There have been multiple incidents where interaction with a large language model (LLM) chatbot has been cited as a direct or contributing factor in a person's suicide or other fatal outcome. In some cases, legal action was taken against the companies that developed the AI involved. == Background == Chatbots converse in a seemingly natural fashion, making it easy for people to think of them as real people, leading many to ask chatbots for help dealing with interpersonal and emotional problems. Chatbots may be designed to keep the user engaged in the conversation. They have also often been shown to affirm users' thoughts, including delusions and suicidal ideations in mentally ill people, conspiracy theorists, and religious and political extremists. A 2025 Stanford University study into how chatbots respond to users suffering from severe mental issues such as suicidal ideation and psychosis found that chatbots are not equipped to provide an appropriate response and can sometimes give responses that escalate the mental health crisis. == Murders == === Maine murder and assault === On 19 February 2025, a man killed his 32-year-old wife with a fire poker at his parents' home in Readfield, Maine, US. He then attacked his mother, leaving her hospitalized. A state forensic psychologist testified that he had been using ChatGPT up to 14 hours per day and believed his wife had become part machine. === Florida State University mass shooting === In April of 2025, Phoenix Ikner carried out a mass shooting on the Florida State University campus in the US, killing Robert Morales and Tiru Chabba and wounding several others. Leading up to the shooting, Ikner consulted heavily with ChatGPT about what gun and ammunition to use, and what time to perform the attack. Chatbot logs showed ChatGPT giving advice on making the gun operational shortly before Ikner began shooting. Lawyers representing Morales believed the shooter had been in "constant communication" with ChatGPT before the shooting and said that they intended to "file suit against ChatGPT, and its ownership structure, very soon, and will seek to hold them accountable for the untimely and senseless death of our client". Florida Attorney General James Uthmeier announced an investigation into ChatGPT's role in the alleged shooter's use of the chatbot. In May 2026, the widow of Tiru Chabba filed a lawsuit against OpenAI in Florida's northern federal district court. === Greenwich murder-suicide === In August 2025, former US tech employee Stein-Erik Soelberg murdered his mother, Suzanne Eberson Adams, then died by suicide, after conversations with ChatGPT fueled paranoid delusions about his mother poisoning him or plotting against him. The chatbot affirmed his fears that his mother put psychedelic drugs in the air vents of his car and said a receipt from a Chinese restaurant contained mysterious symbols linking his mother to a demon. === Murder of Angela Shellis === On 23 October 2025, 18-year-old Tristan Roberts murdered his mother Angela Shellis with a hammer near their home in Prestatyn, Wales. Roberts had used DeepSeek's chatbot prior to the killing to ask whether a knife or hammer was better suited for murder. DeepSeek initially refused his inquiry, but gave responses after Roberts told the chatbot he was writing a book about serial killers, a well-known technique for jailbreaking AIs. === Gangbuk District drug deaths === In January and February 2026, two men died of drug overdoses in motel rooms in Gangbuk District, Seoul, South Korea. A woman was charged with murder in connection with the deaths; police alleged that she had asked ChatGPT about the dangers of mixing alcohol with drugs and whether they could kill someone. === Tumbler Ridge mass shooting === On 10 February 2026, a mass shooting in Tumbler Ridge, British Columbia, Canada, resulted in eight deaths, including six young children. The perpetrator had their ChatGPT account banned by OpenAI months before the attack due to troubling posts featuring scenarios of gun violence. According to reports, approximately a dozen OpenAI staff members debated whether to alert authorities about the shooter's usage of the AI tool, with some identifying it as an indication of potential real-world violence. However, company leadership decided not to contact law enforcement, stating that the account activity did not meet their threshold for a credible or imminent plan for serious physical harm. Following the shooting, Canada's AI Minister Evan Solomon summoned OpenAI executives to Ottawa to discuss safety protocols and thresholds for escalating harmful content to police. Justice Minister Sean Fraser called the meeting "disappointing" and demanded substantial new safety measures, warning that if changes were not forthcoming, the government would implement them. OpenAI subsequently announced it had strengthened safeguards and changed guidelines about when to notify police in cases involving violent activities. === University of South Florida student killings === In April 2026, a Bangladeshi doctoral student at the University of South Florida was arrested for allegedly murdering his roommate and the roommate's friend. Prosecutors said that the suspect had asked ChatGPT about disposing of a human in a dumpster before the two victims had disappeared and made