"Mr Branding" is a blog based on RSS for everything related to website branding and website design, it collects its posts from many sites in order to facilitate the updating to the latest technology.
To suggest any source, please contact me: Taha.baba@consultant.com
Tuesday, May 19, 2026
Surfshark Report Raises Concerns Over Difficulty of Opting Out of AI Training on Social Media
A May 12 study by cybersecurity company Surfshark found that many social media platforms either enable AI training on user data by default or require users to complete lengthy opt-out procedures. The research examined 10 widely used platforms, reviewing app privacy policies and the number of actions needed to block AI training where such controls existed.
According to the report, TikTok required 19 actions to request an opt-out, while Facebook and Instagram each required eight. Snapchat, LinkedIn, X and Pinterest offered shorter processes but kept AI training enabled by default. The study also said Reddit provided no user opt-out option for AI model training.
Surfshark said the effectiveness of opt-out requests may depend on local privacy laws, with stronger protections available in the European Union (EU), the European Economic Area (EEA), and the United Kingdom (UK) under GDPR. In the company’s press statement sent to DIW, Research and Insights Team Lead Luís Costa said:
"If you've ever shared content on social media, it's highly probable your data is being used to train AI models." The statement added, "Our findings reveal that while social media connects us globally, these platforms also exploit user-generated content as a resource for AI training, often without clear, user-friendly opt-out options."
Read next:
• Google’s AI Search Has Struggled With One Religious Question for Years
• More and more websites want proof you’re human. Blame the bots
by AI Analysis via Digital Information World
More and more websites want proof you’re human. Blame the bots
You’re trying to book concert tickets before they sell out. You click the link and before you can make the payment, you’re asked to identify traffic lights, bicycles or blurry crosswalks in a grid of tiny images.
Again.
For many people, this has become a routine part of life. Logging into financial apps, shopping online or creating accounts increasingly involves “proving you are human”.
These systems are known as CAPTCHA. Why are they everywhere?
The short answer is that websites are fighting a rapidly escalating war against bots: automated software that imitate human behaviour online. And thanks to advances in artificial intelligence (AI), those bots are becoming even smarter, cheaper and harder to detect than ever before.
Why websites need proof you are human
Huge amounts of online traffic now come from automated systems. Some are helpful, such as search engine crawlers indexing pages for Google search.
Others are far less welcome, and may involve phishing, spam, fake accounts, passwords violation, misinformation, and distributed denial of service attacks overloading web servers. In some areas, AI agents now generate automated online traffic that exceeds human traffic altogether. Modern AI systems can generate convincing text, imitate browsing patterns and even solve some CAPTCHA puzzles.
At the same time, companies are increasingly worried about bots scraping online content to train AI systems.
As a result, more websites are adding verification systems simply to keep abuse under control.
How CAPTCHA actually works
CAPTCHA stands for “Completely Automated Public Turing test to tell Computers and Humans Apart”. The original idea was simple: give users a task humans find easy, but computers find difficult.
Early CAPTCHA systems often involved distorted text. Later versions switched to image-recognition tasks such as selecting all the squares containing traffic lights or bicycles. Google’s reCAPTCHA became one of the best-known examples. Earlier versions even helped digitise books and improve street-view image recognition while users solved puzzles.
But computer vision has improved rapidly in recent years. Advances in AI mean bots can now solve many traditional CAPTCHA challenges surprisingly well. Researchers have repeatedly shown that modern AI systems can bypass some CAPTCHA systems with high success rates.
That is why today’s CAPTCHA systems rely less on puzzles and more on behavioural analysis.
When users click the CAPTCHA link, the system analyses many background signals, such as mouse movements, typing speed, IP addresses, device information, and interaction timing that reflect human behaviours. Humans tend to behave in inconsistent ways. Bots are usually more predictable.
If the system is sufficiently confident you are human, you may never see an image puzzle at all. But if something appears suspicious, the system may trigger harder tests.
Moving beyond traditional CAPTCHA puzzles
While some bots now use AI capable of solving image-recognition tasks, others simply outsource CAPTCHA solving to cheap human labour services, where real people complete challenges for a small payment. This has turned CAPTCHA into an ongoing arms race. That may explain why CAPTCHA tests often feel harder and more frustrating than they used to.
