Can AI Fix Politics? Texas Group Deploys Algorithm to Find 'Builders,' Not 'Dividers'

DALLAS, TX – February 24, 2026 – As Texas voters head into a contentious primary season, a new nonprofit is introducing a novel, technology-driven approach to cutting through the political noise. Builders Bloc, a recently formed 501(c)(4) organization, today launched the Builders Index—a nonpartisan voter tool that uses artificial intelligence to rate candidates not on their party affiliation, but on their perceived capacity for constructive governance.

The tool aims to identify and elevate candidates who prioritize citizen-focused solutions over partisan warfare. By entering their home address on the VoteLikeABuilder.org website, Texans can view a personalized ballot with candidates in their districts rated as 'Builders' (high-scoring problem-solvers), 'Dividers' (low-scoring purveyors of conflict), or 'Toss Ups' (those in the middle). The goal, according to the group, is to help Americans reclaim their civic power by changing the criteria for what makes a good candidate.

A New Metric for Leadership

The Builders Index evaluates politicians on what the organization calls a 'Builders Mindset.' This framework moves beyond traditional left-right ideology to assess behaviors and track records. The core criteria include a history of constructive debate, positive leadership, bipartisan collaboration, legislative effectiveness, and responsiveness to constituents.

To generate its ratings, the system employs a Large Language Model (LLM) combined with a weighted scoring framework. This AI sifts through a vast trove of publicly available data, including legislative voting records, public statements, social media activity, and news coverage. According to Builders Bloc, the algorithm is designed to penalize candidates who engage in personal attacks or consistently use divisive rhetoric, ensuring that such behavior negatively impacts their score while still accounting for their legislative work.

“With the Primary Election increasingly determining who governs in Texas, the Builders Index aims to give voters a stronger pulse on which candidates are prepared to lead and which are more likely to deepen political divides,” said Builders Bloc President Stacy Blakeley in a statement announcing the launch.

In a pilot program demonstrating its model, Builders Bloc has also made independent expenditures to support four state-level candidates who scored highly as 'Builders.' Reflecting its stated nonpartisan approach, the group is backing two Republicans—Angelia Orr (HD 13) and Trent Ashby (HD 9)—and two Democrats—Liz Campos (HD 119) and Rep. Chris Turner (HD 101). This support is contingent upon the candidates signing the 'Builders Pledge,' a commitment to seek common ground, model respectful debate, and govern for all constituents, not just their political base.

The Promise and Peril of AI in the Voting Booth

The introduction of an AI-driven voter guide places the Builders Index at the forefront of a growing, and controversial, trend in electoral politics. Proponents argue that AI can democratize information, making complex legislative records and policy stances more accessible. By analyzing vast datasets, such tools can offer insights that might otherwise require hours of research, potentially increasing voter engagement and education.

Recent academic studies have shown that well-designed, nonpartisan AI voter guides can be perceived by users as trustworthy and can influence voting intentions. The technology holds the promise of helping voters see past slick campaign advertising and focus on substantive records. However, the use of AI in the political sphere is fraught with ethical challenges.

Experts in AI ethics and political science warn of the significant risks, chief among them the potential for inherent bias. LLMs are trained on massive datasets from the internet, which can contain and amplify existing societal and political biases. The very definitions of 'constructive debate' and 'divisive rhetoric' are subjective, and codifying them into an algorithm risks oversimplifying complex political discourse. What one voter sees as a principled stand, the AI might flag as divisive.

Furthermore, the potential for 'black box' algorithms—where the exact reasoning behind a score is opaque—raises serious questions about transparency and accountability. Without a clear understanding of the data sources, the weighting of different criteria, and the fine-tuning of the model, it can be difficult to independently verify the tool's neutrality.

Scrutinizing the 'Nonpartisan' Label

While Builders Bloc presents its index as a purely nonpartisan tool, its structure as a 501(c)(4) 'social welfare' organization invites scrutiny. Under U.S. tax law, these organizations can engage in political and lobbying activities without disclosing their donors, earning them the moniker 'dark money' groups in campaign finance circles. Because the organization is new, public records detailing its funding sources and the full composition of its board are not yet available for independent review.

The challenge for any organization attempting to algorithmically rate politicians is maintaining true objectivity. The selection of data, the design of the scoring rubric, and the interpretation of a candidate's language are all points where human bias can be introduced, intentionally or not. Critics of similar systems argue that a tool's claim of nonpartisanship can mask an underlying ideological agenda.

Builders Bloc maintains that its methodology is balanced, pointing to its initial endorsements of both Republican and Democratic candidates. The organization also states that a candidate’s 'Builder' designation can be withdrawn if they fail to govern in accordance with the pledge they signed, suggesting an ongoing monitoring process.

As the Texas primaries approach, the real-world impact of the Builders Index will be closely watched. Its success or failure may depend on whether voters find its ratings credible and useful. The initiative represents a bold experiment in leveraging technology to foster a different kind of politics, but it also serves as a critical case study in the complex and high-stakes intersection of artificial intelligence and the democratic process.