innovations such as a browser tool that shared a customer’s interests rather than their detailed online history.

“In our study, Privacy Sandbox recovered only about 4 percent of the revenue lost when cookies were removed,” says Shunto J. Kobayashi, a Questrom assistant professor of marketing. That weak impact was in part due to the limited adoption of the new tools and because they changed the user experience, he says, introducing “technical frictions, especially slower ad loading times.”

In their paper, the researchers write that their findings, alongside those from other studies, “informed Google’s decision to abandon its plan to replace cookies with Privacy Sandbox. The episode underscores the difficulty of aligning privacy, performance, and competition goals in digital markets.”

To examine privacy technologies in a real-world setting, the BU team used data from ad management firm Raptive, and leveraged an experiment conducted by Google and overseen by the United Kingdom’s Competition and Markets Authority. During the study, Chrome users were randomly assigned to one of three groups: cookies-enabled, cookies-disabled, or cookies replaced by Privacy Sandbox. The study included around 60 million desktop and mobile Chrome users.

“The experiment created a rare opportunity for independent, large-scale evaluation open to external participants,” says Johnson, an expert on digital marketing who has studied privacy regulations, online ad effectiveness, and the economics of digital advertising.

He adds that many European regulators are considering even tighter online privacy rules, which could have a negative impact: “Our results provide unusually strong evidence—from a global, industry-wide field experiment—that restricting cookies carries significant economic downsides that regulators should consider.”

As for users faced with that daily accept or reject decision, Johnson recognizes that everyone will make the call that works for them—but he leans toward clicking “accept.”

“From my perspective, accepting cookies creates substantial benefits for the advertising ecosystem and the publishers I care about,” he says, “with what I perceive to be little personal risk.”

This research received financial support from the Center for Industry Self-Regulation.

This post was originally published on Boston University's The Brink and republished here with permission.

Reviewed by Irfan Ahmad.

Read next: Your phone screen doesn’t have the same color range as the human eye – and AI widens the gap between digital images and the real thing
by External Contributor via Digital Information World

Your phone screen doesn’t have the same color range as the human eye – and AI widens the gap between digital images and the real thing

Douglas Goodwin, University of California, Los Angeles; California Institute of the Arts

Image: ricardo frantz - Unsplash

A peacock feather in sunlight shifts from blue to green to bronze as you turn it. Photograph it, and this shimmer collapses into one angle, one exposure, one compromise.

A digital image is not a record of what your eye sees. The standard color space that most digital images use was built for an older display world, when cathode-ray tube monitors swept beams of electrons across phosphor-coated glass. This standard color space made color predictable across many devices, but the compromise was a narrower range of colors for screens, cameras and image files to share.

Whatever the screen offers feels complete. It is not that your eyes cannot see more; digital images give them less to work with.

I teach a class about color at the California Institute of the Arts called Plastics, Neon, and Psychedelia, which covers the many ways color is produced: by materials, by light, by screens and by the mind.

I also have a condition called deuteranomaly, which changes the way I discriminate color, though not in the way you might imagine. A deuteranomalous eye does not simply lose color distinctions – it remaps them.

Vision researchers in Cambridge showed in 2005 that deuteranomalous observers can reliably distinguish khakis and olives that look identical to people with standard color vision. I have mistaken a traffic light for an overhead streetlamp while driving at night, but my color vision is not a shrunken copy of ordinary vision: It is a different map of the same ground.

While my eyes leave some colors uncertain, they sharpen other distinctions. Screens impose another kind of limit, though more quietly: They organize color according to their own rules, then offer that version as complete. My eye and the screen are both maps that include and exclude differently. Mine trades some distinctions for others. The screen trades range for reliability. The question for any color system is not whether it is accurate but what it keeps.

From wild green to screen green

My neon pothos houseplant is so green that it seems to generate its own light. Photograph it with a smartphone and the result is fine: The leaves are green, the picture makes sense. But the green in the photograph is not the green on the plant.

Look at the photo. Look at the plant. Then look at the photo again. The photographed leaves are muted, but not evenly. Some greens flatten while others appear boosted, as if the phone were trying to compensate for what it cannot show. The leaves on the actual plant are electric. No phone I own, no printed page and no Instax print has captured that green, though the Instax comes closer.

Here is what happens. Light bounces off the pothos and strikes the phone’s sensor, which records numbers representing the color the phone sensed. Each pixel is stored as a recipe for red, green and blue light: three values that tell a screen how much of each primary color to emit. In much of the image world, those numbers are still translated into sRGB, the default color space for ordinary digital images.

Color scientists map human color perception as a horseshoe-shaped field. A standard display space cuts a triangle from that horseshoe, enclosing only part of what the eye can see. A triangle’s straight sides cannot follow the horseshoe’s curve, so some colors always fall outside the display space.

Many modern screens can show more than sRGB, but sRGB remains the default format for ordinary digital images because it works reliably across devices and platforms. The pothos green is remapped to fit, and that remapped version is the picture you get. Screen green is not wild green.

Every medium translates color in its own way. Film does too, through chemistry, exposure, dyes and paper. The Instax print is not more accurate in any absolute sense, but it conveys the pothos differently. It reflects light from a surface rather than rebuilding color as light from a screen. The green feels denser, less flat and less removed from its source. The Instax still misses the plant’s absolute color, but it misses it in a different way.

