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Sponsors tell committee pricing algorithms trained on nonpublic data risk enabling price‑fixing; bill would require disclosures

House Technology and Innovation Committee · March 3, 2026
AI-Generated Content: All content on this page was generated by AI to highlight key points from the meeting. For complete details and context, we recommend watching the full video. so we can fix them.

Summary

Representatives Cockley and Tex Fisher told the House Technology and Innovation Committee that House Bill 665 would clarify prohibitions on algorithmic price fixing and require companies with over $5,000,000 in gross receipts to disclose use of pricing algorithms trained on nonpublic competitor data; members pressed sponsors on enforcement and evidence collection.

Representatives Cockley and Tex Fisher testified in favor of House Bill 665, telling the House Technology and Innovation Committee that the measure would clarify Ohio law to cover pricing algorithms that use nonpublic competitor data and require companies with more than $5,000,000 in gross receipts to disclose if they use pricing algorithms trained on such data.

"Pricing algorithms that are given non public competitor data can skirt around current laws to engage in price fixing in a roundabout way," Representative Cockley told the committee, arguing that the practice can undermine competition and harm consumers.

Cockley cited the rental market…

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