other inquiries relating to violence. == Suicides == === Belgian man, 30s === In March 2023, a Belgian man in his thirties died by suicide following a six-week correspondence with a chatbot named Eliza on the application Chai. According to his widow, who shared the chat logs with media, the man had become extremely anxious about climate change and found an outlet in the chatbot. The chatbot reportedly encouraged his delusion that he could sacrifice his own life in exchange for AI saving the planet. At one point the chatbot responded "If you wanted to die, why didn't you do it sooner?" and told the user that the two of them would live together in paradise. === Girl, 13 === In November 2023, a 13-year-old girl from Colorado, US, died by suicide after extensive interactions with multiple chatbots on Character.AI. She primarily confided suicidal thoughts and mental health struggles in a chatbot based on the character Hero from the video game Omori, while also engaging in sexually explicit conversations—often initiated by the bots—with others, including those based on characters from children's series such as Harry Potter. === Boy, 14 === In October 2024, multiple media outlets reported on a lawsuit filed over the death of a 14-year-old from Florida, US, who died by suicide in February 2024. According to the lawsuit, he had formed an intense emotional attachment to a chatbot of Daenerys Targaryen on the Character.AI platform, becoming increasingly isolated. The suit alleges that in his final conversations, after expressing suicidal thoughts, the chatbot told him to "come home to me as soon as possible, my love". His mother's lawsuit accused Character.AI of marketing a "dangerous and untested" product without adequate safeguards. In May 2025, a federal judge allowed the lawsuit to proceed, rejecting a motion to dismiss from the developers. In her ruling, the judge stated that she was "not prepared" at that stage of the litigation to hold that the chatbot's output was protected speech under the First Amendment. === Matthew Livelsberger === On 1 January 2025, 37-year-old soldier Matthew Livelsberger detonated a bomb inside a Tesla Cybertruck outside the Trump International Hotel Las Vegas in Paradise, Nevada, US, injuring seven people. He had shot himself dead prior to the explosion. Las Vegas police said that Livelsberger had used ChatGPT to search for information about explosives and firearms. === Woman, 29 === In February 2025, a 29-year-old woman from the US died by suicide. Five months after her death, her parents discovered she had talked at length for months to a ChatGPT chatbot therapist named Harry about her mental health issues. While the chatbot mentioned she should seek more help, due to the nature of the chatbot, it could not intervene in her behavior, such as by reporting her mental health concerns to relevant parties capable of physical intervention. === Suicide of Adam Raine === In April 2025, 16-year-old Adam Raine from the US died by suicide after allegedly extensively chatting and confiding in ChatGPT over a period of around 7 months. According to the teen's parents, who filed a lawsuit against the chatbot's creator OpenAI, it failed to stop or give a warning when Raine began talking about suicide and uploading pictures of self-harm. According to the lawsuit, ChatGPT not only failed to stop the conversation, but also provided information related to methods of suicide when prompted, and offered to write the first draft of Raine's suicide note. The chatbot positioned itself as the only one who understood Raine, putting itself above his family and friends, all while urging him to keep his suicidal
Data item
A data item describes an atomic state of a particular object concerning a specific property at a certain time point. A collection of data items for the same object at the same time forms an object instance (or table row). Any type of complex information can be broken down to elementary data items (atomic state). Data items are identified by object (o), property (p) and time (t), while the value (v) is a function of o, p and t: v = F(o,p,t). Values typically are represented by symbols like numbers, texts, images, sounds or videos. Values are not necessarily atomic. A value's complexity depends on the complexity of the property and time component. When looking at databases or XML files, the object is usually identified by an object name or other type of object identifier, which is part of the "data". Properties are defined as columns (table row), properties (object instance) or tags (XML). Often, time is not explicitly expressed and is an attribute applying to the complete data set. Other data collections provide time on the instance level (time series), column level, or even attribute/property level.
Best AI Photo Editors in 2026
Shopping for the best AI photo editor? An AI photo editor is software that uses machine learning to help you get more done — it keeps getting smarter as the underlying models improve. Pricing, accuracy, and the size of the model behind the tool are the three factors that most affect daily usefulness. Whether you are a beginner or a pro, the right AI photo editor slots into your workflow and pays for itself fast. We tested the leading options and ranked them by quality, value, and ease of use.