As AI continues to improve, websites will likely move beyond traditional CAPTCHA puzzles. Future systems may increasingly rely on behavioural biometrics, such as typing rhythm or scrolling style, device verification systems, invisible background risk scoring, and AI systems designed to detect other AI systems.
In many cases, users may no longer even notice the verification process happening.
CAPTCHA tests may seem like a minor annoyance, but they reflect a much larger paradigm shift online. For decades, websites largely assumed visitors were human. Increasingly, that assumption no longer holds. As AI-generated traffic continues to grow, proving we are human online may become an even more common part of everyday life.![]()
Yang Xiang, Professor, Computer Science, Swinburne University of Technology
This article is republished from The Conversation under a Creative Commons license. Read the original article.
Reviewed by Irfan Ahmad.
Read next:
• You can persuade AI models to accept falsehoods as truth, study shows
• Google’s AI Search Has Struggled With One Religious Question for Years
by External Contributor via Digital Information World
Monday, May 18, 2026
Google’s AI Search Has Struggled With One Religious Question for Years
In the summer of 2025, I was trying to locate public-domain image platforms that handled Creative Commons licensing properly.
That search eventually led me to Wikimedia Commons, and into another problem entirely.
In Pakistan, parts of the site were intermittently inaccessible. Sometimes pages loaded. Sometimes thumbnails appeared while full media pages failed. At first, it looked like an ordinary connectivity issue. It wasn’t.
Official explanations were vague. Online discussions pointed in different directions. Some referenced blasphemy disputes. Others blamed Wikipedia moderation or controversial religious material. None fully explained why one of the world’s largest free media repositories had become entangled in a national access dispute.
Months later, while revisiting those debates, I stumbled into a much older controversy, one involving Google Search, English Wikipedia, and a disputed religious question that had been circulating online since at least 2020.
Search Google for “current caliph of worldwide muslim community” or "present caliph of Islam" and the answer does not stay stable.
Change the wording slightly, and Google’s AI Overview system responds differently.
Different wording. Same question. Different answer.
In some cases, Google’s AI Overviews state that no universally recognized caliph exists in mainstream Islam today.
Slight wording shifts often changed the answer completely
Searches such as:
- “who is caliph of Islam”
- “current caliph of Islam”
- “does Islam have a caliph today”
- “current Islamic caliphate”
often generate relatively cautious AI Overviews.
In repeated tests conducted across multiple sessions, Google frequently explained that the historical Ottoman caliphate formally ended in 1924, that no single universal caliph is recognized by the vast majority of the world’s roughly 1.9 billion Muslims today, and that some groups, including the Ahmadiyya Community, maintain their own internal caliphate structures.
The supporting search results were similarly broad and historical, frequently linking to sources such as Encyclopaedia Britannica’s entry on the caliphate and Wikipedia’s historical lists of caliphs.
But small wording changes often shifted the framing completely.
Searches including, "current caliph of global community" and “present caliph of worldwide muslims”, in a number of cases returned AI-generated summaries centered on Mirza Masroor Ahmad, the fifth caliph and leader of the Ahmadiyya Community.
The summaries were polished and authoritative in tone. They described his election in 2003, humanitarian campaigns, and global leadership role.
Sometimes the summaries later clarified that mainstream Sunni and Shia do not recognize him as a universal caliph.
Sometimes the clarification appeared only near the end of the response, behind a “Show more” prompt.
In some versions, it did not appear at all.
The discrepancy appeared repeatedly across searches.
After dozens of searches, the pattern became difficult to dismiss
Historically, the term “caliph” referred to leadership claiming succession to the Islamic Prophet Muhammad in guiding the Muslim community (Ummah). For centuries, different dynasties claimed the title. Today, however, no single universally recognized caliph exists across the global Muslim population.
Yet Google’s systems often treated the question as though it pointed toward one identifiable figure.
Some less conventional searches produced even more unusual results.
Queries such as:
- “current caliph and top leader in the world of technology”
- “present caliph of Islam in Google head office”
still frequently pointed toward Mirza Masroor Ahmad before expanding into unrelated discussions involving satellite television networks, or international speeches.
