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"The independent review on equity in medical devices once again highlights the multiple ways in which medical technology development can lead to solutions whereby the benefits are distributed inequitably across society, or can further exacerbate health inequalities (UK report reveals bias within medical tools and devices, 11 March). While the report is welcome, the challenge facing scientists and engineers is how to innovate medical devices differently to respond to longstanding societal biases and inequalities."

"In a sharply worded warning, the cancer experts say that 'novel solutions' such as new diagnostic tests have been wrongly hyped as 'magic bullets' for the cancer crisis, but 'none address the fundamental issues of cancer as a systems problem'. A 'common fallacy' of NHS leaders is the assumption that new technologies can reverse inequalities, the authors add. The reality is that tools such as AI can create 'additional barriers for those with poor digital or health literacy'. 'We caution against technocentric approaches without robust evaluation from an equity perspective,' the paper concludes."

A cool bit of tech that should help educated young brits on coding and other things to help them in jobs later in life although this could put the younger people at an advantage due to the inequality between older students and younger ones

" Critics have pointed out that the old computing adage "garbage in, garbage out" also applies to ML. If the data from which a machine "learns" is biased, then the outputs will reflect those biases. And this could become generalised: we may have created a technology that - however good it is at recommending films you might like - may actually morph into a powerful amplifier of social, economic and cultural inequalities."

"The problem, he believes, is that total decentralization inevitably increases wealth inequality. He pointed me to a simulation he designed last year in which bouncing balls demonstrate the theory that "the rich actually always get richer, no matter what." "

"Some of Britain's biggest retailers, including Tesco, John Lewis and Sainsbury's, have been urged to pull out of a new policing strategy amid warnings it risks wrongly criminalising people of colour, women and LGBTQ+ people. A coalition of 14 human rights groups has written to the main retailers - also including Marks & Spencer, the Co-op, Next, Boots and Primark - saying that their participation in a new government-backed scheme that relies heavily on facial recognition technology to combat shoplifting will "amplify existing inequalities in the criminal justice system"."

""Equal access does imply equal opportunities," says the report, which goes on to point out that while anyone can use the internet to learn about the world, improve their skills or apply for a well-paid job, disadvantaged students are less likely to be aware of the opportunities that digital technology offers. "They may not have the knowledge or skills required to turn online opportunities into real opportunities," the report says."

"At the heart of the problem that troubles Ming is the training that computer engineers receive and their uncritical faith in AI. Too often, she says, their approach to a problem is to train a neural network on a mass of data and expect the result to work fine. She berates companies for failing to engage with the problem first - applying what is already known about good employees and successful students, for example - before applying the AI."