The phone’s translation matters now because people see a thing’s color on a screen before they meet it in the world.

When AI learns from limited colors

AI image generators do not simply inherit this color gap. They can amplify it. They are not trained on the plant in front of you. They are trained on other people’s photographs of plants like it: millions of images already filtered through sensors, editing software, platform compression and the color limits described above. Many of the vivid greens were clipped or shifted before the model ever encountered them.

Ask an AI image model to generate a peacock feather and you will likely receive a competent image: the canonical eyespot, the dark pupil, the cyan ring, the gold, the magenta rim. The surviving colors are the ones the image world knows how to keep. What is missing is the iridescence.

In a real feather, the barbs can flash the same blue-green-bronze as the eyespot. A photograph fixes that shimmer to a single angle. The generated image flattens it further. Its barbs are muddy brown with faint metallic highlights. The model has learned the symbols of a peacock feather, but not the event of seeing one turn in the light.

Generative models make images from the patterns they find most often in their training images. They render ordinary brightness convincingly. The rarer effects are the ones that slip away: saturated colors, metallic flashes, structural glints. The model can still make an image that looks bright, even spectacular. But its brightness is screen-native, learned from other images on screens, not from seeing the subject itself.

The loop tightens with each pass. AI-generated images are uploaded, shared, indexed and may be folded into future training sets. When models train on material produced by earlier models, their outputs narrow over time. The rare colors are the first to go.

These images do not stay inside the machine. They can fill social media feeds and image searches until they stand in for the thing itself. The simulated green becomes the green you meet first.

Watching for the gap

Day after day, screens show you only the colors inside their range, translating anything outside that range into colors they can display. If you only ever see the beetle wing as a dull image, nothing tells you a brighter one ever existed. It will just look dull. If every picture of a plant arrives with its greens muted into the same screen-safe range, that range becomes green. You will not miss the absent colors.

One way to observe the gap is to find something vividly colored: a ripe persimmon, a peacock feather, the orange-pink at the bottom of the desert sky. Look at it before you photograph it. Stay with it. Stand close. Give it a name, even a private one. Then photograph it. Hold the image next to the thing. That distance is the gap.

The wild colors have not been erased. They have been excluded from the screen’s territory. The version that travels is what gets remembered. The thing is still there. Look for it.

Douglas Goodwin, Lecturer in Design and Media Arts, University of California, Los Angeles; California Institute of the Arts

This article is republished from The Conversation under a Creative Commons license. Read the original article.

Reviewed by Irfan Ahmad.

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by External Contributor via Digital Information World

Internet Traffic Is Surging Worldwide

By Tristan Gaudiaut, Statista

Global internet traffic has surged in recent years, more than doubling between 2020 and 2025 as digital services, streaming and cloud computing continue to expand worldwide. According to data from the International Telecommunication Union (ITU), total traffic volumes have increased sharply across both fixed (landline) and mobile networks.

As our chart shows, landline traffic remains by far the dominant channel, rising from around 3,100 exabytes in 2020 to 7,300 exabytes in 2025. Mobile data usage has also grown rapidly, climbing from about 560 to 1,500 exabytes over the same period. In both cases, Asia-Pacific accounts for the largest share, at 50 to 60 percent, with traffic more than doubling across fixed networks and reaching over 900 exabytes on mobile alone.

Other regions have followed a similar upward trajectory, albeit at lower levels. The Americas and Europe remain the second- and third-largest markets, while regions such as Africa and the Arab States have recorded particularly strong relative growth, reflecting rising connectivity and smartphone adoption.

Overall, the data highlights the accelerating scale of global data consumption, with fixed networks continuing to carry the bulk of traffic even as mobile usage expands rapidly. With one exabyte equivalent to one billion gigabytes, which is roughly equivalent to the storage capacity of about 8 million 128GB smartphones, the figures underscore the massive and growing infrastructure demands of the digital economy.

This post was originally published on Statista and republished here with permission.

Reviewed by Irfan Ahmad.

Read next:

• Three ways to avoid being fooled by AI slop

• Bad Bots Are Taking Over the Web
by External Contributor via Digital Information World

Three ways to avoid being fooled by AI slop

Silvia Montaña-Niño, The University of Melbourne and T.J. Thomson, RMIT University

Image: Marten Newhall/Unsplash

Global society makes billions of images and uploads hundreds of thousands of hours of video on the internet every day.

The problem is, some of this content is misleading or downright wrong. And when it’s in visual form, it can be particularly convincing.

Take the Met Gala that happened earlier this month in New York. While photographers snapped photos of Rhianna, Beyoncé and Nicole Kidman as they strutted their stuff, others saw “photos” of celebrities, such as Rosalía, Lady Gaga and Jacob Elordi, who were actually elsewhere (the images in the below Instagram carousel are AI generated).

While this type of AI slop might seem harmless and can be easily verified, other “media fakery” is becoming far more problematic and demands more robust techniques to verify.

Traditional verification techniques are falling short as AI becomes increasingly convincing and the line between authentic and synthetic blurs. This is true across all content, from still images to moving ones and audio deepfakes.

The volume of content and the speed at which it travels doesn’t help. It also doesn’t help that fact-checking can take hours or days while fakes can be created in seconds.

