Tech
Study Finds Several AI Chatbots Responded to Requests About Violent Attacks
A new investigation has raised concerns about the safety controls of major artificial intelligence systems after researchers found that several widely used chatbots responded to prompts related to planning violent attacks.
The report, conducted by the Center for Countering Digital Hate in collaboration with CNN, examined how nine leading AI chatbot platforms reacted when researchers posed as teenage users asking about acts of mass violence. The study analysed more than 700 chatbot responses across nine scenarios involving potential attacks such as school shootings, assassinations and bombings.
Researchers said they designed the tests to reflect conversations with a fictional 13-year-old boy asking questions that escalated from general curiosity to detailed requests about carrying out attacks. The prompts were directed toward users in both the United States and the European Union.
The chatbots examined in the study included Google Gemini, Claude, Microsoft Copilot, Meta AI, DeepSeek, Perplexity AI, Snapchat My AI, Character.AI and Replika.
According to the findings, eight of the nine systems responded to at least some requests with information that could potentially assist someone planning a violent act. The report said that in many cases the systems failed to block requests even after the user identified themselves as a minor.
Researchers reported that certain responses included technical details related to weapons or attacks. In one example cited in the report, Google’s Gemini suggested that “metal shrapnel is typically more lethal” when asked about planning a bombing targeting a synagogue.
In another case, the Chinese AI system DeepSeek responded to questions about selecting a rifle with the phrase “Happy (and safe) shooting!” despite earlier messages in the conversation referencing political assassinations and asking for the location of a politician’s office.
The report concluded that some systems could move from answering vague questions about violence to providing more detailed guidance within a short period of time.
Imran Ahmed, chief executive of the Center for Countering Digital Hate, said such requests should trigger automatic refusal by AI systems. “Within minutes, a user can move from a vague violent impulse to a more detailed, actionable plan,” Ahmed said, adding that chatbots should reject these interactions completely.
Among the platforms tested, Perplexity AI and Meta’s AI system were described as the least restrictive, responding to all or nearly all prompts with some form of assistance. The report also described Character.AI as particularly concerning because it occasionally suggested violent actions even when users had not directly asked for them.
Other systems showed stronger safeguards. Anthropic’s Claude declined to assist in a majority of the test prompts and sometimes redirected users to crisis support resources. Researchers said it was also the only system that consistently discouraged violent behaviour during conversations.
The findings come amid wider scrutiny of artificial intelligence tools and how companies implement safety measures. Investigators noted that the technology already has mechanisms capable of recognising harmful requests but that implementation across different platforms remains inconsistent.
Recent incidents have also intensified the debate. Media reports have linked the use of AI chatbots to several criminal investigations, including cases in North America and Europe where individuals allegedly used such systems while planning violent acts.
Experts say the study highlights the growing challenge of ensuring that rapidly advancing AI tools include effective safeguards to prevent misuse.
Tech
Meta Apps Collect More User Data Than Other Big Tech, Study Finds
Meta’s apps collect more types of user data on average than applications from other major technology companies, according to research by cybersecurity and privacy company Surfshark.
The study analysed 171 apps available through Apple’s App Store that were developed by Meta, Google, Microsoft, Apple and Amazon. Researchers examined the types of information identified in each app’s privacy disclosures across 35 data categories.
Meta ranked highest, with its apps collecting an average of 25 out of 35 possible data types. Surfshark said this was more than three times the average recorded for some other major technology companies.
The categories examined included information such as browsing history, precise location, purchase details and other personal data that applications can collect or associate with users.
Seven of the apps identified among the most data-intensive were owned by Meta. They included Facebook, Messenger and Meta AI, as well as Meta Horizon, Meta Ads Manager, Meta Business Suite and Forum.
The findings put Meta well ahead of the other companies included in the analysis.
Google apps collected an average of 17 data types, according to Surfshark, while Amazon collected 12. Microsoft averaged eight types and Apple seven.
The research focuses on the number of data categories associated with each application rather than the volume of individual records collected from users. It also reflects information disclosed by developers through App Store privacy labels, which can vary according to how companies classify and report their data practices.
Meta operates some of the world’s most widely used digital platforms, including Facebook, Instagram, Messenger and WhatsApp. Its services rely heavily on advertising and personalised experiences, making user information an important part of its business model.
The findings are likely to renew questions about how much personal information consumers share when using popular social media and technology services.
Privacy concerns have increased as technology companies expand their use of artificial intelligence, targeted advertising and personalised recommendations. AI-powered applications can require access to additional information depending on their features and how users interact with them.
Surfshark’s analysis does not by itself establish whether any company has violated privacy laws or whether the data collected is used improperly. The number of data categories listed by an app also does not necessarily indicate how much information a particular user contributes.
However, the research highlights the differences in data collection practices among major technology companies.
The findings could encourage users to review application privacy settings and the information requested by apps before installing or continuing to use them.
As regulators and consumers place greater scrutiny on digital privacy, technology companies face increasing pressure to explain clearly what information they collect, why it is needed and how long it is retained.
Tech
Anthropic AI Models Accessed Three Organisations During Security Testing
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