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Michigan Data Pioneer Sparks Privacy Debate with Voter Scores

11/3/2025

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Summary

Story summary

Mark Grebner, a political data pioneer in Michigan, has spent two decades building databases that predict voter party affiliation.
His scoring system assigns a numeric score from various personal data, using about 850 fields per voter.
The database includes factors such as ethnicity and interests and is used by candidates in local elections, prompting privacy concerns.

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Story summary

Mark Grebner, a political data pioneer in Michigan, has spent two decades building databases that predict voter party affiliation.
His scoring system assigns a numeric score from various personal data, using about 850 fields per voter.
The database includes factors such as ethnicity and interests and is used by candidates in local elections, prompting privacy concerns.