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"From 2016 to 2020, the Australian government operated an automated debt assessment and recovery system, known as "Robodebt," to recover fraudulent or overpaid welfare benefits. The goal was to save $4.77 billion through debt recovery and reduced public service costs. However, the algorithm and policies at the heart of Robodebt caused wildly inaccurate assessments, and administrative burdens that disproportionately impacted those with the least resources. After a federal court ruled the policy unlawful, the government was forced to terminate Robodebt and agree to a $1.8 billion settlement."

Another interesting article - but is this Government and Politics as an Area of Impact?

"Bitcoin mining - the process in which a bitcoin is awarded to a computer that solves a complex series of algorithms - is a deeply energy-intensive process. "Mining" bitcoin involves solving complex math problems in order to create new bitcoins. Miners are rewarded in bitcoin. Earlier in bitcoin's relatively short history - the currency was created in 2009 - one could mine bitcoin on an average computer. But the way bitcoin mining has been set up by its creator (or creators - no one really knows for sure who created it) is that there is a finite number of bitcoins that can be mined: 21m. The more bitcoin that is mined, the harder the algorithms that must be solved to get a bitcoin become."

"Caroline, the 28-year-old behind a popular TikTok account where she posts satirical skits, found herself dropping the comedic tone when the child of a family vlogger sent her a letter and asked Caroline to share it with her 2.3 million followers. "To any parents that are considering starting a family vlog or monetizing your children's lives on the public internet, here is my advice: you shouldn't do it," the letter read. "Any money you get will be greatly overshadowed by years of suffering… your child will never be normal… I never consented to being online.""

"The new AI Index report notes that in 2023, AI still struggled with complex cognitive tasks like advanced math problem-solving and visual commonsense reasoning. However, 'struggled' here might be misleading; it certainly doesn't mean AI did badly. Performance on MATH, a dataset of 12,500 challenging competition-level math problems, improved dramatically in the two years since its introduction. In 2021, AI systems could solve only 6.9% of problems. By contrast, in 2023, a GPT-4-based model solved 84.3%. The human baseline is 90%. "

"Researchers at the University of Pennsylvania found that Turkish high school students who had access to ChatGPT while doing practice math problems did worse on a math test compared with students who didn't have access to ChatGPT. Those with ChatGPT solved 48 percent more of the practice problems correctly, but they ultimately scored 17 percent worse on a test of the topic that the students were learning. "