In 2023, a Belgian man reportedly ended his life after developing eco-anxiety and confiding in an AI chatbot over six weeks about the future of the planet. Without those conversations, his widow reportedly told the Belgian outlet La Libre, "he would still be here". In April this year, a 35-year-old Florida man was shot and killed by police in another chatbot-related incident: his father later told media that the man had come to believe an entity named Juliet was trapped inside ChatGPT, and then killed by OpenAI. When the man, who reportedly struggled with bipolar disorder and schizophrenia, was confronted by police, he allegedly charged at them with a knife. The wide availability of chatbots in the past few years has apparently led some to believe there is a ghost in the machine – one that is conscious, capable of loving and being loved.

The H-1B visa program was intended to bring in specialized talent from abroad, but instead it has become a tool for employers to hire lower-cost labor for ordinary jobs. The result is a distorted job market, where highly skilled workers are being squeezed out of the H-1B visa program by spam applications for ordinary workers who then take entry-level positions that are already in short supply. This misuse of H-1B visas has a negative synergy with growing impact of AI on the job market and is part of a larger problem that urgently needs attention. The impact of this visa-farming problem is particularly acute among young people and recent college graduates, who face a bleak job market despite moderate overall unemployment rates. According to government data, the ratio of unemployment for college grads under 25 to those over 25 has hit an all-time high of more than four to one.

ChatGPT does amazingly well at communicating with people in English. Only 15% of ChatGPT users are from the US, where Standard American English is the default. But the model is also commonly used in countries and communities where people speak other varieties of English. Over 1 billion people around the world speak varieties such as Indian English, Nigerian English, Irish English, and African-American English. Speakers of these non-"standard" varieties often face discrimination in the real world.

Medical tools enabled with artificial intelligence (AI) can greatly improve health care by helping with problem-solving, automating tasks, and identifying patterns. AI can aid in diagnoses, predict patients' risk of developing certain illnesses, and help determine the communities most in need of preventative care. But AI products can also replicate--and worse, exacerbate--existing biases and disparities in patients' care and health outcomes. Alleviating these biases requires first understanding where they come from. Christina Silcox, Ph.D., research director for digital health at the Duke-Margolis Center for Health Policy, and her team identified four sources of AI bias and ways to mitigate them in a recent report funded by The Pew Charitable Trusts. She spoke with Pew about the findings.

Four projects have received a share of £1.4million to use artificial intelligence to address racial and ethical health inequalities. The funding, a joint programme with the NHSX AI Lab and the Health Foundation, aims to ensure healthcare solutions don't "exacerbate existing health inequalities". The four projects range from using artificial intelligence (AI) to investigate disparities in maternal health outcomes, to developing standards and guidance to ensure that datasets for training and testing AI systems are inclusive and generalisable. Dr Indra Joshi, director of the AI Lab at NHSX, said: "As we strive to ensure NHS patients are amongst the first in the world to benefit from leading AI, we also have a responsibility to ensure those technologies don't exacerbate existing health inequalities. "These projects will ensure the NHS can deploy safe and ethical artificial intelligence tools that meet the needs of minority communities and help our workforce deliver patient-centred and inclusive care to all." Speaking exclusively to The Guardian today (October 20) health secretary Sajid Javid said he was committed to "removing barriers" in the NHS. "As the first health and social care secretary from an ethnic minority background, I care deeply about tackling the disparities which exist within the healthcare system.

A dress worn this week by Democratic Congresswoman Alexandria Ocasio-Cortez (D-NY), which bore the message "tax the rich," set off a wave of debate over how best to address wealth inequality, as Congress weighs a $3.5 trillion spending bill that includes tax hikes on corporations and high-earning individuals. The debate coincides with the ongoing pandemic in which billionaires, many of whom are tech company founders, have added $1.8 trillion in wealth while consumers have come to depend increasingly on services like e-commerce and teleconference, according to a report released last month by the Institute for Policy Studies. In a new interview, artificial intelligence expert Kai Fu-Lee -- who worked as an executive at Google (GOOG, GOOGL), Apple (AAPL), and Microsoft (MSFT) -- attributed the rise of wealth inequality in part to the tech boom in recent decades, predicting that the trend will worsen in coming years with the continued emergence of AI. "We can just already see all the internet companies," says Lee, the co-author of a new book entitled "AI 2041: Ten Visions for Our Future." "Without AI, they probably would be only worth half of what they're worth, because AI helped them monetize." "When it's simultaneously making a small number of people ultra-rich and making many people jobless," he says.

Technology, artificial intelligence and automation are supposed to solve our biggest problems, not create new ones or exacerbate existing issues. Unbeknownst to many, big tech is actually putting a huge burden on the environment. In a study assessing the energy consumption required to train several common large AI models, Researchers at the University of Massachusetts Amherst said artificial intelligence emissions can be over 626,000 pounds of carbon dioxide, which is about 5 times as much the lifetime emissions of an average car. According to research firm IDC, spending on AI systems is exploding, with the figure expected to hit nearly $98 billion in 2023, more than 3.5 times the $37.5 billion being spent this year. The U.S. is expected to deliver more than half of that spending through the forecast, which will be led by the retail and banking industries, according to IDC.

AI is disrupting every area of life, including how organizations find talent. Companies are generally aware of the ROI that comes from finding the right person for the right job. McKinsey estimated that, for highly complex roles, stars can be expected to produce 800% more than average performers. And a recent Harvard Business School study showed that there are even bigger benefits to avoiding toxic workers. Despite this crucial role of talent, organizations are still unable to attract the right talent, relying more on intuitive rather than data-driven talent identification practices -- especially at the top, where the stake are actually highest. Indeed, too many leaders are hired on the basis of their technical expertise, political influence, or interview performance.

The robots will someday take our jobs. But not all our jobs, and we don't really know how many. Nor do we understand which jobs will be eliminated and which will be transitioned into what some say will be better, less tedious work. What we do know is that automation and artificial intelligence will affect Americans unevenly, according to data from McKinsey and the 2016 US Census that was analyzed by the Brookings think tank. Young people -- especially those in rural areas or who are underrepresented minorities -- will have a greater likelihood of having their jobs replaced by automation.

Recent breakthroughs in machine learning and artificial intelligence (A.I.) have prompted breathless speculation about their national security applications. Yet most of that work has focused narrowly on their implications for autonomous weapons systems, rather than on the broader security environment. Apart from Michael Horowitz and a handful of others, few scholars have sketched out how A.I. might affect core questions of international relations and foreign policy. One key challenge stands out: What influence will A.I. have on security dilemmas between great powers? With the two leading producers of A.I., the United States and China, already eyeing each other warily, the question is far from an idle one.