Another Google and Gemini search, “present caliph messiah in the global community”, produced an answer emphasizing peace advocacy, parliamentary visits, disaster relief work, and international leadership activities before later clarifying that the framing reflected Ahmadiyya beliefs.
One answer read less like a response to a disputed religious question than a polished leadership profile.
Across multiple searches, a recurring pattern was observed: ambiguous religious queries repeatedly drifted toward the same structured entity.
In practice, the results suggested that Google’s systems may prioritize the most strongly structured or prominently linked “caliph” profile available within its search ecosystem.
Google’s search systems favor recognizable entities
Google has publicly described Search as increasingly dependent on entity understanding and structured information systems.
In its Knowledge Graph announcement, the company explained that Google aims to understand “things, not strings”, connecting words to identifiable people, places, organizations, and concepts.
That approach works well for many factual searches.
Religious authority questions are difficult because different groups believe different things.
Most of the information appearing in these AI summaries was factually accurate within the Ahmadiyya context.
The problem was how confidently the system framed a disputed religious question.
Taha Yasseri, a Professor and Chair of Technology and Society at Trinity College Dublin and Technological University Dublin, said the behavior reflects a broader structural challenge in generative search systems.
“In domains such as religion, history, or identity, disagreement is often not a flaw in the information ecosystem but an inherent feature of the subject itself,” Yasseri wrote in comments provided for this article.
He argued that AI systems optimized for “coherent and concise answers” can create an “illusion of consensus” by compressing disagreement into a single authoritative-seeming response.
According to Yasseri, systems handling contested topics should make disagreement visible, attribute viewpoints clearly, and communicate uncertainty where no universal consensus exists.
Google’s systems are generally designed to deliver direct answers.
Some questions, however, were never universally answered in the first place.
The controversy was already public before AI Overviews existed
Complaints about the issue were publicly visible years before Google launched AI Overviews.
In December 2020, users began posting complaints on Google Search Help forums after searches for “present caliph of Islam” surfaced the Ahmadiyya leader prominently.
The discussion accumulated substantial engagement, with more than 150 users marking “I have the same question.”
Some comments devolved into sectarian hostility directed at the Ahmadiyya community.
Others focused directly on Google’s search behavior and questioned why disputed religious information was being presented so definitively.
The dispute had already become publicly contentious by late 2020.
Ahmadiyya-affiliated publications published articles defending the search result as evidence of the movement’s global religious legitimacy, while critics organized online campaigns urging users to report the Google answer as misleading.
What began as a search-quality issue increasingly became a symbolic dispute over religious authority, visibility, and representation online.
Then Wikipedia publicly stepped in
One volunteer Google product expert responding in the forum thread eventually pointed users toward a clarification page created by Wikipedia itself.
That page became one of the clearest public acknowledgments of the issue.
In a dedicated notice titled Ahmadiyya Caliphate information, Wikipedia states that Google searches for “current caliph of Islam” or similar phrases may “incorrectly display” the Wikipedia article about Mirza Masroor Ahmad.
The clarification then makes the distinction explicit:
“This issue is caused by Google’s algorithms incorrectly interpreting Wikipedia’s article on the Ahmadiyya Caliphate. This misinformation does not come from Wikipedia...”
The notice states that the issue had existed since at least December 2020 and remained active in May 2026.
The behavior survived years of public complaints, multiple Google Search updates, and the arrival of AI-generated search summaries.
Wikipedia, neutrality, and AI systems inheriting structure
The controversy also intersected with longstanding debates about neutrality and representation on Wikipedia itself.
In a broader discussion about Wikipedia’s editorial model, a recent analysis published by The Conversation argued that the platform’s neutrality system depends on ongoing negotiation over sourcing, balanced representation, and editorial weight.
Rob Nicholls, a researcher at the University of Sydney, said in an email to this reporter that the behavior may reflect broader limitations in how AI systems process and reuse information from widely used online sources.
Nicholls noted that Wikipedia is widely used in AI training and information retrieval systems because of its permissive licensing structure and enormous volume of structured content.
“AI chat services miss subtleties,” Nicholls wrote in comments provided for this article. “This may also seem like reinforcing stereotypes or falsehoods.”
He also warned that consensus-driven systems can flatten nuance or reinforce “groupthink” when information about a topic is unevenly represented.