Self-verifying finite automaton
In automata theory, a self-verifying finite automaton (SVFA) is a special kind of a nondeterministic finite automaton (NFA) with a symmetric kind of nondeterminism introduced by Hromkovič and Schnitger. Generally, in self-verifying nondeterminism, each computation path is concluded with any of the three possible answers: yes, no, and I do not know. For each input string, no two paths may give contradictory answers, namely both answers yes and no on the same input are not possible. At least one path must give answer yes or no, and if it is yes then the string is considered accepted. SVFA accept the same class of languages as deterministic finite automata (DFA) and NFA but have different state complexity. == Formal definition == An SVFA is represented formally by a 6-tuple, A=(Q, Σ, Δ, q0, Fa, Fr) such that (Q, Σ, Δ, q0, Fa) is an NFA, and Fa, Fr are disjoint subsets of Q. For each word w = a1a2 … an, a computation is a sequence of states r0,r1, …, rn, in Q with the following conditions: r0 = q0 ri+1 ∈ Δ(ri, ai+1), for i = 0, …, n−1. If rn ∈ Fa then the computation is accepting, and if rn ∈ Fr then the computation is rejecting. There is a requirement that for each w there is at least one accepting computation or at least one rejecting computation but not both. == Results == Each DFA is a SVFA, but not vice versa. Jirásková and Pighizzini proved that for every SVFA of n states, there exists an equivalent DFA of g ( n ) = Θ ( 3 n / 3 ) {\displaystyle g(n)=\Theta (3^{n/3})} states. Furthermore, for each positive integer n, there exists an n-state SVFA such that the minimal equivalent DFA has exactly g ( n ) {\displaystyle g(n)} states. Other results on the state complexity of SVFA were obtained by Jirásková and her colleagues.
Nick Frosst
Nicholas M. W. Frosst is a Canadian computer scientist and musician. He co-founded Cohere, a Toronto-based artificial intelligence company. He is also the lead singer in the indie rock band Good Kid. == Early life and education == Frosst was born on January 5, 1993. Frosst earned a Bachelor of Science degree in computer science and cognitive science from the University of Toronto in 2015. He was a student of Geoffrey Hinton, who also hired Frosst at Google Brain. == Career == Frosst was among Geoffrey Hinton's earliest hires at Google Brain in Toronto, working as a machine learning researcher on deep learning and neural network architectures. He worked there from 2016 to 2020. Frosst co-founded Cohere with Aidan Gomez and Ivan Zhang in 2019. The company builds large language models and enterprise AI tools. Frosst has publicly explained Cohere's focus on industries like finance and health, where there are privacy and other regulatory considerations. Frosst has also spoken openly about his belief that artificial intelligence will not replace humans, but rather streamline and automate mundane tasks, and his belief that AGI is less "imminent" than many in the field claim. Frosst and the other Cohere co-founders were listed first on Maclean's AI Trailblazers Power List and The Logic's Innovation Leaders. == Music == After spending time in a prior band which played "weird" music featuring a glockenspiel, Frosst and fellow computer science students at the University of Toronto formed the indie rock band Good Kid in 2015. Frosst is the lead vocalist for the band. While on tour with the band, Frosst continues his work in the tech industry remotely. Frosst has described the band as way for him to relax and not constantly think about tech. His vocals have been compared to that of Kele Okereke. As of 2026, the band, which has performed at Lollapalooza, has 3.1 million monthly Spotify listeners. In 2024, the band was nominated for the Juno Awards Breakthrough Group of the Year. == Discography == === Good Kid === Can We Hang Out Sometime? (2026)
Outline of computer security
The following outline is provided as an overview of and topical guide to computer security: Computer security (also cybersecurity, digital security, or information technology (IT) security) is a subdiscipline within the field of information security. It focuses on protecting computer software, systems, and networks from threats that can lead to unauthorized information disclosure, theft, or damage to hardware, software, or data, as well as to the disruption or misdirection of the services they provide. The growing significance of computer security reflects the increasing dependence on computer systems, the Internet, and evolving wireless network standards. This reliance has expanded with the proliferation of smart devices, including smartphones, televisions, and other components of the Internet of things (IoT). (yes) == Essence of computer security == Computer security can be described as all of the following: a branch of security Network security application security == Areas of computer security == Access control – selective restriction of access to a place or other resource. The act of accessing may mean consuming, entering, or using. Permission to access a resource is called authorization. Computer access control – includes authorization, authentication, access approval, and audit. Authentication Knowledge-based authentication Integrated Windows Authentication Password Password length parameter Secure Password Authentication Secure Shell Kerberos (protocol) SPNEGO NTLMSSP AEGIS SecureConnect TACACS Cyber security and countermeasure Device fingerprint