Staff at the UK's leading artificial intelligence institute have raised concerns about the organisation's governance and internal culture in a whistleblowing complaint to the charity watchdog. The Alan Turing Institute (ATI), a registered charity with substantial state funding, is under government pressure to overhaul its strategic focus and leadership after an intervention last month from the technology secretary, Peter Kyle. In a complaint to the Charity Commission, a group of current ATI staff raise eight points of concern and say the institute is in danger of collapse due to government threats over its funding. The complaint alleges that the board of trustees, chaired by the former Amazon UK boss Doug Gurr, has failed to fulfil core legal duties such as providing strategic direction and ensuring accountability, with staff alleging a letter of no confidence was delivered last year and not acted upon. A spokesperson for ATI said the Charity Commission had not been in touch with the institute about any complaints that may have been sent to the organisation.

Primary healthcare is a crucial strategy for achieving universal health coverage. South Asian countries are working to improve their primary healthcare system through their country specific policies designed in line with WHO health system framework using the six thematic pillars: Health Financing, Health Service delivery, Human Resource for Health, Health Information Systems, Governance, Essential Medicines and Technology, and an addition area of Cross-Sectoral Linkages [11]. Measuring the current accessibility of healthcare facilities and workforce availability is essential for improving healthcare standards and achieving universal health coverage in developing countries. Data-driven surveillance approaches are required that can provide rapid, reliable, and geographically scalable solutions to understand a) which communities and areas are most at risk of inequitable access and when, b) what barriers to health access exist, and c) how they can be overcome in ways tailored to the specific challenges faced by individual communities. We propose to harness current breakthroughs in Earth-observation (EO) technology, which provide the ability to generate accurate, up-to-date, publicly accessible, and reliable data, which is necessary for equitable access planning and resource allocation to ensure that vaccines, and other interventions reach everyone, particularly those in greatest need, during normal and crisis times. This requires collaboration among countries to identify evidence based solutions to shape health policy and interventions, and drive innovations and research in the region.

Artificial intelligence (AI) could lead to UK health services that disadvantage women and ethnic minorities, scientists are warning. They are calling for biases in the systems to be rooted out before their use becomes commonplace in the NHS. They fear that without that preparation AI could dramatically deepen existing health inequalities in our society. The researchers examined the state of the art approach to AI used by hospitals worldwide and found it had a 70 per cent success rate in predicting liver disease from blood tests. But they uncovered a wide gender gap underneath – with 44 per cent of cases in women missed, compared with 23 per cent of cases among men.

Artificial intelligence (AI) could lead to UK health services that disadvantage women and ethnic minorities, scientists are warning. They are calling for biases in the systems to be rooted out before their use becomes commonplace in the NHS. They fear that without that preparation AI could dramatically deepen existing health inequalities in our society. The researchers examined the state of the art approach to AI used by hospitals worldwide and found it had a 70 per cent success rate in predicting liver disease from blood tests. But they uncovered a wide gender gap underneath – with 44 per cent of cases in women missed, compared with 23 per cent of cases among men.

Biases in artificial intelligence will aim to be eradicated in a world first as the NHS in England trials a new approach to the ethical adoption of AI in healthcare. AIAs designed by the Ada Lovelace Institute will be piloted to support researchers and developers to assess the possible risks and biases of AI systems to patients and the public before they can access NHS data. While artificial intelligence has the potential to support health and care workers to deliver better care for people, it could also exacerbate existing health inequalities if concerns such as algorithmic bias aren't accounted for. Innovation minister Lord Kamall said: "While AI has great potential to transform health and care services, we must tackle biases which have the potential to do further harm to some populations as part of our mission to eradicate health disparities. "This pilot once again demonstrates the UK is at the forefront of adopting new technologies in a way that is ethical and patient-centred.

Biases in artificial intelligence will aim to be eradicated in a world first as the NHS in England trials a new approach to the ethical adoption of AI in healthcare. Algorithmic Impact Assessment (AIA), designed by the Ada Lovelace Institute, will be piloted to support researchers and developers to assess the possible risks and biases of AI systems to patients and the public before they can access NHS data. While artificial intelligence has the potential to support health and care workers to deliver better care for people, it could also exacerbate existing health inequalities if concerns such as algorithmic bias aren't accounted for. While AI has great potential to transform health and care services, we must tackle biases which have the potential to do further harm to some populations as part of our mission to eradicate health disparities. This pilot once again demonstrates the UK is at the forefront of adopting new technologies in a way that is ethical and patient-centred.

NHSX' NHS AI Lab and the Health Foundation have today awarded £1.4m to four projects to address racial and ethnic health inequalities using artificial intelligence (AI). The winning projects range from using 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. The NHS AI Lab introduced the AI Ethics Initiative to support research and practical interventions that complement existing efforts to validate, evaluate and regulate AI-driven technologies in health and care, with a focus on countering health inequalities. Today's announcement is the result of the Initiative's partnership with The Health Foundation on a research competition, enabled by NIHR, to understand and enable opportunities to use AI to address inequalities and to optimise datasets and improve AI development, testing and deployment. '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.

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.

The £1.4m funding is financed by the NHS' AI Lab – called NHSX – and The Health Foundation, with the projects aiming to utilise AI to address racial and ethnic health inequalities in the UK. The selected initiatives will implement the technology in a broad range of investigations, from assessing disparities in maternal health outcomes to designing standards and guidance to ensure AI systems are inclusive and generalisable. The NHS AI lab introduced the AI Ethics Initiative in March 2021 to assist research and practical interventions that enhance existing efforts to validate, evaluate, and regulate AI-based technologies in the healthcare sector to mitigate health inequalities. This considerable funding results from their partnership with The Health Foundation on a research competition, which the NIHR enabled. The endeavour saw the organisations collaborate to explore and create opportunities to employ AI to address health inequalities and optimise datasets to improve AI's development, testing, and deployment.

Life-expectancy is a complex outcome driven by genetic, socio-demographic, environmental and geographic factors. Increasing socio-economic and health disparities in the United States are propagating the longevity-gap, making it a cause for concern. Earlier studies have probed individual factors but an integrated picture to reveal quantifiable actions has been missing. Amidst growing concerns about the further widening of healthcare inequality and differential access created by Artificial Intelligence, it is imperative to explore it's potential for illuminating biases and enabling transparent policy decisions. In this work, we reveal actionable interventions for decreasing the longevity-gap in the United States by analyzing a County-level data resource with healthcare, socio-economic, behavioral, education and demographic features. We learn an ensemble-averaged structure, draw inferences using the joint probability distribution and extend it to a Bayesian Decision Network for identifying policy actions. We draw quantitative estimates for the positive roles of diversity, preventive-care quality and stable-families within the unified framework of our decision network. Finally, we make this analysis and dashboard available as an interactive web-application for enabling users and policy-makers to validate our insights on bridging the longevity-gap and explore the ones beyond reported in this work.