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Risk Channel helps you stay ahead of essential risk news shaping your profession. Every weekday, our unique blend of AI, risk experts and researchers monitor 100,000s of articles to share a summary of the most relevant and useful content to help you lead, innovate and grow.

From supply chain to regulatory enforcement, data privacy, GRC controls, whistleblowers, and risk management strategies. Risk Channel is the only trusted online news source dedicated to covering current headlines, articles, reports and interviews to make sure you’re at the forefront of changes in the risk industry.

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Risk Channel
North America
Insurance companies lose bid to hold utility liable for LA wildfire

Insurance companies have lost their bid to hold Southern California Edison (SCE) liable for the 2025 Eaton wildfire without a trial. Superior Court Judge Laura Seigle tentatively denied a request to hold SCE, ​a unit of Edison International, ‌automatically liable for billions of dollars in property losses from the Los Angeles-area fire. If the judge makes her tentative ruling final, Edison will get a chance to argue to a jury at a trial that the unusual circumstances around the ignition of the fire do not qualify for inverse condemnation. “We are pleased with the tentative ruling,” said SCE spokesperson Kathleen Dunleavy.

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Risk Channel
UK/Europe
Google's AI team says its HR filters are unreliable

Bloomberg reports that Google DeepMind's AGI Safety and Alignment Team, which seeks to mitigate the risks of advanced AI, is encouraging job candidates for its open roles to complete a special form alongside their application to eliminate the risk it may be automatically screened out by the company's internal AI systems, according to an internal document. "We have an applications system with a non-trivial probability your CV will be screened out incorrectly or take too long to reach us," the document reads. "Filling out this form makes sure that a real human on the team will get to see your application." A Google DeepMind spokesperson denied that the company's systems filter out applicants incorrectly.

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