First, equip yourself

Guides on detecting AI-generated content suggest multiple strategies and acknowledge there are no perfect solutions. But there are helpful things you can do.

Familiarise yourself with examples of fakes and study how they were fact-checked. This helps you understand what is possible and learn how fact-checkers sort real from fake.

Look deeply. Zoom in. Pause the content or watch it frame-by-frame. Inspect the small details. Look out for inconsistencies, textures that are flat when they shouldn’t be, or patterns that are too perfect or are inexplicably off. Does the location shown match with where the scene is purported to be? Do shadows fall naturally and do lines follow the rules of perspective?

Look widely. Are you familiar with the source? What else does it publish and how long has it been around? What do other trusted sources say? How does this depiction compare to others that are available? Or if there aren’t others available, should that give you pause?

Then, apply your learnings

Let’s take an example and work through it together.

This Facebook reel, posted by an account called “Real Talk Hub”, purports to show migrants being stopped and returned by Australian police at an airport.

Before getting too granular, let’s take stock of the opening image.

The video uses scale to show what appears to be a long stream of passengers. Some are moving toward and some are moving away from a plane. It is difficult to identify specifics in the video. The superimposed text blocks almost all of the horizon line. Shallow depth of field makes aspects in the distance blurry and hard to discern.

Many of the passengers have darker skin and are visually coded as “other”. They interact with a light-skinned police officer who takes notes on a clipboard.

The vertical video is framed carefully to not reveal identifiers like the name of the airline that seems to start with the letter “P”. This makes it difficult to search the airline’s name and whether credible sources corroborate the story that’s told.

Even though the people and scenes look realistic at first glance, the video’s integrity unravels when we slow down and look closer. People in the passenger line morph and transform.

The officer is able to single-handedly remove the paper from the clipboard and it appears to inexplicably leave white strips behind. The police vests look different to images you can find in verified media photos of the Australian Federal Police.

Taken together, all these clues suggest the video is AI-generated.

The paper on the clipboard moves in an unrealistic way, and the police vest is not accurate. Real Talk Hub/Facebook

Think like a fact-checker

Many AI-generated videos can trick you and create a very compelling narrative. So, fact-checkers have developed triangulated methodologies that examine elements beyond just what you see in the video.

One way to do this is to systematically check contextual factors – the other things surrounding the content. Our team’s research has found professional fact-checkers usually pay attention to the type of social media accounts or websites distributing suspicious media.

For this AAP verification on a video about banning dogs on the beach, it was crucial to inspect the user’s activity and posting patterns.

In addition to visual anomalies, the fact-checkers also found an invisible watermark that helped them determine the content was AI-generated.

Other things to check are how long a social media account has been operating, how often the social media account posts, and whether the account is transparent about its use of AI.

These aren’t fool-proof indicators of authenticity, though. The migrant example above comes from an account that is about five years old. It also comes from a “verified” account, which might make it feel more credible. But both Facebook and X now let users pay for this verification.

Overall, when it comes to suspect images or video, don’t just look deeply. Also look widely.

AI-generated content can increasingly fool our eyes, so you also have to look beyond what’s in the video. Taking a mixed-methods approach that considers visual and contextual clues can help. By training your ability to think like a fact-checker, you can stay safer online.

Silvia Montaña-Niño, Lecturer, Centre for Advancing Journalism, The University of Melbourne and T.J. Thomson, Associate Professor of Visual Communication & Digital Media, RMIT University

This article is republished from The Conversation under a Creative Commons license. Read the original article.

Reviewed by Irfan Ahmad.

Read next:

• Google’s AI Search Has Struggled With One Religious Question for Years

• Bad Bots Are Taking Over the Web

by External Contributor via Digital Information World

Bad Bots Are Taking Over the Web

By Tristan Gaudiaut, Data Journalist Statista

More than half of global web traffic is now generated by bots, accounting for 53 percent in 2025. Within that, malicious bots alone make up 40 percent, nearly matching human activity at 47 percent, according to the Thales Bad Bot Report 2026. What was once a human-dominated internet has rapidly shifted toward automation. As our chart shows, the balance looked very different just a few years ago. In 2018, humans made up 62 percent of web traffic, compared with 20 percent for malicious bots and 18 percent for benign bots. Since then, malicious activity has doubled, while the share of benign bots has declined to 13 percent.

This rise in malicious bot activity reflects a growing cybersecurity challenge. Bad bots are increasingly used to steal login credentials, extract sensitive data, spread misinformation and manipulate digital advertising. Industries such as e-commerce, finance and social media remain particularly exposed, with bot-driven fraud costing businesses billions each year. Notably, roughly one in four attacks now targets APIs, allowing bots to bypass user interfaces and operate at high speed and scale. At the same time, the nature of automation itself is evolving. AI-driven bots and emerging AI agents are accelerating this shift, moving beyond simple scraping to interacting with websites, executing workflows and acting on behalf of users. In 2025 alone, AI-driven bot attacks surged by more than 12 times compared to the previous year, underscoring how quickly this threat is scaling.

However, not all bots are harmful. Benign bots, such as search engine crawlers and chatbots, remain essential for indexing the web and supporting digital services. Nevertheless, their declining share highlights how quickly malicious automation is developing. As AI continues to advance, the growing dominance and sophistication of bots are set to remain a defining feature of the internet.