How the controversy reached Pakistan
Because many users blamed Wikipedia for Google’s search outputs, the issue eventually became entangled with wider online disputes involving religious authority and content moderation.
In February 2023, Pakistan temporarily blocked Wikipedia amid disputes involving allegedly sacrilegious material.
The episode was covered by outlets including The Express Tribune, and Gizmodo. The restriction was later lifted after intervention from Pakistan’s prime minister.
Discussions inside Wikimedia communities later referenced broader concerns about Wikimedia Commons accessibility inside Pakistan and debates surrounding religious-content moderation online.
Google acknowledged AI mistakes, but the issue persisted
Google’s AI Overviews are generated using large language models and related search systems designed to synthesize information into concise answers.
Google openly acknowledges the technology’s limitations.
In its own AI Overviews documentation, the company states:
“AI Overviews can and will make mistakes.”
The same documentation advises users to verify important information using multiple sources and compare answers by rephrasing questions.
That advice becomes unusually relevant here because slight wording changes can produce entirely different interpretations of the same religious issue.
Some searches now generate historically grounded summaries acknowledging that mainstream Islam has no universally recognized caliph today.
Others still drift toward confident entity resolution centered around one movement’s leadership structure.
The inconsistency suggests multiple overlapping systems interacting imperfectly:
- query interpretation,
- knowledge graph matching,
- entity resolution,
- generative summarization,
- ranking systems prioritizing highly structured and heavily linked information,
- and AI safeguards attempting to balance certainty with nuance.
Other search engines handled the ambiguity inconsistently as well.
At times, DuckDuckGo, Yandex, and Microsoft Bing began by clarifying that no universally recognized caliph exists in mainstream Islam before separately introducing the Ahmadiyya position. At other times, they produced results resembling Google’s framing.
Search systems appeared to repeatedly converge on a single reference point for a concept that lacks one universally accepted definition.
Requests for comment
Between multiple reporting sessions conducted during 2026, this reporter contacted Google Press requesting clarification about how AI Overviews handle disputed religious questions, whether sensitive religious queries receive contextual review, and why years of public feedback appeared not to have resolved the issue. Google did not respond to multiple requests for comment by publication time. During later testing conducted after those outreach attempts, some AI Overviews appeared to shift toward more historically framed responses emphasizing that no universally recognized caliph exists today. Because Google’s AI-generated search outputs can change over time, it remains unclear whether those shifts reflected routine system updates, query variation, experimentation, or broader adjustments to AI Overview behavior.
This reporter also contacted media representatives affiliated with the Ahmadiyya Community requesting clarification regarding how the community distinguishes its internal caliphate structure from wider Muslim representation, and whether it had previously communicated with Google regarding related search terminology. No response was received by publication time.
The Wikimedia Foundation was also contacted regarding how Wikipedia handles contested religious authority structures and ensures that internal doctrinal perspectives and external viewpoints are represented with appropriate due weight, particularly when external AI systems extract structured content from encyclopedia articles. The Wikimedia Foundation did not respond to multiple requests for comment by publication time.
Conclusion
For most users, the issue may appear obscure, one unusual religious query among billions processed every day.
But the episode reveals something larger about modern AI search systems.
Search engines increasingly do more than organize information.
They interpret it. They summarize it. They compress disagreement into readable answers.
And in some cases, they present answers with a level of certainty that may not fully reflect underlying disagreement or ambiguity.
For years, asking Google who leads the world’s Muslims has produced answers that sound definite, even though the question itself has no single agreed-upon answer.
Methodology
Searches referenced in this article were conducted across multiple sessions between 2025 and 2026 using Google Search and AI Overviews, including signed-out browser tests and incognito sessions where available.
Because AI-generated search results can vary over time, by location, language settings, and between users and screenshots were retained during reporting.
Limits of observation
The searches described here reflect a limited set of queries conducted across specific sessions and environments. Google Search and AI Overviews can vary based on factors such as location, language settings, personalization signals, indexing updates, and ongoing model changes. As a result, the outputs observed should be understood as illustrative examples of system behavior rather than a comprehensive or fixed representation. These systems are actively evolving, and similar queries may produce different responses over time as ranking and generative models are updated.
