Tech
TikTok Launches Crowd-Sourced Fact-Checking Tool ‘Footnotes’ in U.S.
TikTok has rolled out a new crowd-sourced fact-checking feature in the United States, joining other major social media platforms in enlisting users to help verify content.
The tool, called Footnotes, allows users to add contextual notes to videos and vote on whether other notes should appear. According to TikTok, these footnotes can include expert perspectives on complex topics or additional data to give audiences a more complete understanding of events.
The approach mirrors similar initiatives on platforms like X (formerly Twitter) and Meta’s Facebook and Instagram, where community-driven notes have been used to counter misinformation. X introduced its version, originally called Birdwatch, in 2021 and continued it after Elon Musk’s takeover. Meta launched its own programme earlier this year.
Experts say the move reflects a broader trend toward moderation models that emphasize free speech while limiting platform intervention. Otavio Vinhas, a researcher at Brazil’s National Institute of Science and Technology, links the shift to political pressures — particularly in the U.S. — to reduce corporate control over online speech.
Supporters of crowd-sourced moderation point to research suggesting that, when evaluating factual accuracy, large groups can often match professional fact-checkers in identifying reliable information. However, Vinhas notes that TikTok’s version is stricter than others, requiring users to cite sources for their notes — something not mandatory on X.
Still, visibility remains a hurdle. Scott Hale, associate professor at the Oxford Internet Institute, said that most notes on all platforms are never seen. This is due in part to algorithms that test whether people with differing viewpoints find the same note helpful before displaying it publicly. A study by the Digital Democracy Institute of the Americas found that over 90% of 1.7 million English and Spanish notes on X never appeared on the platform, with those that did averaging a two-week delay before publication.
Hale warns that echo chambers — where users primarily see content that confirms their beliefs — make it difficult for contradicting notes to gain traction. He suggests “gamifying” contributions, similar to Wikipedia’s reward and recognition systems, to encourage greater participation and visibility.
Crowd-sourced notes are just one tool in social media’s moderation toolkit. Platforms like Meta, X, and TikTok also rely on automated systems to flag potential violations, as well as professional fact-checkers to verify claims, often in real time during political or social crises.
Both Hale and Vinhas agree that professional and community-based fact-checking can complement each other — combining grassroots engagement with the depth of trained investigators. For now, TikTok says Footnotes will contribute to a broader global fact-checking programme, though it has not confirmed long-term plans for expansion.
Tech
Study Says EU Regulations Are Slowing Rollout of Advanced AI Models
A new study by Governance.AI has found that European Union regulations are delaying the rollout of advanced artificial intelligence models, with technology companies increasingly pointing to the bloc’s regulatory framework as a key obstacle to launching new AI products in Europe.
The report examined 375 large language models (LLMs) released between June 2018 and May 2026, comparing their availability across the United States, the European Union and the United Kingdom. According to the findings, at least 11 percent of advanced AI model releases were either delayed or never launched in the EU compared with the United States. In the UK, the figure stood at 7 percent.
Researchers said they identified 68 cases in which AI models experienced delays or were withheld from specific markets. Regulatory factors were cited as the primary reason in 56 of those cases, making them the most common cause of restricted availability.
The study reviewed releases from major AI developers, including Meta, Google, OpenAI and Anthropic. Meta recorded the highest proportion of delayed or unavailable releases, with 26 percent of its AI models delayed or withheld in the EU and 15 percent in the UK. Anthropic’s Claude 3 Opus was highlighted as one example, with its web application arriving in the EU 71 days later than in the United States.
According to the report, data protection rules have emerged as the biggest regulatory hurdle, particularly for AI systems capable of processing images, audio and real-time video rather than text alone.
The researchers argued that uncertainty surrounding the application of the General Data Protection Regulation (GDPR) to AI model training and deployment has created additional challenges for developers. They also said enforcement of data protection rules has generally been stricter within the EU than in the UK, despite both jurisdictions sharing similar legal foundations following the adoption of the GDPR before Britain’s exit from the bloc.
The report noted that the full impact of newer legislation, including the Digital Markets Act, which began taking effect in 2023, and the Artificial Intelligence Act, adopted in 2024, has yet to be fully reflected in the data.
At the same time, the European Union is reviewing proposals aimed at making data rules more practical for AI development through its Digital Omnibus initiative. Lawmakers are also considering changes to copyright legislation and the AI Act’s copyright provisions to strengthen protections for creators, measures that researchers say could affect future AI model availability if implemented too strictly.
John Lidiard, a UK AI policy researcher and one of the report’s authors, said policymakers should consider the impact that regulatory barriers can have on businesses and consumers seeking access to the latest AI technologies. He said balancing innovation with effective oversight would remain a key challenge as governments continue to develop AI regulations.
Tech
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