This post was originally published on Statista and republished under the Creative Commons License CC BY-ND 3.0.

Reviewed by Irfan Ahmad.

Read next:

• YouTube Says It Will Add More Visible AI Disclosure Labels and Automatically Label Some Undisclosed AI Content

• Google AI Keeps Treating a Contested Religious Question as Settled Fact
by External Contributor via Digital Information World

YouTube Says It Will Add More Visible AI Disclosure Labels and Automatically Label Some Undisclosed AI Content

In a May 27 post published by the YouTube Team, the company said that it is updating how disclosure labels appear on content created or altered with artificial intelligence tools and will begin automatically applying labels in some cases where creators do not disclose significant AI use.

The Google-owned video search engine explained that disclosure labels for “photorealistic and meaningfully AI altered or generated content” will move to more prominent positions for viewers. According to YouTube, labels on long-form videos will appear below the video player and above the description, while labels on Shorts will appear as overlays on the videos themselves.

Image: YT

The company said disclosures for “unrealistic, animated, or slightly altered” content will remain in expanded video descriptions.

YouTube also said that beginning in May 2026 it will roll out “new internal signals” to help identify AI-generated content. The company said that if a creator does not specify AI use and its systems detect “significant photorealistic AI use,” YouTube will automatically apply a label.

According to the company, creators who believe content was incorrectly identified will be able to update the disclosure status in YouTube Studio. However, YouTube said disclosures will remain permanent for content created using YouTube AI tools including Veo or Dream Screen, and for content containing C2PA metadata indicating the content was fully generative AI.

YouTube said disclosure labels will not affect recommendations or monetization eligibility.

The update reflects broader efforts by online platforms to identify AI-generated media more clearly as generative tools become more common. Supporters may view the changes as a transparency measure that could also help parents more quickly identify AI-generated or heavily AI-altered videos when children are watching online content. Critics, however, are likely to focus on the accuracy of automated detection systems and how disclosure policies will be applied in practice.

Reviewed by Irfan Ahmad.

Read next: Privacy isn’t dead – it’s just that tech companies have made it inconvenient
by AI Analysis via Digital Information World

Privacy isn’t dead – it’s just that tech companies have made it inconvenient

Sandra Matz, Columbia University

Image: Ono Kosuki - pexels

“You have zero privacy … Get over it,” Scott McNealy, then CEO of Sun Microsystems, declared in 1999.

What might have sounded like a bold claim at the turn of the millennium has turned into a self-fulfilling prophecy in today’s era of big data and artificial intelligence.

Computer algorithms – step-by-step instructions – can connect the digital breadcrumbs of your existence, including Google searches, browsing histories, social media posts, credit card records and GPS locations to paint an astonishingly accurate picture of your preferences, routines and inner mental life.

These profiles often describe people better than their closest friends and family might. Yours may even tell you something you don’t know about yourself.

And as McNealy said nearly three decades ago, many people seem to have given up on the idea of ever reclaiming their privacy. When was the last time you carefully read the terms and conditions of the products you’re using?

Why do so many people do so little to protect their privacy online? I’m a computational social scientist with a background in psychology and computer science and author of “Mindmasters: The Data-Driven Science of Predicting and Changing Human Behavior.”

In talking to my students as a business professor at Columbia University and giving public talks around the world over the past decade, I have come to realize that people often substitute the question of whether they care about their privacy with two simpler and misleading ones: Is sharing my data worth it? And am I worried about my data being out there?

These questions act as mental shortcuts. They seem reasonable, but can mask your true feelings and lead you to decisions that don’t serve your long-term interests.

The ‘it’s worth it’ fallacy

When I ask people whether they care about their online privacy, they often respond by listing the benefits they get from sharing their personal data: Google Maps navigation, Netflix recommendations, Uber rides.

These are fantastic perks, no doubt. But that’s answering a different question: Is sharing my personal data worth it?

Swapping these questions seems like a reasonable approach on the surface. People often assess value by how much it would hurt to give something up. For instance, I know that drinking five cups of coffee a day might not be great for my health, but I enjoy it too much to stop. Similarly, sharing personal data brings benefits you may be unwilling to give up.

But this substitution is problematic.

First, the upside of sharing data is typically obvious and immediate: If I share my GPS location, Google maps can tell me how to get from A to B. But the downside of sharing data is often far more nebulous and abstract. My GPS location, for example, can also reveal to anyone who collects or buys the data whether I might be at risk of depression. With the carrot in plain sight, and the stick hidden away, that’s hardly a fair battle.

Second, people’s attention naturally gravitates toward the few instances where data sharing benefits them. But those instances are the exception, not the rule. Much of your data is collected and used without any direct benefit to you at all.

Finally, even if the benefits were to outweigh the risks in a particular instance, that doesn’t mean you don’t care about privacy. Ideally, wouldn’t you prefer to enjoy these services while also maintaining a high level of privacy?

The ‘I have nothing to hide’ fallacy

A second common response is I don’t care because I have nothing to hide. This idea has been carefully nurtured by Big Tech: If you’re uncomfortable sharing your data, something must be wrong with you.

But that’s not true. Privacy isn’t about covering wrongdoing. It’s about maintaining control over your personal information and deciding how it is used.