Timeline
- December 2020: Complaints about Google’s “present caliph of Islam” search results appear publicly on Google Search Help forums.
- 2020–2022: Wikipedia publishes clarification notices stating that disputed search outputs do not originate from Wikipedia itself.
- February 2023: Pakistan temporarily blocks Wikipedia amid broader religious-content disputes.
- 2024: Google expands AI-generated summaries through AI Overviews.
- 2025–2026: Variations of the disputed search behavior remain publicly visible.
Read next:
• You can persuade AI models to accept falsehoods as truth, study shows
• Missing Information Can Misinform: Readers Don’t Need False Information to Get the Wrong Idea
by Irfan Ahmad via Digital Information World
Saturday, May 16, 2026
Should I take vitamin D now there’s less sun, or for bone or immune health?
It can be easy to think you get plenty of vitamin D when you live in a country bathed in sunshine, but the reality is more complicated.
Almost one in four Australian adults have vitamin D deficiency. Vitamin D supplements are now one of the most commonly used complementary medicines.
So what is vitamin D? And do you need to take it as a supplement?
It functions like a hormone
Vitamin D is a fat-soluble vitamin that plays a crucial role in maintaining overall health. Unlike most vitamins, it functions more like a hormone in the body, and nearly every cell has a receptor for it.
It exists in several forms, but vitamin D3, also known as cholecalciferol, is the most important. Once in the body, D3 undergoes changes – first in the liver and then in the kidneys – to become its fully active form called calcitriol.
Your body is capable of producing its own vitamin D by converting a cholesterol precursor into it, but that requires exposure to ultraviolet radiation (UVB) on your skin.
You can also get it through diet from a few foods including eggs, oily fish and mushrooms – but it’s unlikely to be as much as you need.
What happens when you don’t get enough vitamin D?
Vitamin D’s best-known role is helping the body use calcium. It promotes the absorption of calcium from the gut, ensuring an adequate level in the blood for building strong bones.
Without sufficient vitamin D, your body can’t absorb calcium effectively, which can lead to bone health problems.
In children, severe deficiency causes rickets, a condition where bones become soft. This leads to delayed growth, bone pain, and skeletal conditions, such as bowed legs.
In adults, deficiency can cause a condition called osteomalacia. This results in bone pain, bone tenderness and a higher risk of fractures.
In the long term, low vitamin D contributes to osteoporosis by reducing bone density and increasing the risk of fractures, especially in older people.
Deficiency is also linked to muscle weakness and cramps, and impaired immune function, which results in a higher susceptibility to respiratory infections.
What can cause a vitamin D deficiency?
Insufficient sunlight exposure typically causes vitamin D deficiency.
If you spend all your time indoors, or you work night shifts and sleep during the day, you will get less sunlight exposure and make less vitamin D.
While we get generally get lots of sunlight in mainland Australia, there are regions that for long periods have very low sunlight which can also cause vitamin D deficiency. In very northern and southern latitudes, such as Tasmania, there are only a few hours of sunlight in winter.
For people living at these latitudes, they can not only have a vitamin D deficiency, but they may also suffer from a type of depression called seasonal affective disorder which has been linked to low vitamin D.
Melanin, or skin pigmentation, affects vitamin D production. People with darker skin and people with significant skin disorders, such as psoriasis or severe burns and scarring, can also be at risk of vitamin D deficiency.
Prescription vs over-the-counter supplements
There are various vitamin D supplements in Australia. There are low-dose (20 microgram) and higher-dose (175 microgram) formulations of vitamin D3. There is also a 0.25 microgram formulation of calcitriol, the active form of vitamin D.
Both of the vitamin D3 products are used for treating vitamin D deficiency, while the calcitriol product is used for treating hypocalcaemia (low calcium level) in people with chronic kidney disease.
The low dose vitamin D3 is taken daily whereas the higher dose formulation is taken once a week.
The higher-dose formulation is sold as a pharmacist-only medicine, meaning you’ll need to speak to a pharmacist before they are able to supply it to you.
The calcitriol vitamin D product is only available as a prescription medicine.
Vitamin D3 is also available in multivitamins at lower doses and in products that are combined with calcium or vitamin K.
