As language models grow in popularity, it becomes increasingly important to clearly measure all possible markers of demographic identity in order to avoid perpetuating existing societal harms. Many datasets for measuring bias currently exist, but they are restricted in their coverage of demographic axes and are commonly used with preset bias tests that presuppose which types of biases models can exhibit. In this work, we present a new, more inclusive bias measurement dataset, HolisticBias, which includes nearly 600 descriptor terms across 13 different demographic axes. HolisticBias was assembled in a participatory process including experts and community members with lived experience of these terms. These descriptors combine with a set of bias measurement templates to produce over 450,000 unique sentence prompts, which we use to explore, identify, and reduce novel forms of bias in several generative models. We demonstrate that HolisticBias is effective at measuring previously undetectable biases in token likelihoods from language models, as well as in an offensiveness classifier. We will invite additions and amendments to the dataset, which we hope will serve as a basis for more easy-to-use and standardized methods for evaluating bias in NLP models.

Text analysis in the social sciences often involves using specialized dictionaries to reason with abstract concepts, such as perceptions about the economy or abuse on social media. These dictionaries allow researchers to impart domain knowledge and note subtle usages of words relating to a concept(s) of interest. We introduce the dictionary-assisted supervised contrastive learning (DASCL) objective, allowing researchers to leverage specialized dictionaries when fine-tuning pretrained language models. The text is first keyword simplified: a common, fixed token replaces any word in the corpus that appears in the dictionary(ies) relevant to the concept of interest. During fine-tuning, a supervised contrastive objective draws closer the embeddings of the original and keyword-simplified texts of the same class while pushing further apart the embeddings of different classes. The keyword-simplified texts of the same class are more textually similar than their original text counterparts, which additionally draws the embeddings of the same class closer together. Combining DASCL and cross-entropy improves classification performance metrics in few-shot learning settings and social science applications compared to using cross-entropy alone and alternative contrastive and data augmentation methods.

The European Parliament's co-rapporteurs of the AI Act have proposed expanding the European Commission's revision powers to extend the list of high-risk systems and prohibited practices at a later stage. The eighth batch of compromise amendments on the proposed Artificial Intelligence regulation was shared by leading lawmakers Dragoș Tudorache and Brando Benifei with the representatives of the other political groups last Friday (21 October). The AI Act is a flagship legislative proposal to regulate the development, deployment and use of artificial intelligence. The co-rapporteurs are currently trying to reach a common position with the other political groups, pitching several significant changes to the original wording. The most relevant amendment would significantly extend the Commission's revision powers after the legislation becomes effective.

In Cybersecurity, systems that can learn and adapt to evolving threats are much more competent than " fine-tuned " systems to identify these threats. Consequently, using artificial intelligence (AI) for cybersecurity provides a compelling use case. Typical security systems like firewalls, antivirus or intrusion detection systems (IDS) can only detect threats they are already familiar with. This leaves enough room for zero-day attacks and other matured forms of malware. A security system that's powered by AI can identify evolving threats and even adjusts its defences to restrict the danger until it can be effectively neutralized.

Oct 25 - Tesla Inc (TSLA.O) is under criminal investigation in the United States over claims that the company's electric vehicles can drive themselves, three people familiar with the matter said. The U.S. Department of Justice launched the previously undisclosed probe last year following more than a dozen crashes, some of them fatal, involving Tesla's driver assistance system Autopilot, which was activated during the accidents, the people said. As early as 2016, Tesla's marketing materials have touted Autopilot's capabilities. On a conference call that year, Elon Musk, the Silicon Valley automaker's chief executive, described it as "probably better" than a human driver. Last week, Musk said on another call Tesla would soon release an upgraded version of "Full Self-Driving" software allowing customers to travel "to your work, your friend's house, to the grocery store without you touching the wheel."

Tesla is under criminal investigation in the United States over claims that the company's electric vehicles can drive themselves, three people familiar with the matter said. The US Department of Justice (DoJ) launched the previously undisclosed investigation last year following more than a dozen crashes, some of them fatal, involving Tesla's driver assistance system known as Autopilot, which was activated during the accidents, the people said. As early as 2016, Tesla's marketing materials have touted Autopilot's capabilities. On a conference call that year, Elon Musk, the Tesla chief executive, described it as "probably better" than a human driver. Last week, Musk said on another call Tesla would soon release an upgraded version of "full self-driving" software, allowing customers to travel "to your work, your friend's house, to the grocery store without you touching the wheel".

Dr. Stephen Thaler developed DABUS (Device for Autonomous Bootstrapping of Unified Science), an artificial intelligence (AI) system that can autonomously create patentable inventions. Thaler has filed patent applications in various jurisdictions for two inventions created by DABUS – a food container with side walls having a fractal profile, and a beacon for attracting enhanced attention for example in a search and rescue scenario[1]. In each application, Thaler listed DABUS as the sole inventor, forcing patent offices in various jurisdictions to address the issue of whether an AI system can be an inventor on a patent application. Thus far, the DABUS patent applications have found very limited success in patent offices and courts around the world. In the latest decision, the United States Court of Appeals for the Federal Circuit (CAFC) held that the US Patent Act requires an inventor to be a natural person, and consequently, an AI system cannot be an inventor on a United States patent application.[2] The DABUS applications were initially rejected by the United States Patent and Trademark Office (USPTO).

A Chinese military contractor created a video showing off its terrifying new military technology, revealing a robot attack dog that can dropped off by a drone. The video that was initially released on the verified Weibo account of "Kestrel Defense Blood-Wing," a page affiliated with a Chinese defense contractor, shows a drone hovering over a building and then dropping off a robot on the roof. After the drone flies away, the robot gets up on four legs and then begins to scan for targets around the building with what appears to be some sort of automatic weapons attached to its back. According to a report from WarZone, the weapon mounted on the robot dog is possibly a Chinese QBB-97 light machine gun, which is capable of firing 650 rounds per minute at an effective range of 400 meters. A drone is displayed at a Chinese military parade.

On 8 July 2022, former Japanese Prime Minister Shinzo Abe was delivering a political campaign speech outside the Yamato-Saidaiji Station in Nara City, Japan, when a man approached and shot him in the back using a homemade firearm. Even before Abe died from his injuries, footage of the assassination had been posted online. Social media users began to speculate as to the identity and motive of the killer. On the internet forum 4chan, a site notorious for its anarchic, often hateful trolling, an anonymous user posted a photograph of the video game director Hideo Kojima, claiming this "left-wing extremist" was the perpetrator. If the post was intended to bait the gullible, it worked.

NASA previously announced that it would create a panel to study "unidentified aerial phenomena" (UAP), aka UFOs -- while saying it doesn't believe they're "extraterrestrial in origin." Now, the space agency has unveiled the 16-member panel that will focus on these unclassified sightings, chaired by David Spergel, former head of astrophysics at Princeton University. Other members include Anamaria Berea, a research affiliate at the SETI (Search for Extraterrestrial Life) Institute in California; retired NASA astronaut and test pilot Scott Kelly; and astrophysicists, science journalists and more. The US government is effectively running two tracks of UFO probes. There's also a Pentagon group looking into UAPs reported by military pilots and investigated by US defense and intelligence officials.