A judge found that a court stenographer used generative AI to help prepare an official court transcript, resulting in errors like attributing statements to the wrong speakers. The transcript contained multiple errors including a motion attributed to the trial court instead of the State, an objection attributed to the Bailiff instead of the defendant, and closing argument attribution errors. The judge reminded the court reporter that transcripts must be accurate representations of proceedings and warned that using AI without proper proofreading undermines the integrity of official trial records.
The proposed AI Kill Switch Act would authorize the US government to order shutdown of AI systems deemed to cause catastrophic harm, requiring AI companies to build in technical capabilities for such shutdowns. Violations could result in fines up to $20 million per day. Companies would be forced to comply with government orders to throttle, disable, or completely shut down their systems or face severe penalties.
AI API providers are routing user requests to different models than requested without consistently disclosing which model actually ran the computation, creating ambiguity about what customers purchased. Cursor's Router classifier and OpenRouter's quantization practices route requests based on cost or complexity without naming specific model assignments, while only Anthropic transparently returns the served model in its response. This breaks the chain of custody for legal authentication and evidence, making it impossible for courts or firms to verify which model produced output in disputes over hallucinations, plagiarism, or misconduct.
Communities are establishing data collectives and cooperatives to control their data rather than allow major tech companies to extract it for AI training without consent or compensation. Mozilla Data Collective hosts approximately 700 hours of voice data in 39 Pakistani languages and over 20 African languages, with Meta and other companies now negotiating usage terms directly with communities. This shift enables underrepresented language communities to build AI tools in their own languages while maintaining governance over how their data is used.
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