You might not be worried about your data today, but that sense of safety can be fragile. Take history: In 1933, Germany was a democracy. In 1934, it wasn’t. Personal data, such as religious affiliation, included in the census, played a major role in enabling persecution during the Holocaust. Now imagine such regimes having access to today’s digital footprints.

That scenario may feel distant, but the principle is not. The 2022 overturning of Roe v. Wade – which had guaranteed a constitutional right to abortion for five decades – made privacy suddenly relevant for millions of American women, whose search histories, app usage and location data could suddenly be used against them.

No matter how safe you feel today, you cannot predict how your data will be used tomorrow.

When you trade privacy for convienence by giving an app access to your data, it’s import to know what you’re giving away – and who is sharing it.

Asking the right questions isn’t enough

Understanding the true value of privacy, and realizing that you care about protecting it more than you might have thought, is a necessary precursor to action. But personal motivation isn’t enough.

Managing your personal data in today’s world is time-consuming. It’s too much for even a very efficient and diligent person to read and decipher the legalese of all the terms and conditions they sign off on.

For the intention-action gap to close, the burden to protect privacy needs to shift away from individuals and toward systemic solutions. That means designing policies and technologies where the safe choice is the easy one, and where maintaining privacy doesn’t automatically mean giving up on convenience and better service. Privacy-by-design standards could include more restrictive default settings. Connected computers could process information without exchanging raw data by using decentralized networks such as federated learning. New forms of collective data governance such as data trusts could also help serve that function.

Because data is permanent but leadership is not, I believe that the real solution isn’t to expect people to outmaneuver the system that exploits them but to build one that is worthy of their trust.

Sandra Matz, Professor of Business, Columbia University

This article is republished from The Conversation under a Creative Commons license. Read the original article.

Reviewed by Irfan Ahmad.

Read next: AI is making journalistic language more repetitive and predictable – and it’s a problem for all of us

by External Contributor via Digital Information World

Which Countries Have The Most Data Centers?

By Anna Fleck, Data Journalist Statista

A data center is generally defined as a building or group of buildings used to house computer systems, particularly components for telecommunications and storage. In the age of Big Data, such data centers have become indispensable forms of infrastructure and represent strategic challenges for governments.

The Cloudscene platform currently lists more than 11,700 data centers as being operational worldwide. But where are they located? According to the site, the United States dominates the market with 5,427 data centers listed there as of May 2026, accounting for 46 percent of the global total. It is followed by Germany (529), the United Kingdom (523), China (449) and Canada (337). With 155 data centers listed as of May, India ranks 14th worldwide.

This statistic provides a snapshot of the distribution of data centers around the world. It is important to note though that it does not show the size of such data centers, which is important as some may have much higher storage capacities than others.

This article was originally published by Statista under a Creative Commons License (CC BY-ND 3.0) and is republished here with permission.

Reviewed by Irfan Ahmad.

Read next: Why 40 per cent of people are avoiding the news, according to a psychologist
by External Contributor via Digital Information World

Why 40 per cent of people are avoiding the news, according to a psychologist

Ali Jasemi, Wilfrid Laurier University

Image: Anna Keibalo - Unsplash

During several recent conversations, people have told me that they’ve stopped checking their phones in the morning. Not because nothing was happening, but because everything was. They described the feeling as standing under a waterfall of perpetual bad news.

This experience is far from an isolated one. According to Reuters Institute’s 2025 Digital News Report, 69 per cent of Canadians at least occasionally avoid the news now.

Globally, 40 per cent report they at least sometimes or often do the same, the highest figure ever recorded. People shared consistent reasons for this: the news put them in a bad mood, they felt overwhelmed and powerless to act.

As a researcher in developmental psychology, focusing on social development and psychological well-being, I argue that news fatigue is not laziness, weakness or a generational decline in civic interest. It’s the predictable response of a human brain meeting an environment it was never designed to navigate.

Wired for bad news

Long before smartphones or even the printing press, our cognitive architecture was shaped by a single problem: stay alive long enough to reproduce. Our ancestors whose attention drifted past the rustle in the grass left fewer descendants than those who froze, looked and listened.

The brain that paid attention to threats was the brain that survived.

This is the foundation of what psychologists call the negativity bias, one of the most replicated findings in cognitive science. Across decades of research, the human mind has been shown to weigh negative information more heavily than positive, attend to it faster and remember it longer.

A predator nearby mattered more than a beautiful sunset. The cost of missing a real threat was death, while the cost of overreacting was a few minutes of wasted vigilance. The asymmetry made this bias adaptive.

Here is the problem: the human brain has not changed since then. We are the same species as we were thousands of years ago. What’s changed is the size of the world it’s asked to scan for threats.

Scanning the whole world

For most of human history, the threats our nervous system processed were local. A neighbouring tribe. A drought. The illness of a child we personally knew. Information about distant places would barely arrive, and if it did, it was mainly irrelevant.

In 2026, the same neurological system is being asked to absorb a war in one region, a financial shock in another, a climate disaster in a third and a violent crime in a fourth, all before lunchtime.

A study published in the scientific journal Nature Human Behaviour examined more than 105,000 real news headlines viewed nearly six million times. Each additional negative word increased click-through rates, while positive words had the opposite effect.

Recent studies suggest people around the world demonstrate measurably stronger physiological responses to negative news than to positive news. The body is reacting before the mind has decided whether the threat is relevant.

