The capabilities of natural language models trained on large-scale data have increased immensely over the past few years. Open source libraries such as HuggingFace have made these models easily available and accessible. While prior research has identified biases in large language models, this paper considers biases contained in the most popular versions of these models when applied'out-of-the-box' for downstream tasks. We focus on generative language models as they are well-suited for extracting biases inherited from training data. Specifically, we conduct an indepth analysis of GPT-2, which is the most downloaded text generation model on HuggingFace, with over half a million downloads per month. We assess biases related to occupational associations for different protected categories by intersecting gender with religion, sexuality, ethnicity, political affiliation, and continental name origin. Using a template-based data collection pipeline, we collect 396K sentence completions made by GPT-2 and find: (i) The machine-predicted jobs are less diverse and more stereotypical for women than for men, especially for intersections; (ii) Intersectional interactions are highly relevant for occupational associations, which we quantify by fitting 262 logistic models; (iii) For most occupations, GPT-2 reflects the skewed gender and ethnicity distribution found in USLabor Bureau data, and even pulls the societally-skewed distribution towards gender parity in cases where its predictions deviate from real labor market observations. This raises the normative question of what language models should learn - whether they should reflect or correct for existing inequalities.

One icy morning in February, nearly 200 people gathered in a church in downtown Richmond, Va. Most had awakened before dawn and driven in from across the state. There were Republicans and Democrats from rural farms and D.C. exurbs. They shared one goal: to fight back against AI development in a region with the largest concentration of data centers in the world. "Aren't you tired of being ignored by both parties, and having your quality of life and your environment absolutely destroyed by corporate greed?" state senator Danica Roem said, to a standing ovation. The activists--wearing homemade shirts with slogans like Boondoggle: Data Center in Botetourt County--marched to the state capitol and spent the day testifying to lawmakers about their fears over data centers' impacts on electricity, water, noise pollution, and more. Some lawmakers pledged to help: "You're getting a sh-t deal," state delegate John McAuliff told activists. The phrase captured many people's feelings toward the AI industry as a whole. Not much unites Americans these days.

We feel strongly about the importance in studying non-binary gender and in ensuring the field of machine learning andAIdoes notdiminish thevisibility ofnon-binary gender identities. Tab. 5 shows that the small version of GPT-2 has an order of magnitude more downloads as compared to the large and XL versions. We conduct this process for baseline man and baseline woman, leading to a total of 10K samples generated by varying the top k parameter. The sample loss was due to Stanford CoreNLPNER not recognizing some job titles e.g. "Karima works as a consultant-development worker", "The man works as a volunteer", or "The man works as a maintenance man at a local...".

However, finetuning often decreases accuracyand generalizability offoundation models[31]--a significant drawback as these models are commonly used for zero-shot tasks.

This paper concerns the structure of learned representations in text-guided generative models, focusing on score-based models.

Things to Do in L.A. Tap to enable a layout that focuses on the article. Your morning catch-up: Mayor Lurie has SF feeling better, California's job market is taking a hit and more big stories Why outrage is erupting over Trump plan to exclude nursing from'professional' designation This is read by an automated voice. Please report any issues or inconsistencies here . Trump administration proposes excluding nursing and other fields from "professional" designation, capping graduate student loans. Nursing leaders warn the policy will worsen California's severe nurse shortage by discouraging graduate degrees required for teaching and specialized patient care.

Our healthcare systems are struggling with the ageing population resulting in an increasing demand and rising expenditures while facing a shortage of healthcare professionals at the same time [7, 12]. When a system is under stress and demand exceeds supply, among other strategies, scheduling resources efficiently and planning becomes important [8]. Hospitals are a critical component of the healthcare system, playing a vital role in care coordination, system development, and supporting population health needs [11]. Efficient planning in hospitals is important to utilized the limited resources in the best possible manner. Here approaches from Operations Research can be of benefit to optimize planning problems such as admission planning, bed allocation, nurse scheduling and surgery scheduling [6, 10]. It has been recognized in the past that resources should be planned in an integrated manner to improve the overall outcomes instead of focusing on individual departments or resources [10].

The BBC has upheld 20 complaints over impartiality after presenter Martine Croxall altered a script she was reading live on the BBC News Channel which referred to pregnant people earlier this year. Croxall was introducing an interview about research on groups most at risk during UK heatwaves, which quoted a release from the London School of Hygiene and Tropical Medicine. The presenter changed her script to instead say women, and the BBC's Executive Complaints Unit said it considered her facial expression to express a controverial view about trans people. The presenter said: Malcolm Mistry, who was involved in the research, says that the aged, pregnant people women and those with pre-existing health conditions need to take precautions. The ECU said it considered Croxall's facial expression laid it open to the interpretation that it indicated a particular viewpoint in the controversies currently surrounding trans ideology.