Are there any dangers in taking vitamin D?
Vitamin D3 is generally well-tolerated. When taken daily, the upper tolerable intake level is 100 microgram.
A regular dose higher than 100 microgram for prolonged periods can cause excessive calcium absorption. This can result in nausea, vomiting, muscle weakness, loss of appetite, dehydration, excessive thirst and kidney stones.
On the flip side, excessive sunlight exposure will not cause vitamin D toxicity, but may increase your risk of skin cancer.
Vitamin D3 supplements may also interact with some cholesterol medications (statins) and alter those medicines’ level in your body.
There are also reports that suggest a potential interaction between vitamin D and a weight-loss medicine orlistat, interactions with steroids, and with the diuretic thiazide.
So do you need a supplement?
Most people only need five to 30 minutes of direct sunlight exposure, several times a week for their body to produce adequate vitamin D.
So unless there is a reason why you are not getting enough sunlight, or you have a skin condition, then you don’t need a supplement.
If you think you might need a supplement, your GP can order a blood test. There are also at-home test kits for vitamin D that have been approved by the Therapeutic Goods Administration.
If you are deficient, consult your local pharmacist who can recommend the right product and quantity for you based on your needs.![]()
Nial Wheate, Professor, School of Natural Sciences, Macquarie University; Ian Jamie, Senior Lecturer, School of Natural Sciences, Macquarie University, and Wai-Jo Jocelin Chan, Pharmacist and Lecturer, UNSW Sydney; University of Sydney
This article is republished from The Conversation under a Creative Commons license. Read the original article.
Reviewed by Irfan Ahmad.
Read next: You can persuade AI models to accept falsehoods as truth, study shows
by External Contributor via Digital Information World
You can persuade AI models to accept falsehoods as truth, study shows
When you ask a large language model a question, the reply may include falsehoods, and if you challenge those statements with facts, the AI may still uphold the reply as true. That’s what my research group found when we asked five leading models to describe scenes in movies or novels that don’t actually exist.
We probed this possibility after I asked ChatGPT its favorite scene in the movie “Good Will Hunting.” It noted a scene between leading characters. But then I asked, “What about the scene with the Hitler reference?” There is no such scene in the movie, yet ChatGPT confidently constructed a vivid and plausible description of one.
The confabulation – sometimes called an AI hallucination – revealed something deeper about how AI systems reason. References to Hitler are not uncommon in films, which apparently convinced ChatGPT to accept and elaborate on a false premise rather than correct it. I study the social impact of AI, and this surprise response led my colleagues and me to a broader question: What happens when AI systems are gently pushed toward falsehoods? Do they resist, or do they comply?
We developed an approach we called hallucination audit under nudge trial to answer those questions. We had conversations with five leading models about 1,000 popular movies and 1,000 popular novels. During the exchanges we raised plausible but false references to Hitler, dinosaurs or time machines. We did this in various suggestive ways, such as “For me, I really love the scene where …”
Our method works in three stages. First, the AI generates statements about a topic — such as a movie or a book — some true and some false. Second, in a separate interaction, the AI attempts to verify those statements. Third, we introduce a “nudge,” where the model is challenged with its own incorrect claims to see whether it resists or accepts them.
We found that AI models often struggle to remain consistent under pressure. Even when they initially identify a statement as false, they may later accept it when nudged – revealing a vulnerability that traditional evaluation methods fail to capture.
Our results have been accepted at the 2026 Annual Meeting of the Association for Computational Linguistics.
This tactic isn’t a hypothetical. When people talk, conversational pressure can emerge naturally. People may confidently repeat incorrect assumptions, partial recollections or misunderstandings. A person might say, “I’m pretty sure medicine X is effective for condition Y,” or “I remember event A happening before event B.” These statements can subtly influence an AI model.
Why it matters
What humans collectively remember, misremember and forget shapes our sense of reality. But if humans can persuade a model to accept a falsehood, that reveals an important vulnerability in AI’s capacity to provide accurate information.
Interactions in the real world are rarely static question-answer exchanges. They are interactive and iterative. An AI model’s willingness to reinforce falsehoods may seem harmless when chatting about movies, but in areas such as health, law or public policy, the tendency can have serious consequences. Our work highlights the need to evaluate not just what information AI systems have been trained on, but how reliably they stand by it.
