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.

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• 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.

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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.

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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.

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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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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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