SENATE . . . . . . . . . . . . . . No. 2983
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The Commonwealth of Massachusetts
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In the One Hundred and Ninety-Fourth General Court
(2025-2026)
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SENATE, March 12, 2026.
The committee on Housing, to whom was referred the petitions (accompanied by bill, Senate, No. 994) of Cindy F. Friedman and Julian Cyr for legislation to prohibit algorithmic rent setting; and (accompanied by bill, Senate, No. 1016) of Michael O. Moore, Patricia D. Jehlen and James B. Eldridge for legislation to establish the Preventing Algorithmic Rent Fixing in the Rental Housing Market Act., report the accompanying bill (Senate, No. 2983).
For the committee,
Julian Cyr
FILED ON: 2/27/2026
SENATE . . . . . . . . . . . . . . No. 2983
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The Commonwealth of Massachusetts
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In the One Hundred and Ninety-Fourth General Court
(2025-2026)
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An Act prohibiting algorithmic rent setting.
Be it enacted by the Senate and House of Representatives in General Court assembled, and by the authority of the same, as follows:
Chapter 186 of the General Laws is hereby amended by adding the following section:-
Section 15G. (a) As used in this section, the following words shall have the following meanings unless the context clearly requires otherwise:
"Algorithmic device", any computational process derived from machine learning or other artificial intelligence techniques, that processes or calculates nonpublic competitor data for the purpose of advising a lessor or landlord concerning the amount of rent that the lessor or landlord may consider charging a tenant; provided, however that "algorithmic device" shall not include: (i) any report published periodically, but not more frequently than monthly, by a trade association that receives renter data and publishes it in an aggregated and anonymous matter; or (ii) a product used for the purpose of establishing rent or income limits in accordance with the affordable housing program guidelines of a local government, the commonwealth, the federal government or other political subdivision.
“Coordinating function”, any action utilizing nonpublic competitor data that includes: (i) collecting historical or contemporaneous actual rent prices, supply levels or lease or rental contract termination and renewal dates of residential dwelling units from two or more rental property lessors or landlords; (ii) analyzing or processing of historical or contemporaneous actual rent prices, supply levels or lease or rental contract termination and renewal dates of residential dwelling units from two or more rental property lessors or landlords through use of a system, software or process that uses computation, including by using the information to train an algorithm; and (iii) recommending rental prices, lease renewal terms or ideal occupancy levels to a rental property lessor or landlord.
"Coordinator", any person who operates an algorithmic device, software or data analytics service that performs a coordinating function for any residential rental property lessor or landlord, including a residential rental property lessor or landlord performing a coordinating function for their own benefit.
"Nonpublic competitor data", information that is not widely available or easily accessible to the public, including information about actual rent prices, occupancy rates, lease start and end dates, and similar data, regardless of whether the data are attributable to a specific competitor or anonymized, and that is derived from or otherwise provided by any other lessor or landlord.
“Person”, any natural person or persons, or any corporation, partnership, company, trust or association of persons.
"Residential Dwelling Unit", any house, apartment, accessory unit or other unit intended to be used as a primary residence in the state.
(b) In setting the amount of rent to be charged to a tenant for the occupancy of a residential dwelling unit, determining any change in the amount of rent to be charged to a tenant for the renewed occupancy of a residential dwelling unit, or otherwise determining what amount to charge a tenant to rent a residential dwelling unit, or determining occupancy levels of residential dwelling units, no lessor or landlord shall employ, use or rely upon an algorithmic device or coordinator.
(c) A violation of this section shall constitute a violation of section 2 of Chapter 93A. The civil penalty for each violation of this section shall not exceed $5,000 per violation. For the purposes of this section, each time a rent is determined, increased or otherwise set under subsection (b) shall constitute a single and separate violation.
(d) In the case of any successful action to enforce liability pursuant to this chapter, the costs of the action together with reasonable attorney fees, expert fees and the costs of investigation as determined by the court shall be awarded to plaintiffs. Costs and attorney fees, expert fees and the costs of investigation shall be awarded to the attorney general or municipality where the attorney general or municipality successfully enforces this chapter.