Some researchers have introduced a clinical framework for what happens in this instance called Problematic News Consumption (PNC) — a pattern of news engagement that results in preoccupation, dysregulation and disruption to daily functioning. In their 2022 study, the researchers found that 17 per cent of American adults qualified as having severe levels of PNC. Among that group, 61 per cent reported feeling unwell quite a bit or very much, compared with six per cent of those who didn’t.

For minority populations, news fatigue may be even more consequential.

Repeatedly witnessing harm directed at our own groups, even when we’re not the immediate target, can have a significant psychological impact on people from the same group affiliation. For racialized communities, such as immigrants, the cognitive load could be even heavier, and the option to simply stop watching is much harder to exercise when the news is about their country of origin.

Looking away is not the fix

What’s the solution to news fatigue? Well, it’s not avoidance. A democracy depends on informed citizens.

Many adults already cite the spread of misleading information as a major source of stress. Withdrawing from accurate, trustworthy information only deepens the problem. We’re wired to pay more attention to bad news, and that kind of content will find its way to us one way or another.

The fix is to manage the consumption and the sources.

Several approaches can help manage news fatigue and protect mental health. Containing news consumption to defined windows of time reduces the sense of being overwhelmed. Choosing depth over volume also matters: one carefully reported long-form article will inform you better than bursts of random, unreliable and emotionally loaded posts on Instagram.

There is also value in distinguishing between information and action — research on perceived control and stress consistently shows that the gap between awareness and agency is one of the strongest predictors of psychological distress. Identifying what you can actually do about what you read in the news, however small, regulates that response.

Finally, be wary of “rage bait” — intentionally provocative messages or content designed to boost engagement on social media platforms by eliciting negative reactions. Recognizing that certain content creators want to provoke rather than reflect reality creates useful cognitive distance.

The news will not become less “heavy.” But our relationship with it can become more deliberate. Our brains were not built for this scale of input. They were, however, built to learn to adapt.

Ali Jasemi, Lecturer, Psychology, Wilfrid Laurier University

This article is republished from The Conversation under a Creative Commons license. Read the original article.

Reviewed by Irfan Ahmad.

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by External Contributor via Digital Information World

Why people share live locations and how it changes modern communication

By Marianne Stein, ACES NEWS

Image: Ron Lach - Pexels

Mobile apps that allow people to share their location with others have become increasingly popular. But how and why do we use these apps, and what are the implications for interpersonal communication? That’s the topic of a new study from the University of Illinois Urbana-Champaign.

“I was teaching a class on relationship development to undergraduate students, and I made a comment about location sharing. They all got very animated, sharing experiences and asking questions about use cases. I realized there was very little research about this topic, so I decided to conduct a study,” said lead author Brian Ogolsky, professor in the Department of Human Development and Family Studies at U. of I.

“I believe knowing how people use these technologies helps us to understand the scripts and the processes that underpin relationships, how they are changing, and what that means for how we relate to each other.”

Ogolsky and his colleagues conducted an online survey with individuals across the U.S. and the U.K., asking them to describe their location sharing practices.

Respondents on average shared their location with 3.86 people, with a span ranging from 1 to 83. The majority reported using the Find My app for iPhone, followed by Google Maps, Life360, Snapchat, and WhatsApp.

People most often shared their location with their romantic partner, then friends, siblings, parents, children, other family members, and roommates.

The researchers organized the reasons people were sharing their location into four main categories: safety, practicality, casual use, and relationship processes.

Safety was the main reason for sharing location with immediate family, parents, and children.

“Respondents said it helps them feel safer knowing where someone is. That’s unsurprising; however, it’s really an illusion of safety. Knowing where my partner is 50 miles from here does not mean I can help them in a pinch, or that I can get somebody to help them. It may be more about peace of mind than actual safety,” Ogolsky said.

For romantic partners and friends, practicality was the most common reason for sharing. That included convenience and planning, such as what time to make dinner, or coordinating who picks up the kids. Respondents also mentioned keeping track of people who are traveling, or interacting with others who live or work in different places.

Casual use included sharing location for fun and novelty. Some respondents said it seemed interesting or entertaining, and there was no specific intent. For example, they would share location with everyone in their friend group and then forget about it.

Finally, the researchers identified relationship processes as a separate category, indicating usage specifically intended to maintain, support, and manage a relationship. This could be about trust, honesty, and open communication. A few people also mentioned pressure or expectations from their partner or family members about their roles and responsibilities.

Ogolsky pointed out there are potential drawbacks when technology replaces human interaction.

“Our findings highlight we’re heading towards a world where technological changes will dictate how and when we communicate. Location sharing is moving from primarily safety-related causes into the relationship realm, where it alters communication,” he said.

“You can check where someone is and decide you don’t want to bother them, so you don’t call or text. It takes away the ability of the person to say whether they would like to talk right now, and removes interpersonal negotiation.”

People come to depend on technology; for example, if you plan to meet someone at a concert and your phone dies, you may not be able to find each other. Location sharing with friend groups can also create a sense of FOMO, the fear of missing out, if you notice other people getting together without you.

Giving others access to your location also raises privacy concerns. However, this appears to be less important to younger generations who have grown up in a world where they have been surveilled by tech companies since they were born. Their idea of what should be private information is fundamentally different than older generations, Ogolsky noted.

