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Bill

HR 55

A Resolution directing the Joint State Government Commission to conduct a study on the feasibility of computational redistricting in Pennsylvania.

2025-2026 Regular Session Introduced by Roni Green and 5 co-sponsors

Pennsylvania commission to study whether algorithms could replace political redistricting, potentially reducing partisan gerrymandering but raising questions about defining fairness computationally.

Referred to State Government
0
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Bill Summary · HR 55

Legislative bill overview

HR 55 directs Pennsylvania's Joint State Government Commission to study whether computational (algorithmic) redistricting could be implemented in the state. The resolution does not change current redistricting procedures but rather authorizes an investigation into the technical feasibility, legal implications, and potential benefits or drawbacks of using computer algorithms to draw legislative districts instead of the current political process.

Why is this important

Redistricting—redrawing electoral districts every 10 years—is a high-stakes process that directly affects which party controls the legislature and how representative districts are. Currently, Pennsylvania uses a politically-controlled process that frequently results in allegations of partisan gerrymandering. A computational approach could theoretically produce more objective, transparent district maps, though implementation raises complex questions about how to code fairness into algorithms and whether they can truly eliminate political considerations.

Potential points of contention

  • Defining "fairness" in code: Algorithms must be programmed with criteria for what makes a good district (compactness, competitiveness, minority representation, etc.), but reasonable people disagree on priorities—embedding political choices into supposedly "neutral" software
  • Partisan stakes: Whichever party controls redistricting currently benefits; computational methods threaten that advantage, creating strong opposition from beneficiaries of the status quo
  • Public trust and transparency: While algorithms offer the appearance of objectivity, many voters find computational processes less understandable and potentially less trustworthy than traditional methods, even if less corrupt

Compiled from official sources — confirm details with the bill’s official record.

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