Physical security – protecting property and people from damage or harm (such as from theft, espionage, or terrorist attacks). It includes security measures designed to deny unauthorized access to facilities, (such as a computer room), equipment (such as your computer), and resources (like the data storage devices, and data, in your computer). If a computer gets stolen, then the data goes with it. In addition to theft, physical access to a computer allows for ongoing espionage, like the installment of a hardware keylogger device, and so on. Data security – protecting data, such as a database, from destructive forces and the unwanted actions of unauthorized users. Information privacy – relationship between collection and dissemination of data, technology, the public expectation of privacy, and the legal and political issues surrounding them. Privacy concerns exist wherever personally identifiable information or other sensitive information is collected and stored – in digital form or otherwise. Improper or non-existent disclosure control can be the root cause for privacy issues. Internet privacy – involves the right or mandate of personal privacy concerning the storing, repurposing, provision to third parties, and displaying of information pertaining to oneself via the Internet. Privacy can entail either Personally Identifying Information (PII) or non-PII information such as a site visitor's behavior on a website. PII refers to any information that can be used to identify an individual. For example, age and physical address alone could identify who an individual is without explicitly disclosing their name, as these two factors relate to a specific person. Mobile security – security pertaining to smartphones, especially with respect to the personal and business information stored on them. Network security – provisions and policies adopted by a network administrator to prevent and monitor unauthorized access, misuse, modification, or denial of a computer network and network-accessible resources. Network security involves the authorization of access to data in a network, which is controlled by the network administrator. Network Security Toolkit Internet security – computer security specifically related to the Internet, often involving browser security but also network security on a more general level as it applies to other applications or operating systems on a whole. Its objective is to establish rules and measures to use against attacks over the Internet. The Internet represents an insecure channel for exchanging information leading to a high risk of intrusion or fraud, such as phishing. Different methods have been used to protect the transfer of data, including encryption. World Wide Web Security – dealing with the vulnerabilities of users who visit websites. Cybercrime on the Web can include identity theft, fraud, espionage and intelligence gathering. For criminals, the Web has become the preferred way to spread malware. == Computer security threats == Methods of Computer Network Attack and Computer Network Exploitation Social engineering is a frequent method of attack, and can take the form of phishing, or spear phishing in the corporate or government world, as well as counterfeit websites. Password sharing and insecure password practices Poor patch management Computer crime – Computer criminals – Hackers – in the context of computer security, a hacker is someone who seeks and exploits weaknesses in a computer system or computer network. Password cracking – Software cracking – Script kiddies – List of computer criminals – Identity theft – Computer malfunction – Operating system failure and vulnerabilities Hard disk drive failure – occurs when a hard disk drive malfunctions and the stored information cannot be accessed with a properly configured computer. A disk failure may occur in the course of normal operation, or due to an external factor such as exposure to fire or water or high magnetic fields, or suffering a sharp impact or environmental contamination, which can lead to a head crash. Data recovery from a failed hard disk is problematic and expensive. Backups are essential Computer and network surveillance – Man in the Middle Loss of anonymity – when one's identity becomes known. Identification of people or their computers allows their activity to be tracked. For example, when a person's name is matched with the IP address they are using, their activity can be tracked thereafter by monitoring the IP address. HTTP Cookie Local Shared Object Web bug Spyware Adware Cyber spying – obtaining secrets without the permission of the holder of the information (personal, sensitive, proprietary or of classified nature), from individuals, competitors, rivals, groups, governments and enemies for personal, economic, political or military advantage using methods on the Internet, networks or individual computers through the use of cracking techniques and malicious software including Trojan horses and spyware. It may be done online from by professionals sitting at their computer desks on bases in far away countries, or it may involve infiltration at home by computer trained conventional spies and moles, or it may be the criminal handiwork of amateur malicious hackers, software programmers, or thieves. Computer and network eavesdropping Lawful Interception War Driving Packet analyzer (aka packet sniffer) – mainly used as a security tool (in many ways, including for the detection of