New device finds breast cancer like earthquake detection

New device finds breast cancer like earthquake detection

Jessica Fitzjohn, a postdoctoral fellow at the University of Canterbury, demonstrates the novel breast cancer screening device.

University of Canterbury.

Mammograms are necessary breast cancer checks for women as they reach the recommended screening age between 40 and 50 years. Yet, many find the procedure uncomfortable. “I have large breasts, and to be able to image the full breast, the radiographer had to manipulate my breast within the machine, which took time and was quite uncomfortable,” recalls Angela, who preferred not to disclose her last name.

Breast cancer is the most widespread cancer in the world, affecting 2.3 million women in 2020. Screening exams such as mammograms can help find breast cancer early, leading to timely diagnosis and treatment. If this type of cancer is detected before the disease has spread, the 5-year survival rate is 99 percent. But some women forgo mammograms due to concerns about radiation or painful compression of breasts. Other issues, such as low income and a lack of access to healthcare, can also serve as barriers, especially for underserved populations.

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Rina Diane Caballar
Rina Diane Caballar is a former software engineer turned freelance writer based in New Zealand. She covers tech and its intersections with science, society, and the environment. You can find her on https://rinacaballar.com/
Researchers probe extreme gene therapy for severe alcoholism

When all traditional therapeutic approaches fail for alcohol abuse disorder, a radical gene therapy might be something to try in the future.

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Story by Freethink

A single shot — a gene therapy injected into the brain — dramatically reduced alcohol consumption in monkeys that previously drank heavily. If the therapy is safe and effective in people, it might one day be a permanent treatment for alcoholism for people with no other options.

The challenge: Alcohol use disorder (AUD) means a person has trouble controlling their alcohol consumption, even when it is negatively affecting their life, job, or health.

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Kristin Houser
Kristin Houser is a staff writer at Freethink, where she covers science and tech. Her written work has appeared in Business Insider, NBC News, and the World Economic Forum’s Agenda, among other publications, and Stephen Colbert once talked about a piece on The Late Show, to her delight. Formerly, Kristin was a staff writer for Futurism and wrote several animated and live action web series.
Massive benefits of AI come with environmental and human costs. Can AI itself be part of the solution?

Generative AI has a large carbon footprint and other drawbacks. But AI can help mitigate its own harms—by plowing through mountains of data on extreme weather and human displacement.

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The recent explosion of generative artificial intelligence tools like ChatGPT and Dall-E enabled anyone with internet access to harness AI’s power for enhanced productivity, creativity, and problem-solving. With their ever-improving capabilities and expanding user base, these tools proved useful across disciplines, from the creative to the scientific.

But beneath the technological wonders of human-like conversation and creative expression lies a dirty secret—an alarming environmental and human cost. AI has an immense carbon footprint. Systems like ChatGPT take months to train in high-powered data centers, which demand huge amounts of electricity, much of which is still generated with fossil fuels, as well as water for cooling. “One of the reasons why Open AI needs investments [to the tune of] $10 billion from Microsoft is because they need to pay for all of that computation,” says Kentaro Toyama, a computer scientist at the University of Michigan. There’s also an ecological toll from mining rare minerals required for hardware and infrastructure. This environmental exploitation pollutes land, triggers natural disasters and causes large-scale human displacement. Finally, for data labeling needed to train and correct AI algorithms, the Big Data industry employs cheap and exploitative labor, often from the Global South.

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Payal Dhar
Payal is a writer based in New Delhi who has been covering science, technology, and society since 1998.