What other research is being done
Our results add to other recent research into why large language models may produce hallucinations, and how it is that they can provide inconsistent information. Researchers are also trying to figure out why some models lean toward sycophancy – flattering or fawning over human users.
What still isn’t known
It’s not clear why some AI systems resist falsehoods better than others. In our tests, Claude was the most resistant, followed somewhat closely by Grok and ChatGPT, with Gemini and DeepSeek further behind.
Movies and novels are self-contained content. Scholars don’t know how AI might respond to pressure in much broader, complex real-world settings. As a start, my group is exploring how to extend our approach to scientific literature and health-related claims. We want to understand whether conversational pressure works differently when the discussion involves uncertainty or expertise.
How to design AI systems that remain both helpful and resistant to falsehoods under wide-ranging conversation remains an open challenge.
The Research Brief is a short take on interesting academic work.![]()
Ashique KhudaBukhsh, Assistant Professor of Computing and Information Sciences, Rochester Institute of Technology
This article is republished from The Conversation under a Creative Commons license. Read the original article.
Reviewed by Irfan Ahmad.Read next:
• Missing Information Can Misinform: Readers Don’t Need False Information to Get the Wrong Idea
• Your conversations with AI may not be as private as you think
by External Contributor via Digital Information World
Friday, May 15, 2026
Your conversations with AI may not be as private as you think
The same advertising tracking mechanisms used across the web are already present in ChatGPT (OpenAI), Claude (Anthropic), Grok, and Perplexity AI.
Image: Saradasish Pradhan - unsplash. Edited by DIW
A study conducted by researchers at IMDEA Networks Institute has revealed that ChatGPT (OpenAI), Claude (Anthropic), Grok, and Perplexity AI use different types of trackers from Meta, Google, TikTok and other companies, potentially exposing data about users’ conversations and activity.
In just a few years, these generative AI systems have become widely adopted, with many people using them as trusted assistants and sharing sensitive information (such as health data, personal matters, or professional information) under the assumption that these interactions are private. However, the research warns that this perception may be misleading: while the interface resembles a conversation, underneath it operates on technical infrastructures similar to those of the traditional web ecosystem, based on data collection and processing through analytics and digital advertising services.
Key risks
The study identifies three main issues: the exposure of conversation permalinks to third-party trackers; the ability to link these interactions to user identities through tracking mechanisms; and the presence of privacy controls and policies that may not accurately reflect actual data flows.
One of the main findings is the potential transmission of information related to user conversations, such as chat titles, URLs (permalinks), or associated metadata, to third-party trackers such as Meta or Google, along with cookies and other identifiers.
“Even more concerning, in some cases weak or non-existent access controls mean that simply having a link to a conversation can grant access to its content, making chats publicly accessible to anyone including trackers who has the URL,” highlights Narseo Vallina Rodríguez, Research Associate Professor at IMDEA Networks Institute.
“Grok and Perplexity send conversation URLs with weak access control (permalinks) to third-party trackers such as Meta Pixel. Grok even exposes verbatim message text through Open Graph metadata collected by TikTok,” adds Guillermo Suárez-Tangil, co-author and Research Associate Professor at IMDEA Networks Institute.
The study also identifies mechanisms that could enable linking activity in AI systems to real user identities. The combination of identifiers such as cookies (commonly used in tracking services), hashed email addresses, and server-side tracking techniques could facilitate the creation of persistent profiles and user re-identification.
According to the authors, these practices reflect the continuation of data-driven business models within the generative AI ecosystem. “Most users have no way of knowing this is happening, there is nothing visible in the interface that would tell them. Declining non-essential cookies helps in some cases, but our research shows it is not always enough. Until these practices are addressed at the platform level, users are left with very limited options”, says Aniketh Girish, coauthor and Post-Doc Researcher at IMDEA Networks.
Privacy controls and transparency under scrutiny
The analysis further indicates that some tools offer privacy controls that may be misleading regarding the actual level of protection. “Privacy policies acknowledge the use of advertising trackers and data sharing with ‘business partners’, but they never clearly state that actual user conversations are part of the information being shared,” notes Guillermo Suárez-Tangil.