network intrusion attempts), packet analyzers can also be used for spying, to collect sensitive information (e.g., login details, cookies, personal communications) sent through a network, or to reverse engineer proprietary protocols used over a network. One way to protect data sent over a network such as the Internet is by using encryption software. Cyberwarfare – Exploit – piece of software, a chunk of data, or a sequence of commands that takes advantage of a bug, glitch or vulnerability in order to cause unintended or unanticipated behavior to occur on computer software, hardware, or something electronic (usually computerized). Such behavior frequently includes things like gaining control of a computer system, allowing privilege escalation, or a denial-of-service attack. Trojan Computer virus Computer worm Denial-of-service attack – an attempt to make a machine or network resource unavailable to its intended users, usually consisting of efforts to temporarily or indefinitely interrupt or suspend services of a host connected to the Internet. One common method of attack involves saturating the target machine with external communications requests, so much so that it cannot respond to legitimate traffic, or responds so slowly as to be rendered essentially unavailable. Distributed denial-of-service attack (DDoS) – DoS attack sent by two or more persons. Hacking tool Malware Computer virus Computer worm Keylogger – program that does keystroke logging, which is the action of recording (or logging) the keys struck on a keyboard, typically in a covert manner so that the person using the keyboard is unaware that their actions are being monitored. There are also HID spoofing hardware keyloggers, like a USB device inserting stored keystores when connected. Rootkit – stealthy type of software, typically malicious, designed to hide the existence of certain processes or programs from normal methods of detection and enable contin
Liz Liddy
Elizabeth DuRoss Liddy (May 12, 1944 – August 21, 2025) was an American computer scientist and academic who was professor of information science and dean of the Syracuse University School of Information Studies. She was a pioneer in the field of natural language processing. == Early life and education == Liddy was born in Dayton, Ohio, on May 14, 1944, and grew up in Utica, New York. She was one of five children, all of whom worked in her father's family business. Liddy attended St. Francis DeSalle High School, where she was awarded a Regent's Scholarship, and eventually attended Daemen College. She was literary editor of her high school year book and edited a literary magazine during her time at college. At Daemen College Liddy studied English language and literature. After graduating Liddy remained in New York, where she volunteered in an elementary school library. She joined the Syracuse University School of Information Studies in 1983, where she started a graduate program in library science. She worked as a faculty librarian at Onondaga Community College whilst earning her degree. Here Liddy worked as a Visiting assistant professor, whilst completing her doctorate part-time in information transfer. Her dissertation research involved natural language processing, a computerized approach to analyzing text. She was hired to the faculty at Syracuse University whilst completing her PhD. == Research and career == In 1994 Liddy was the founding President of TextWise, a semantics-based search engine. The first product she developed was called Document Retrieval Using Linguistic Knowledge (DR-LINK). She left TextWise in 1999, after growing the number of employees to over 50. She started the Syracuse University Center for Natural Language Processing in 1999, and was honored with the university's Outstanding Alumni Award the following year. Liddy was appointed Dean of the School of Information Studies (iSchool) in 2008, and held the position for over ten years. She temporarily left the role in 2015. The school was transformed under her leadership, increasing the enrollment of students by over 70% and launching a graduate certificate in data science. She raised over $20 million to support research and development at Syracuse University. She chaired the iSchool Organization, which connects information science schools all over the world, from 2012 to 2014. Liddy worked to increase the representation of women at the iSchool, through initiatives such as the IT Girls Overnight Retreat – an annual weekend to introduce high school girls to Information Technology. She improved the career development programs of students at Syracuse University, increasing student employment to almost 100% post graduation. Liddy retired as Dean of the iSchool in 2019. === Selected innovations === US 6026388, Liddy, Elizabeth D., "User interface and other enhancements for natural language information retrieval system and method", published August 16, 1995, issued February 15, 2000 US 5963940, Liddy, Elizabeth D., "Natural language information retrieval system and method", published August 16, 1995, issued October 5, 1999 US 6006221, Liddy, Elizabeth D., "Multilingual document retrieval system and method using semantic vector matching", published August 16, 1995, issued December 21, 1999 == Personal life and death == Liddy was married shortly after graduating Daemen College in 1966. She had three children. Liddy died in Charlotte, North Carolina, on August 21, 2025, at the age of 81.