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The Supreme Court on Monday lifted a lower court's injunction on President Trump's executive order seeking to limit mail-in voting ahead of November's midterm elections. Trump's order directs the Department of Homeland Security to create state-by-state lists of eligible voters who are citizens. The U.S. Postal Service would then use the lists provided by states to assess whether voters should be allowed to vote by mail. Justices ruled 6 to 3 that California and 22 other states lacked standing to sue over the issue. The ruling, however, did not address whether Trump had authority to impose the rules. A separate nationwide injunction against parts of the same order remains in place.
"This leads to a lot of uncertainty going into the midterms, because the Trump executive order would radically restrict vote by mail," says Ari Berman, the national voting rights correspondent for Mother Jones. If the ruling goes into effect, "it could disenfranchise millions of voters in
November."
"If voting proceeds based on these DHS lists," adds Berman, "it's going to be inaccurate, it's going to be unconstitutional, and a lot of legitimate American voters are going to be wrongly labeled as noncitizens and unable to vote — either based on shoddy data or an intentional attempt by the Trump administration to prevent people from voting."
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(Second column, 7th story, link)
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(Second column, 9th story, link)
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We speak with Timnit Gebru, a leader in the field of AI ethics, about how artificial intelligence is entrenching societal biases and inequality. Gebru is the founder and executive director of the Distributed Artificial Intelligence Research Institute, a group of academics, activists and engineers who produce research rooted in the belief that technology should benefit everyone. She also co-founded Black in AI, a nonprofit that works to increase the inclusion and visibility of Black people in the field of AI. Gebru previously served as co-lead of the ethical AI research team at Google but was fired in 2020 for writing a paper that warned about the financial and environmental costs of large language models, as well as their propensity to promote racism. The internet, which is what AI uses to train itself, "represents hegemonic views," says Gebru. "We even know articles like Wikipedia are heavily biased. It's overwhelmingly Western and male."
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