There are also implications regarding whether location sharing information can be used as evidence in criminal court cases, and it can be misused in abusive relationships.

Ultimately, most people adopt a new technology because they think it's going to make their lives easier.

“There is something to be said for streamlining the minutia of relationships. A lot of people do not like planning; they do not like waiting. With location sharing, they can get information about others without intruding, they can be where they need to be at the right times. If they can squeeze in one more thing, that can be a real benefit for some people,” Ogolsky concluded.

The study, “Near, Far, Wherever You Are: With Whom and Why Do People Use Location Sharing in Relationships,” is published in the Journal of Social and Personal Relationships [DOI: 10.1177/02654075261446344]. This research was supported by Hatch funding from USDA’s National Institute of Food and Agriculture.

This article was originally published by the University of Illinois Urbana-Champaign, ACES NEWS and republished here with permission.

Reviewed by Irfan Ahmad.

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by External Contributor via Digital Information World

Pope Leo warns of AI’s risks to humanity in his first encyclical

Niusha Shafiabady, Australian Catholic University; Darius von Guttner Sporzynski, Australian Catholic University, and Sandie Cornish, Australian Catholic University

Image: AI-assisted, generated for illustrative purposes by DIW

Pope Leo XIV has just declared artificial intelligence one of the defining moral challenges of our time, in his first encyclical: a formal letter intended to guide moral, social and theological thought. Titled Magnifica Humanitas (Magnificent Humanity), it argues technology must serve humanity, rather than concentrate power or weaken human dignity.

He presented it at the Vatican alongside AI developer Christopher Olah, cofounder of Anthropic, who acknowledged that companies like his need moral guidance to guard against “incentives and constraints that can sometimes conflict with doing the right thing”, the New York Times reported.

“Technology is not simply a tool,” read the roughly 42,300-word open letter. “When it becomes the standard by which everything is judged, it begins to dictate what matters and what can be discarded, reducing creation to an object of exploitation and human beings to mere cogs in a system driven toward ever greater efficiency.”

It warns that AI is never truly neutral, but “takes on the characteristics of those who devise, finance, regulate and use it”. And it calls for ethical oversight, social justice, protection of workers, responsible governance and peace.

Automated warfare

The encyclical criticises the use of AI in warfare, calling for imposing the “most rigorous ethical constraints” on weapons developed using AI.

As governments invest heavily in autonomous military technologies and AI-assisted defence systems, the “growing ease” of deploying them makes war more likely and “less subject to human control”, it warns. This “violates the principle that armed force should be used only as a last resort in cases of legitimate self-defense”.

The letter also criticises the growing concentration of technological power, and systems that reduce people to data or economic functions. It promotes what it calls a “civilisation of love”, centred on human dignity, solidarity, truth, compassion and the common good.

Pope Leo’s response to the the AI revolution deliberately references his predecessor Pope Leo XIII’s response to the problems of the Industrial Revolution, Rerum Novarum (“Of New Things”), in 1891. Though Magnifica Humanitas was released on May 25 2026, it is symbolically dated May 15, the date of Rerum Novarum.

Industrial Revolution to AI Revolution

An encyclical is not an ordinary papal statement. Traditionally addressed to bishops and the wider Catholic world, it is one of the Catholic church’s most authoritative teaching documents.

The pope no longer has the direct political power the papacy held in the 19th century. But papal teaching still carries moral weight across a global Catholic network of schools, universities, charities, hospitals and community organisations.

The Vatican cannot regulate AI. It cannot write safety standards, police data centres, or force companies to disclose how their systems work. But it can help shape the moral terms of the debate. For more than a century, Catholic social teaching has influenced public arguments about work, inequality, poverty, human dignity and the ethical limits of economic power.

Although popes issued encyclicals long before the modern era, Rerum Novarum made social encyclicals globally influential.

It confronted exploitative labour conditions, widening inequality, and conflict between workers and employers. Pope Leo XIII defended workers’ rights and argued that wealth carried social responsibilities. He criticised both unrestricted capitalism and revolutionary socialism.

The document influenced debates about labour rights and economic justice well beyond the church. In Australia in 1907, Justice H.B. Higgins drew on Rerum Novarum when establishing principles for a fair living wage.

Pope Leo XIV’s encyclical attempts to do for the AI age what Rerum Novarum did for the industrial age: provide a moral framework for a technological transformation reshaping work, power and human relationships.

Human dignity in the age of algorithms

Pope Leo XIV argues human rights are not granted by governments or corporations: they arise from the intrinsic dignity of every person. Technologies should serve humanity rather than reduce people to data, economic units or optimisation problems.

He builds on Pope Francis’ critique of “the tendency to let the logic of efficiency, control and profit alone shape personal, social and economic decisions”, in his 2015 encyclical. It, too, warned of the risks of technology.

Pope Leo XIV argues moral responsibility can’t be transferred to automated systems, regardless of how sophisticated they become. He also rejects transhumanist ideas that human limitations should be technologically overcome, arguing vulnerability, dependence and imperfection are essential to being human. Relationships, care, solidarity and compassion are not weaknesses. “Humanity flourishes not despite limitations, but often through them.”

Running throughout the encyclical is a contrast between a “culture of power” and a “civilization of love”. One treats technology primarily as a tool for domination and control. The other places human dignity, justice and care at the centre of social life.

