- Potential benefitReduces risk that pricing algorithms facilitate tacit or explicit collusion among competitors.
- Potential benefitProvides DOJ and FTC with a rapid investigatory audit tool and technical reporting requirements.
- Potential benefitIncreases transparency to customers, employees, and contractors about algorithmic pricing and discrimination.
Preventing Algorithmic Collusion Act of 2025
Read twice and referred to the Committee on the Judiciary.
This bill prohibits using or distributing pricing algorithms that use, incorporate, or were trained with nonpublic competitor data, requires disclosures when algorithms set or recommend prices or terms, and creates a reporting tool for DOJ and the FTC. It creates a presumption of agreement for algorithm-enabled price fixing under the Sherman Act, authorizes civil penalties and injunctive relief, requires senior-officer certification of reports, and directs an FTC study on pricing algorithms within two years.
Progressives emphasize consumer and worker protections and strict enforcement
Relative to its intended legislative type, this bill is a well-specified substantive policy enactment that defines prohibited conduct, integrates with existing antitrust statutes, and supplies concrete enforcement, reporting, and transparency mechanisms.
This bill prohibits using or distributing pricing algorithms that use, incorporate, or were trained with nonpublic competitor data, requires disclosures when algorithms set or recommend prices or terms, and creates a reporting tool for DOJ and the FTC.
It creates a presumption of agreement for algorithm-enabled price fixing under the Sherman Act, authorizes civil penalties and injunctive relief, requires senior-officer certification of reports, and directs an FTC study on pricing algorithms within two years.
Key enforcement features include 30-day reporting to agencies on requested algorithms, civil penalties (per-day minimums), joint-and-several liability for distributors, and confidentiality protections for submitted reports.
Moderate regulatory cost and novel legal presumptions increase opposition from affected industries and likely generate litigation, lowering enactment chances despite regulatory interest.
Relative to its intended legislative type, this bill is a well-specified substantive policy enactment that defines prohibited conduct, integrates with existing antitrust statutes, and supplies concrete enforcement, reporting, and transparency mechanisms.
Progressives emphasize consumer and worker protections and strict enforcement
Who stands to gain, and who may push back.
These are examples from the analysis, not a ranked list of the most-affected groups.
- Potential burdenCreates new compliance costs for firms developing, deploying, or distributing pricing algorithms.
- Potential burdenBroad nonpublic data definition may create legal uncertainty about permissible data practices.
- Potential burdenMay chill investment and innovation in machine learning and automated pricing tools.
Why the argument around this bill splits.
Progressives emphasize consumer and worker protections and strict enforcement
Likely supportive overall because the bill proactively targets anticompetitive algorithmic practices, increases transparency, and gives enforcement agencies tools to protect consumers and workers.
It aligns with priorities to prevent corporate-enabled collusion and wage suppression and to increase accountability for algorithmic pricing.
Some advocates may press for strong enforcement and closing potential loopholes in definitions.
Supportive in principle of preventing algorithmic collusion and improving transparency, but cautious about implementation details and economic tradeoffs.
Would want clearer definitions, targeted safe harbors, and phased guidance to limit unintended burdens on competition-enhancing pricing tools.
Sees value in the FTC study to guide future, more calibrated rules.
Likely skeptical or opposed, viewing the bill as heavy-handed regulation that interferes with private pricing, burdens businesses, and risks chilling innovation in algorithmic tools.
Concerns focus on broad liability, steep per-day fines, and the federal government’s expanded investigatory reach into pricing systems.
May favor narrow, evidence-based interventions instead.
The path through Congress.
Reached or meaningfully advanced
Reached or meaningfully advanced
Still ahead
Still ahead
Still ahead
Moderate regulatory cost and novel legal presumptions increase opposition from affected industries and likely generate litigation, lowering enactment chances despite regulatory interest.
- Absent cost estimates for compliance and enforcement burdens
- Likely litigation over definition 'nonpublic competitor data'
Recent votes on the bill.
No vote history yet
The bill has not accumulated any surfaced votes yet.
Go deeper than the headline read.
Progressives emphasize consumer and worker protections and strict enforcement
Moderate regulatory cost and novel legal presumptions increase opposition from affected industries and likely generate litigation, lowering…
Relative to its intended legislative type, this bill is a well-specified substantive policy enactment that defines prohibited conduct, integrates with existing antitrust statutes, and supplies concrete enforcement, repo…
Go beyond the headline summary with full stakeholder mapping, legislative design analysis, passage barriers, and lens-by-lens tradeoff breakdowns.