Parents spoke after the Antioch High School shooting on Wednesday, Jan. 22, outside of Nashville, Tennessee. Antioch High School in Nashville, Tennessee, where a deadly shooting took place last Wednesday, did not have metal detectors due to some administrators' concerns about racism, the New York Post reported. "I knew this day was gonna happen," Fran Bush, a former Metro Nashville Public Schools (MNPS) board member, told the New York Post. "I knew it was gonna happen just because it's like a free open door, everybody coming in." The shooting, which left 16-year-old student Josselin Corea Escalante and the suspect dead, has parents calling for the school to bring in metal detectors after the AI security system failed to detect the 17-year-old gunman's weapon.

The Final Exam, a recently released video game in which you play as a student caught amid a school shooting, lasts for around ten minutes, about the length of a real shooting event in a U.S. school. The game opens in an empty locker room. You hear distant gunfire, screams, harried footsteps, and the thudding of heavy furniture being overturned. The sense of disharmony is immediate: a familiar scene of youth and learning is grimly debased into one of peril. As the lockers surround you, their doors gaping, you feel caged: get me out of here. Moments later, as you enter the gymnasium, a two-minute countdown flashes on screen.

The internet has brought both benefits and harms to society. A prime example of the latter is misinformation, including conspiracy theories, which flood the web. Recent advances in natural language processing, particularly the emergence of large language models (LLMs), have improved the prospects of accurate misinformation detection. However, most LLM-based approaches to conspiracy theory detection focus only on binary classification and fail to account for the important relationship between misinformation and affective features (i.e., sentiment and emotions). Driven by a comprehensive analysis of conspiracy text that reveals its distinctive affective features, we propose ConspEmoLLM, the first open-source LLM that integrates affective information and is able to perform diverse tasks relating to conspiracy theories. These tasks include not only conspiracy theory detection, but also classification of theory type and detection of related discussion (e.g., opinions towards theories). ConspEmoLLM is fine-tuned based on an emotion-oriented LLM using our novel ConDID dataset, which includes five tasks to support LLM instruction tuning and evaluation. We demonstrate that when applied to these tasks, ConspEmoLLM largely outperforms several open-source general domain LLMs and ChatGPT, as well as an LLM that has been fine-tuned using ConDID, but which does not use affective features. This project will be released on https://github.com/lzw108/ConspEmoLLM/.

Narratives serve as fundamental frameworks in our understanding of the world and play a crucial role in collaborative sensemaking, providing a versatile foundation for sensemaking. Framing is a subtle yet potent mechanism that influences public perception through specific word choices, shaping interpretations of reported news events. Despite the recognized importance of narratives and framing, a significant gap exists in the literature with regard to the explicit consideration of framing within the context of computational extraction and representation. This article explores the capabilities of a specific narrative extraction and representation approach -- narrative maps -- to capture framing information from news data. The research addresses two key questions: (1) Does the narrative extraction method capture the framing distribution of the data set? (2) Does it produce a representation with consistent framing? Our results indicate that while the algorithm captures framing distributions, achieving consistent framing across various starting and ending events poses challenges. Our results highlight the potential of narrative maps to provide users with insights into the intricate framing dynamics within news narratives. However, we note that directly leveraging framing information in the computational narrative extraction process remains an open challenge.

The parents of a teenager who was killed in Florida's Parkland school shooting in 2018 have started a bold new project called The Shotline to lobby for stricter gun laws in the country. The Shotline uses AI to recreate the voices of children killed by gun violence and send recordings through automated calls to lawmakers, The Wall Street Journal reported. The project launched on Wednesday, six years after a gunman killed 17 people and injured more than a dozen at a high school in Parkland, Florida. It features the voice of six children, some as young as ten, and young adults, who have lost their lives in incidents of gun violence across the US. Once you type in your zip code, The Shotline finds your local representative and lets you place an automated call from one of the six dead people in their own voice, urging for stronger gun control laws.

Families of gun violence victims are using artificial intelligence to recreate their loved ones' voices and taunt lawmakers who oppose gun control on the sixth anniversary of the Parkland massacre. The robocall messages are being sent to senators and House members who support the National Rifle Association and Second Amendment rights in a campaign that launched on Valentine's Day, Wednesday, according to the Associated Press. Manuel and Patricia Oliver, whose son Joaquin "Guac" Oliver died in the 2018 high school shooting in Parkland, Florida, said the campaign run through The Shotline website is intended to spur Congress to ban the sale of guns like the AR-15 rifle. "We come from a place where gun violence is a problem, but you will never see a 19-year-old with an AR-15 getting into a school and shooting people," Manuel Oliver told the Associated Press in an interview. The Olivers, immigrants from Venezuela, became activists after Joaquin and 13 other students at Marjory Stoneman Douglas High School were murdered by a 19-year-old killer with a rifle.

Six years ago today, Joaquin Oliver was killed in a hallway outside his Florida classroom, one of 17 students and staff murdered in the worst high school shooting in the US. On Wednesday, lawmakers in Washington DC will hear his voice, recreated by artificial intelligence, in phone calls demanding to know why they've done nothing to tackle the plague of gun violence. "It's been six years and you've done nothing. Not a thing to stop all the shootings that have happened since," the message from Oliver, who was 17 when he died in the 2018 Valentine's Day's tragedy at Parkland's Marjory Stoneman Douglas high school, says. "I'm back today because my parents used AI to recreate my voice to call you. Other victims like me will be calling too, again and again, to demand action. How many calls will it take for you to care? How many dead voices will you hear before you finally listen?"

This article was copublished with The Markup, a nonprofit, investigative newsroom that challenges technology to serve the public good. Less than 10 days after the Robb Elementary School shooting in Uvalde, Texas, in May 2022, Axon Enterprises CEO Rick Smith announced the company had formally started developing Taser-equipped drones. The technology, Smith argued, could potentially save lives during mass shootings by incapacitating active shooters within seconds. For Axon, which changed its name from Taser in 2017, the concept seemed a sensible next step for stakeholders who share Axon's public safety mission, Smith said on the company's site. "In brief," he wrote, "non-lethal drones can be installed in schools and other venues and play the same role that sprinklers and other fire suppression tools do for firefighters: Preventing a catastrophic event, or at least mitigating its worst effects."

The'Fox & Friends' co-hosts discussed concerns surrounding artificial intelligence and how it will impact the internet moving forward. A Florida school district is planning to use artificial intelligence to detects guns and potential school shooting threats. Board members with the Hernando County School District voted last week to approve a one-year contract not going over $200,000 with ZeroEyes, a software company, according to FOX 13. ZeroEyes uses school district's security cameras to spot exposed or brandished firearms. The company was founded by Rob Huberty, a former Navy Seal, and claims that its software can alert first responders to a potential threat before someone is able to fire their weapon.

Fox News correspondent Matt Finn has the latest on the impact of AI technology that some say could outpace humans on'Special Report.' WASHINGTON – While most people look to artificial intelligence, or AI, for quick answers to complex problems, a growing number of school districts are turning to the technology to keep their students and staff safe. A school district in Charles County, Maryland, roughly an hour from Washington D.C., is in the process of installing software and hardware which would allow their current security cameras to detect a potential active shooter. "This artificial intelligence has the ability to be able to identify a weapon, to assess what's going on and how that person is acting," said Jason Stoddard, Director of School safety and Security for Charles County Public Schools. The district, through a state grant, is in the process of installing AI gun detection technology at all of its campuses.