Britain’s health secretary, Yvette Cooper, told MPs on November 4 that artificial intelligence could mean the National Health Service in England needs fewer staff in some areas. Giving evidence to the House of Commons health committee, she said the technology “will lead to us wanting to increase certain areas but also to potentially reduce certain areas as well.” She named no jobs and announced no cuts. She also confirmed that the 10-year workforce plan, which will set how many doctors, nurses and other staff the health service trains and hires, has been delayed again and will now arrive in the new year, with no date. Cooper said predicting staff needs is much harder than it was two or three years ago.

The direction she described moves people away from hospitals. She told the committee she wants more emphasis on family doctors and community mental health care, and less on the hospital workforce over time. Practice nurse leaders complained that nurses were left out, and the Royal College of Nursing had already asked in June for the plan to be paused, arguing that it counted on AI savings without enough evidence. A separate independent review of NHS productivity and AI, led by Mark Bailie, a non-executive director of NHS England, is due in early 2027. Cooper suggested giving universities and training colleges clearer signals about where staff are needed, but for now they must plan student places without the official numbers.

Seven in every 100 adults surveyed in Australia, the United Kingdom and the United States say someone has used AI to make or spread sexual images of them without their consent. The survey of over 7,200 people, led by Nicola Henry of RMIT University in Australia and published in the International Journal of Human–Computer Interaction, counted three kinds of abuse since age 18. These were having a nude or sexual image of oneself created or altered with AI tools, having such an image shared, and being threatened with its release. Men reported it at over twice the rate of women, 10.2% against 3.8%, and rates were also higher among people under 35, people from racial and ethnic minorities and people with disabilities.

Women reported more fear for their safety and more damage to their mental and physical health. Almost 87% of all victims described at least one harm to their health, relationships, work or finances. Henry warned that the real number may be higher, because some people never find out that a fake image of them exists. The research was funded by Google, and a Google researcher, Rebecca Umbach, co-wrote it. Henry points to Australia’s proposed digital duty of care, which would require online services to prevent foreseeable harm instead of reacting after it happens. She also asks for better education, accessible support for victims and for technology companies to build safeguards into AI image tools from the start.

Schools are being encouraged to adopt AI tools partly on the strength of research reviews that report large gains in learning, and a new audit argues those reviews do not hold up. Patrick O’Neill, an associate professor at Ivy Tech Community College in Indiana, examined 14 meta-analyses, studies that combine the results of many smaller studies into one overall estimate. In a preprint discussed by Education Week on November 2, he concludes that none of them gives a valid basis for its claims. None clearly defined the kind of AI use it was measuring, and none properly checked for publication bias, the tendency for studies with good results to be published while disappointing ones are left out.

Some of the problems were basic. A study of an elementary school physical education class was grouped with one on simulations for medical students, a few included studies did not use AI at all, and results as different as test knowledge, motivation and mental health were added together. Some of the underlying studies contained impossible statistics or references that appear to be invented, including ChatGPT research dated before the tool was public. The reviews appeared in respected journals and have been cited thousands of times. O’Neill asks journals to require authors to share their data and to tighten peer review. A separate Stanford review of more than 800 studies found only 20 with a strong cause-and-effect design, and none of those involved schoolchildren.