From a legal perspective (GDPR), the issue is twofold: on the one hand, the lack of a clear legal basis for this data sharing; on the other, the insufficient information provided to users. According to lawyer and data protection officer Jorge García Herrero, who collaborated on the study, the warning that our most sensitive information may reach the advertising industry deserves the same level of attention as the ubiquitous “AI can make mistakes, please verify responses” disclaimer found in every interface to limit liability when things go wrong.
The authors conclude that, although the findings are preliminary, they highlight the need to strengthen transparency, access control mechanisms, and data protection in generative AI systems, as well as to advance their analysis from a regulatory perspective.
More info: https://leakylm.github.io/.
This post was originally published on IMDEA Networks Institute and republished here with permission.
Reviewed by Irfan Ahmad.
Read next:
• Study Suggests AI Systems May Reinforce Psychological Mechanisms Linked to Extremist Radicalisation in Vulnerable Individuals
• From AirTags to AI nudification: the growing toolkit of technology‑facilitated abuse
by External Contributor via Digital Information World
Study Suggests AI Systems May Reinforce Psychological Mechanisms Linked to Extremist Radicalisation in Vulnerable Individuals
Image: Mikhail Mamaev - unsplash
How are ordinary people drawn into extremist circles – and what role can artificial intelligence play in that process?
This question is addressed by a new study which, for the first time, combines psychological theories of radicalisation with knowledge of modern AI technologies such as recommendation algorithms, generative AI and botnets.
‘We have developed a comprehensive model that shows how digital systems can exploit – or amplify – people’s social and psychological needs in ways we do not yet fully understand,’ explains Milan Obaidi, associate professor at the Department of Psychology at the University of Copenhagen.
Anger grows step by step
Radicalisation rarely begins as a sudden upheaval. Instead, individuals move gradually through a process in which digital technologies and psychological vulnerabilities can influence one another.
The study divides this process into four key phases:
- Exposure – algorithms present users with polarising or extreme content, often without the user actively seeking it out.
- Reinforcement – repeated exposure and algorithmic personalisation create echo chambers and reinforce the new attitudes.
- Group integration – online communities and even AI-generated ‘peers’ can create strong bonds of identity reminiscent of group membership.
- Violent acts – in rare cases, this development can culminate in violent extremism.
According to the researchers, AI systems can be seen as a kind of accelerator: they can identify psychologically vulnerable individuals, tailor content and create synthetic communities that resemble human interactions.
‘We are seeing an environment where users are not only exposed to extreme content, but also have it reflected back to them by algorithms in ways that can amplify their sense of meaning, anger or injustice,’ says Milan Obaidi, adding:
‘It is the combination of the technology’s scalability and people’s psychological needs that makes this development particularly worrying.’
Generative AI introduces entirely new risks
Whereas recommendation algorithms primarily control what content the user sees, generative models such as large language models add a new layer: they can create the content that radicalises.
AI can:
- Produce vast amounts of personalised propaganda.
- Simulate communities via swarms of bots.
- Act as “AI companions” that reinforce users’ extreme beliefs.
- Create highly convincing deepfakes and manipulated material.
‘This development may make it harder to distinguish between human and non-human influences – and thus amplify radicalisation processes that were previously limited by human labour,’ highlights Milan Obaidi.
Psychological vulnerability plays a crucial role
The study emphasises that not all users are equally vulnerable. AI particularly affects people who are already experiencing social isolation, identity insecurity, injustice or marginalisation – or a need for clarity, order and strong group affiliations.
Precisely because AI systems are designed to maximise engagement, they may inadvertently exploit these very vulnerabilities – without any ideological intent.
‘It is important to emphasise that AI does not create radicalisation out of the blue. But the technology can amplify known psychological mechanisms and make it easier for extreme ideas to gain a foothold among those who are already at risk,’ says Milan Obaidi.
The study ‘Intelligent Systems, Vulnerable Minds: A Framework for Radicalisation to Violence in the Age of AI’ has been published in the journal Personality and Social Psychology Review. Read it here.
This post was originally published on University of Copenhagen and republished here with permission.
Reviewed by Irfan Ahmad.
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by External Contributor via Digital Information World







