The number of sick and disabled people out of work is putting the UK is at risk of an economic inactivity crisis that threatens the country's prosperity, according to a new report. There were 800,000 more people out of work now than in 2019 due to health conditions, costing employers £85bn a year, according to the review by former John Lewis boss Sir Charlie Mayfield. The problem could worsen without intervention, but Sir Charlie, who will lead a taskforce aimed at helping people return to work, said this was not inevitable. The move has been broadly welcomed, but some business groups said Labour's Employment Rights Bill included some disincentives to hiring people with existing illnesses. One in five working age people were out of work, and not seeking work, according to the report, which was commissioned by the Department for Work and Pensions by produced independently.

The prevalence of unwarranted beliefs, spanning pseudoscience, logical fallacies, and conspiracy theories, presents substantial societal hurdles and the risk of disseminating misinformation. Utilizing established psychometric assessments, this study explores the capabilities of large language models (LLMs) vis-a-vis the average human in detecting prevalent logical pitfalls. We undertake a philosophical inquiry, juxtaposing the rationality of humans against that of LLMs. Furthermore, we propose methodologies for harnessing LLMs to counter misconceptions, drawing upon psychological models of persuasion such as cognitive dissonance theory and elaboration likelihood theory. Through this endeavor, we highlight the potential of LLMs as personalized misinformation debunking agents.

The demand for accurate and efficient verification of information in texts generated by large language models (LMs) is at an all-time high, but remains unresolved. Recent efforts have focused on extracting and verifying atomic facts from these texts via prompting LM evaluators. However, we demonstrate that this method of prompting is unreliable when faced with incomplete or inaccurate reference information. We introduce Facts as a Function (FaaF), a new approach to the fact verification task that leverages the function-calling capabilities of LMs. FaaF significantly enhances the ability of LMs to identify unsupported facts in texts, while also improving efficiency and significantly lowering costs compared to prompt-based methods. Additionally, we propose a framework for evaluating factual recall in Retrieval Augmented Generation (RAG) systems, which we employ to compare prompt-based and FaaF methods using various LMs under challenging conditions.

The Lipstick Index, as it's known, was a phrase coined by Leonard Lauder, chairman of the board at Estee Lauder, in the early noughties when it became clear in times of economic crisis, sales of color cosmetics - in particular lipstick - soar as an affordable way to treat yourself. Last year, sales of cosmetics plummeted. With bustling make-up counters in department stores closed for much of 2020, sales of designer brand cosmetics were down by more than 40% according to market research firm NPD, which equates to a loss of £500 million (around $689 million and AU$902 million). Meanwhile, sales of more affordable cosmetics in supermarkets fell by 22% in the UK, according to the Top Products survey from retail trade magazine, The Grocer, adding a further £183 million loss (around $256 million / AU$218 million). A combination of the rise of working from home and mandatory masks meant thousands of us, including this writer, ditched our make-up bags altogether.

Pandemic defines the global outbreak of a disease having a high transmission rate. The impact of a pandemic situation can be lessened by restricting the movement of the mass. However, one of its concomitant circumstances is an economic crisis. In this article, we demonstrate what actions an agent (trained using reinforcement learning) may take in different possible scenarios of a pandemic depending on the spread of disease and economic factors. To train the agent, we design a virtual pandemic scenario closely related to the present COVID-19 crisis. Then, we apply reinforcement learning, a branch of artificial intelligence, that deals with how an individual (human/machine) should interact on an environment (real/virtual) to achieve the cherished goal. Finally, we demonstrate what optimal actions the agent perform to reduce the spread of disease while considering the economic factors. In our experiment, we let the agent find an optimal solution without providing any prior knowledge. After training, we observed that the agent places a long length lockdown to reduce the first surge of a disease. Furthermore, the agent places a combination of cyclic lockdowns and short length lockdowns to halt the resurgence of the disease. Analyzing the agent’s performed actions, we discover that the agent decides movement restrictions not only based on the number of the infectious population but also considering the reproduction rate of the disease. The estimation and policy of the agent may improve the human-strategy of placing lockdown so that an economic crisis may be avoided while mitigating an infectious disease.

COVID-19 pandemic has affected the entire world. Many people lost their jobs, kids stay at home, and the economic crisis is disastrous. The question of "how will the world be after COVID-19" is of high interest. Many futurists predict a different world, where we should rethink public spaces and believes that the memory of the COVID-19 lockdown will remain for a long time (Del Bello, 2020). This information presents a sad situation, where the COVID-19 continues to spreads with tragic death cases.

A drone loaded with explosives detonated near a military event where Venezuelan President Nicolas Maduro was giving a speech, but he escaped unharmed in what the embattled leader called an assassination attempt. Seven people were wounded on Saturday in the apparent attack, which came as Maduro celebrated the National Guard's 81st anniversary in the capital, Caracas. Maduro later said "everything points" to a right-wing plot that an initial investigation suggested was linked to Colombia and the US state of Florida, where many Venezuelan exiles live. Several perpetrators were caught, he said, without elaborating. "This was an assassination attempt, they tried to assassinate me," Maduro said in a televised address.

"In an era of post-truth politics, driven by the 24-hour news cycle, diminishing trust in institutions, rich visual media, and the ubiquity and velocity of social networked spaces, how do we identify information that is tinted -- information that is incomplete, that may help affirm our existing beliefs or support someone's agenda, or that may be manipulative -- effectively driving a form of propaganda?" (Lotan, Gilad. Over 70 years ago, Karl Polanyi established the term "double movement" Reviewing the most recent developments, politically, economically and socially, one may understand the value of his vision and why his ideas have been increasingly discussed lately. Propaganda 2.0 -- Post-truth politics The Definition of Post-truth politics Adjective: "relating to or denoting circumstances in which objective facts are less influential in shaping public opinion than appeals to emotion and personal belief," Why post-truth rhetoric is propaganda This definition not only sounds familiar. The most recent events in global politics give incessant evidence that what is described as an "era" is nothing but history repeating itself. From the economic and social context to commonly used rhetoric.