The Federal Communications Commission will vote to repeal the National Television Ownership Rule that is supposed to prevent a single broadcast station owner from reaching more than 39 percent of all TV households in the US. The proposed change sets up a likely court battle over the FCC claim that it has authority to repeal a limit set by Congress.

FCC Chairman Brendan Carr has already treated the rule as more of a suggestion. In March, the Carr FCC granted a waiver allowing Nexstar Media Group to buy Tegna in a deal that let it reach over half of TV households. The Carr FCC argued that Congress gave it authority to modify or waive the rule.

Carr now plans to repeal the 39 percent limit and replace it with a "case-by-case review" of each proposed merger, the chairman announced today in an op-ed published on Breitbart. The change would make it easier for the FCC to pick and choose which station groups get to surpass the limit. Under Carr, this would likely benefit news companies that provide favorable coverage for President Trump.

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For months, artists and activists have been calling on the prime minister, Anthony Albanese, to act on the AI boom as datacentres pop up around the country. Today he made a major speech at the University of Sydney addressing copyright, the regulation of datacentres and the future of AI in Australia

• 'Not up for grabs': Albanese establishes AI office and vows to protect Australian creatives from copyright 'theft'

Nature, Published online: 15 July 2026; doi:10.1038/s41586-026-10781-4

Meta's AI-fueled layoffs of 8,000 employees targeted workers with disabilities and those who took protected medical or family leaves, alleged a lawsuit filed by 26 employees who were selected for termination. Meta used internal AI tools to select employees for layoffs, according to the complaint filed yesterday by 26 "Doe" plaintiffs in US District Court for the Northern District of California.

"Meta did not assemble the termination list through the considered judgment of managers who knew the work. Instead, Meta used a constellation of internal artificial-intelligence systems—including a system referred to internally as 'Metamate,' employee-trained 'second-brain' agents, keystroke- and activity-monitoring data, AI-token-usage dashboards, and algorithmically assisted performance ranking and calibration—to score, rank, and select employees for inclusion on the list," the lawsuit said.

Employees were allegedly graded, among other things, on how much they used Meta's AI tools. "Meta’s internal dashboards classified employees by their stage of adoption of its artificial-intelligence tools, using categories such as 'AI Native,' 'AI First,' and 'AI Enabled,'" the lawsuit said.

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Nature, Published online: 10 July 2026; doi:10.1038/s41586-026-10853-5