Why this matters

The significance of Magnifica Humanitas lies in its ability to shape public conversation and moral imagination. Moral frameworks matter. They influence what societies fear, what they tolerate, what they defend – and what they refuse to sacrifice.

Governments are investing in AI capability while still developing frameworks for transparency, accountability and safe deployment. Businesses are adopting AI tools at speed. Schools and universities are rethinking assessment, authorship and learning. Workers are being asked to adapt to systems they did not design and often cannot challenge. And citizens are increasingly governed, assessed and targeted by automated systems they may never see.

Pope Leo XIV’s intervention reminds us the central question is not whether AI will be powerful: it already is. The question is whether that power will be made answerable to human dignity.

The future of AI will not just be decided in laboratories, boardrooms or parliaments. It will also be decided by the moral limits societies are willing to set. Pope Leo XIV’s encyclical is an attempt to draw those limits.

Niusha Shafiabady, Professor in Computational Intelligence, Australian Catholic University; Darius von Guttner Sporzynski, Professor of History, Australian Catholic University, and Sandie Cornish, Senior Lecturer, Theology, Australian Catholic University

This article is republished from The Conversation under a Creative Commons license. Read the original article.

Reviewed by Irfan Ahmad.

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by External Contributor via Digital Information World

YouTube’s Ad-blocker Crackdown Has Users Searching For Alternatives

By Derick Migliacci, AllAboutCookies

YouTube adopted its premium model in 2018, alongside its YouTube Music subscription service. This has led to more ad-supported content on the platform, which has increased over the years. Many users, for the better part of the first 5 years of the service, had been able to use ad-blocking software to skirt the advertisements and still watch their favorite online content.

That changed in 2023 when YouTube started cracking down hard on ads in an attempt to get more users to subscribe to their premium service. The platform began using pop-ups warning users that ad-blocking software violated the site’s terms of service and would prevent users from watching videos until they either set their ad blocker to allow ads on YouTube or fully uninstall the blocker.

This change upset users, and they were in search of an alternative. The digital security site All About Cookies noticed a change in users' online behavior since then.

A Huge spike in Ad-block interest

According to their analysis, there was a +336% increase in traffic for users searching for an ad-blocker that can bypass YouTube’s restrictions following the YouTube crackdown in October of 2023.

With the timing of this surge positioned right at the beginning of the ad crackdown, it’s highly likely that YouTube’s stance on ads changing was a direct result of this traffic, showing that users felt very strongly about the changes being implemented on the platform.

Most Users Would Not Pay for Ad-Free YouTube

Another indication of users’ strong negative feelings about the changes YouTube has made regarding ads can be seen in the survey, All About Cookies, conducted. In this survey, they asked users if they would pay for an ad-free version of YouTube known as YouTube Premium, 52% of whom said they would not, even with a heightened emphasis on ads.

Another surprising result is that 75% of users would be willing to pay the actual cost of the lowest tier of ad-free YouTube. YouTube Premium Lite, which includes ad-free viewing on non-music and shorts content, the ability to play videos in the background, and the ability to download videos offline, is $8.99. This does not give you the full ad-free premium experience on YouTube, as that costs $15.99.

According to this data, only 11% of users would be willing to pay what it costs for a full ad-free YouTube experience.

Over Half of Users Plan to Look for Alternatives or Find a Way Around YouTube’s Crackdown

Another question revolved around asking users how the crackdown changed the way they used the platform. The results showed that a majority of respondents planned to find alternatives or ways around the ad-blocker crackdown, as opposed to YouTube’s intended response of paying for a premium subscription.

While 23% users responded and said they would be less likely to use an ad-blocker or more likely to pay for a premium subscription, 53% of respondents plan to use their time to be spiteful and find a way around YouTube’s ad-block ban, look for alternatives, or straight up spend less time on the site.

44% of respondents said this crackdown would not affect their YouTube consumption.

It surely seems that most users’ response to YouTube’s attempt to get more users to watch ads or pay up was not met with the desired response. While around half of users do plan to adhere to the ban, a majority are looking the other way when it comes to watching content online.

More users (16%) claimed they are planning to spend less time on the site than users who said they were more likely to pay for YouTube Premium (12%).

Final Thoughts

This data shows that YouTube’s crackdown on ad blockers still has users upset with the changes they implemented in 2023. A huge increase in traffic on a site such as All About Cookies, searching for alternatives to ad-blockers not banned by YouTube, matches with a user survey where a majority claim they will not adhere to the site's demands of “watch our ads or pay up.”

YouTube has gone the way of traditional streaming services and created a subscription-based way to watch content online, which many users feel is unfair because YouTube is primarily defined by user-generated content. The site has undoubtedly evolved since its inception over 20 years ago, with many controversial changes, such as introducing ads in the first place. However, it seems that this change has angered users more than ever, as they potentially look for new alternatives or ways around the change in strategy. Even three years after the initial crackdown, users are still scorned by the platform, and with new price hikes for premium subscriptions, many more users who were willing to pay may not be anymore

Author Info: Derick Migliacci is a Digital PR Strategist for AllAboutCookies. He brings over 3 years of experience in the PR world as well as a passion for digital trends, cybersecurity, and technology.

Reviewed by Irfan Ahmad.

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by Guest Contributor via Digital Information World