We present an ontology design pattern for modeling Names as part of Roles, to capture scenarios where an Agent performs different Roles using different Names associated with the different Roles. Examples of an Agent performing a Role using different Names are rather ubiquitous, e.g., authors who write under different pseudonyms, or different legal names for citizens of more than one country. The proposed pattern is a modified merger of a standard Agent Role and a standard Name pattern stub.

Over the past half century, there have been several false dawns during which the "arrival" of world-changing artificial intelligence (AI) has been heralded. Tempting fate, the authors believe the age of AI has, indeed, finally arrived. Powerful image generators, such as DALL-E2 and Midjourney have suddenly allowed anyone with access the ability easily to create rich and complex art. In a similar vein, text generators, such as GPT3.5 (including ChatGPT) and BLOOM, allow users to compose detailed written descriptions of many topics of interest. And, it is even possible now for a person without extensive expertise in writing software to use AI to generate code capable of myriad applications. While AI will continue to evolve and improve, probably at a rapid rate, the current state of AI is already ushering in profound changes to many different sectors of society. Every new technology challenges the ability of humanity to govern it wisely. However, governance is usually viewed as both possible and necessary due to the disruption new technology often poses to social structures, industries, the environment, and other important human concerns. In this article, we offer an analysis of a range of interactions between AI and governance, with the hope that wise decisions may be made that maximize benefits and minimize costs. The article addresses two main aspects of this relationship: the governance of AI by humanity, and the governance of humanity by AI. The approach we have taken is itself informed by AI, as this article was written collaboratively by the authors and ChatGPT.

Subset selection tasks, arise in recommendation systems and search engines and ask to select a subset of items that maximize the value for the user. The values of subsets often display diminishing returns, and hence, submodular functions have been used to model them. If the inputs defining the submodular function are known, then existing algorithms can be used. In many applications, however, inputs have been observed to have social biases that reduce the utility of the output subset. Hence, interventions to improve the utility are desired. Prior works focus on maximizing linear functions -- a special case of submodular functions -- and show that fairness constraint-based interventions can not only ensure proportional representation but also achieve near-optimal utility in the presence of biases. We study the maximization of a family of submodular functions that capture functions arising in the aforementioned applications. Our first result is that, unlike linear functions, constraint-based interventions cannot guarantee any constant fraction of the optimal utility for this family of submodular functions. Our second result is an algorithm for submodular maximization. The algorithm provably outputs subsets that have near-optimal utility for this family under mild assumptions and that proportionally represent items from each group. In empirical evaluation, with both synthetic and real-world data, we observe that this algorithm improves the utility of the output subset for this family of submodular functions over baselines.

While the systemic brutality used by Colombian police to quell national protests in 2021 was real and is well documented, photos recently used by Amnesty International to highlight the issue were not. The international human rights advocacy group has come under fire for posting images generated by artificial intelligence in order to promote their reports on social media – and has since removed them. The images, including one of a woman being dragged away by police officers, depict the scenes during protests that swept across Colombia in 2021. But any more than a momentary glance at the images reveals that something is off. The faces of the protesters and police are smoothed-off and warped, giving the image a dystopian aura.

BOTTLED UP - Bud Light shuts down dissent as controversy over trans activist partnership rages. Continue reading … 'AN ATTACK' - This prairie chicken is Biden's latest weapon in his war on fossil fuels, writes Kansas Attorney General Kris Kobach. 'HORRIFIC' - Interstate crash involving 72 vehicles leaves several people dead, many more injured. GRISLY DISCOVERY - Seven bodies found in search for missing teen girls seen traveling with convicted rapist. HOLLYWOOD ON HOLD - Movie, TV writers to strike for the first time in 15 years after failed negotiations.

Tom Newhouse, vice president of Convergence Media, discusses the potential impact of artificial intelligence on elections after an RNC AI ad garnered attention. Republicans are less convinced than Democrats that the federal government needs to impose regulations on artificial intelligence systems and are even more skeptical on whether the government is up to the task, according to a new Fox News poll. The poll of registered voters shows a noticeable gap between the two parties on the question of whether and how to regulate AI, a sign that the increasingly important issue could get hung up in politics as it advances in Washington. When asked how important it is for the federal government to regulate AI, 82% of Democrats said "very" or "somewhat," compared to 71% of Republicans. That was one of the bigger splits in a poll that found 76% of respondents saw some importance to federal regulation.

Sentence Boundary Detection (SBD) is one of the foundational building blocks of Natural Language Processing (NLP), with incorrectly split sentences heavily influencing the output quality of downstream tasks. It is a challenging task for algorithms, especially in the legal domain, considering the complex and different sentence structures used. In this work, we curated a diverse multilingual legal dataset consisting of over 130'000 annotated sentences in 6 languages. Our experimental results indicate that the performance of existing SBD models is subpar on multilingual legal data. We trained and tested monolingual and multilingual models based on CRF, BiLSTM-CRF, and transformers, demonstrating state-of-the-art performance. We also show that our multilingual models outperform all baselines in the zero-shot setting on a Portuguese test set. To encourage further research and development by the community, we have made our dataset, models, and code publicly available.

Since its establishment in 1914, the US Federal Trade Commission has stood as a bulwark against the fraud, deception, and shady dealings that American consumers face every day -- fining brands that "review hijack" Amazon listings, making it easier to cancel magazine subscriptions and blocking exploitative ad targeting. On Monday, Michael Atleson, Attorney, FTC Division of Advertising Practices, laid out both the commission's reasoning for how emerging generative AI systems like ChatGPT, Dall-E 2 could be used to violate the FTC Act's spirit of unfairness, and what it would do to companies found in violation. "Under the FTC Act, a practice is unfair if it causes more harm than good," Atleson said. "It's unfair if it causes or is likely to cause substantial injury to consumers that is not reasonably avoidable by consumers and not outweighed by countervailing benefits to consumers or to competition." He notes that the new generation of chatbots like Bing, Bard and ChatGPT can be used to influence the user's, "beliefs, emotions, and behavior."

More than 150 workers whose labor underpins the AI systems of Facebook, TikTok and ChatGPT gathered in Nairobi on Monday and pledged to establish the first African Content Moderators Union, in a move that could have significant consequences for the businesses of some of the world's biggest tech companies. The current and former workers, all employed by third party outsourcing companies, have provided content moderation services for AI tools used by Meta, Bytedance, and OpenAI--the respective owners of Facebook, TikTok and the breakout AI chatbot ChatGPT. Despite the mental toll of the work, which has left many content moderators suffering from PTSD, their jobs are some of the lowest-paid in the global tech industry, with some workers earning as little as $1.50 per hour. As news of the successful vote to register the union was read out, the packed room of workers at the Mövenpick Hotel in Nairobi burst into cheers and applause, a video from the event seen by TIME shows. Confetti fell onto the stage, and jubilant music began to play as the crowd continued to cheer.

Paedophiles are using a popular new artificial intelligence (AI) platform to transform real photos of children into sexualised images, it has been revealed. It has led to warnings to parents to be careful about the pictures of their children they're posting online. The images were found on the US AI image generator Midjourney, which much like ChatGPT uses prompts to deliver an output, although these usually consist of pictures rather than words. The platform is used by millions and has churned out such realistic images that people across the world have been fooled by them, including users on Twitter. An image of Pope Francis donning a huge white puffer jacket with a cross hanging from his neck sent social media users into a frenzy earlier this year.