Tokyo Shares AI-Generated Mount Fuji Eruption Video to Prepare Citizens - 1

Photo by Max Bender on Unsplash

Tokyo Shares AI-Generated Mount Fuji Eruption Video to Prepare Citizens

  • Written by Andrea Miliani Former Tech News Expert
  • Fact-Checked by Sarah Frazier Former Content Manager

Japanese officials from the Tokyo Metropolitan Government have released an AI-generated video simulating a Mount Fuji eruption to mark Volcanic Disaster Preparedness Day on Sunday.

In a rush? Here are the quick facts:

  • The Tokyo Metropolitan Government released an AI-generated video simulating a Mount Fuji eruption.
  • The realistic video showed how the volcanic ashes could cover the Japanese city within two hours and the consequences of the tragic scenario.
  • Japanese officials explained that the goal is to raise awareness.

According to CNN , the realistic video showed volcanic ash covering the sky and Tokyo’s buildings and vehicles, attempting to show the city’s 20 million residents what could happen if the volcano erupted.

Mount Fuji has not erupted since 1707, but it remains an active volcano. “The moment may arrive without any warning,” was one of the messages in the AI-generated video. It also warns that the volcano ashes could cover the Japanese city within two hours, disrupting power, food supplies, and traffic, while posing serious health risks.

In January, the Japanese government announced that there was an 80% chance the territory could be affected by a severe earthquake. And, while experts also warn that these predictions can never be significantly accurate, Tokyo officials have preferred to pursue an impactful prevention campaign.

🌋 Tokyo releases AI-generated video of Mount Fuji erupting.. It is all part of an artificial intelligence-generated video the Tokyo Metropolitan Government released last week to raise awareness of what could happen to the capital if Mount Fuji erupted. 🌋 pic.twitter.com/PFKKT2Rcu4 — Global𝕏 (@GlobaltrekX) August 26, 2025

The Japanese government explained that even if there are no signs of Fuji’s eruption, the goal is to raise awareness. “The simulation is designed to equip residents with accurate knowledge and preparedness measures they can take in case of an emergency,” said the Tokyo government in a recent statement.

In March, the Japanese government also warned residents to keep a two-week supply of essentials at home in case of emergency. As a country highly vulnerable to natural disasters, Japan continuously prepares for a range of scenarios, from typhoons and earthquakes to floods and volcanic eruptions.

AI is increasingly playing a role in disaster preparedness, helping scientists predict natural phenomena and unexpected events. NASA and MBI recently developed an open-source AI system called Surya to predict solar activity. Scientists are also using AI models to anticipate viral evolution as part of pandemic preparedness .

New AI Detects Questionable Scientific Journals - 2

Image by National Cancer Institute, from Unsplash

New AI Detects Questionable Scientific Journals

  • Written by Kiara Fabbri Former Tech News Writer
  • Fact-Checked by Sarah Frazier Former Content Manager

Scientists developed an AI detection system for open-access journals with shady practices, revealing integrity threats in science and the need for human assessment

In a rush? Here are the quick facts:

  • AI trained on 12,000 reputable and 2,500 low-quality journals.
  • AI flagged over 1,000 previously unknown suspect journals.
  • The current AI false positive rate is 24%, requiring human oversight.

Open-access journals enable free access to research for scientists worldwide, boosting their global exposure. However, the open-access model has created an environment where questionable journals now proliferate. These outlets often charge authors fees, promise fast publication, but lack proper peer review, putting scientific integrity at risk.

Researchers recently published their findings testing a new AI tool which aims to tackle this problem. They trained the AI using more than 12,000 high-quality journals, together with 2,500 low-quality or questionable publications removed from the Directory of Open Access Journals (DOAJ).

The AI learned to identify red flags by analyzing editorial board gaps, unprofessional website design, and minimal citation activity.

It identified more than 1,000 previously unknown suspicious journals from a dataset of 93,804 open-access journals on Unpaywall, which collectively publish hundreds of thousands of articles. Many of the iffy journals come from developing countries.

“Our findings demonstrate AI’s potential for scalable integrity checks, while also highlighting the need to pair automated triage with expert review,” the researchers write.

The researchers point out that the system is not perfect. It currently produces 24% false positives, meaning one in four genuine journals may be incorrectly flagged. Human experts are still required for final evaluation.

The AI system assesses journal credibility by analyzing website content, design elements, and bibliometric data, including citation patterns and author affiliations. Indicators of questionable journals include high self-citation rates and lower author h-index values, while established institutional diversity and broad citation networks indicate reliability.

The research team expects future development will improve the AI system’s ability to detect deceptive publisher strategies. By combining automated tools with human oversight, the scientific community can better protect research integrity and guide authors toward trustworthy journals.