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Supporters and tech groups debate AI training‑data disclosure in HB823; industry urges trade secret protections
Summary
HB823 would require developers of generative AI systems to publicly disclose high‑level information about training data; tech trade groups and industry coalitions supported transparency in principle but asked for narrower, non‑proprietary disclosures and trade‑secret protections; consumer advocates supported the bill with caveats.
House Bill 823 would require developers of generative artificial intelligence systems to publish high‑level summaries of the data used to train their models. Delegate Chao Wu, the bill sponsor, told the Economic Matters Committee the requirement aims to improve accountability, reduce bias, and foster public trust in AI systems used by Marylanders.
"Without transparency about data use, it becomes really impossible to identify or address issues like bias," Delegate Wu said. The bill would require public disclosures on company websites describing training datasets in broad categories rather than publishing raw data.
Industry…
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