MS NOW94%

Software error registered over 6,000 noncitizen voters in NJ, governor says 51%

By Ebony Davis79%

7/21/2026, 10:35:24 PM

BS Summary: This article contains 21 faulty reasoning types, including Self-Serving Bias, Framing Effect, and Representativeness Heuristic, with Negativity Bias as the most egregious example at 22.3% saturation with 126 hits. Analysis detected 954 faulty-reasoning hits from 565 analyzed words, generating a BS Score of 50.8% and a BS Rank of 51% (10,157 of 20,367 articles). This article is worse (more manipulative) than 50.10% of the article peer group.

About 6,600 noncitizens were mistakenly registered to vote because of a software error in New Jersey’s motor vehicle system, though fewer than 400 cast ballots, Gov. 
Mikie Sherrill announced Tuesday. 
Sherrill said the error occurred between June 2023 and June 2024, during the previous administration, after applicants for driver’s licenses and state identification cards correctly indicated they were not U.S. citizens but were registered to vote because of what she described as a “serious” software failure. 
A preliminary review found that the roughly 400 people who cast ballots after being accidentally being added to the voter rolls were registered as Democrats, Republicans and unaffiliated voters. 
The Democratic governor said she learned of the issue last week and immediately ordered an investigation led by her chief counsel. 
She also directed state officials to remove anyone erroneously added to the voter rolls during that period. 
Additionally, Sherrill said the new administrator of the New Jersey Motor Vehicle Commission has begun replacing the vendor responsible for administering the system. 
Sherrill called the error a “reckless failure” and accused the previous administration of lacking transparency. 
“I am appalled by the reckless failures that allowed this to happen and the lack of transparency shown by those in charge at the time,” she said. 
“This failure didn’t occur under my watch, but accountability starts now.” 
Assistant Attorney General Harmeet Dhillon, who oversees the Justice Department’s Civil Rights Division, announced on X that the DOJ is “investigating this unlawful dilution of American votes.” 
In a letter , Dhillon asked Sherrill to provide records on the noncitizens who were mistakenly registered to vote and those who later cast ballots. 
The department requested identifying and voting information within five business days and ordered the state to preserve related records. 
The disclosure comes days after President Donald Trump delivered a speech on election security , reviving false claims about the 2020 election and alleging vulnerabilities in voter registration and voting systems as Republicans make election integrity a central issue ahead of the 2026 midterms. 
Trump alleged the Department of Homeland Security identified “approximately 278,000 noncitizens who are registered to vote in federal elections,” citing a review of state voter rolls and public records. 
“As President Trump has said, there is nothing more important than the integrity of our elections. 
And this latest incident underscores the absolute necessity of the SAVE America Act.” 
White House spokeswoman Abigail Jackson said in a statement Tuesday. 
Sherrill sought to distinguish her administration’s response from Trump’s repeated false claims of widespread voter fraud. 
She accused the president of undermining confidence in U.S. elections through years of baseless allegations about election results and efforts to overturn the outcome of the 2020 presidential election. 
“As the Trump Administration tries to weaponize elections for political gain, I am ensuring we protect our elections,” Sherrill said. 
Federal law prohibits non-U.S. citizens from voting in federal elections, and states routinely maintain voter registration rolls to remove ineligible voters. 
Election experts have said instances of noncitizen voting are rare , though administrative errors occasionally occur. 
Sherrill said her administration would continue investigating how the software malfunction occurred and will implement safeguards to prevent similar errors in the future. 
“When we find a problem, we don’t hide it, deny it, or invent conspiracies,” she said. 
“We investigate it, we fix it, and we tell the public.” 
Article reasoning-pattern comparisonThis article: 2.3%Ebony Davis: 1.9%MS NOW: 7.6%Confirmation Bias2.3%This article: 0.0%Ebony Davis: 0.4%MS NOW: 1.2%Anchoring Bias0.0%This article: 9.7%Ebony Davis: 2.7%MS NOW: 3.7%Availability Heuristic9.7%This article: 12.6%Ebony Davis: 1.1%MS NOW: 1.1%Representativeness Heuristic12.6%This article: 0.0%Ebony Davis: 0.9%MS NOW: 1.3%Hindsight Bias0.0%This article: 0.0%Ebony Davis: 3.4%MS NOW: 2.6%Overconfidence Bias0.0%This article: 14.9%Ebony Davis: 12.5%MS NOW: 15.5%Framing Effect14.9%This article: 0.0%Ebony Davis: 0.3%MS NOW: 0.7%Loss Aversion0.0%This article: 4.1%Ebony Davis: 1.2%MS NOW: 0.9%Status Quo Bias4.1%This article: 0.0%Ebony Davis: 0.1%MS NOW: 0.1%Sunk Cost Effect0.0%This article: 4.1%Ebony Davis: 3.8%MS NOW: 2.4%Optimism Bias4.1%This article: 0.0%Ebony Davis: 1.7%MS NOW: 3.2%Pessimism Bias0.0%This article: 22.3%Ebony Davis: 12.8%MS NOW: 19.3%Negativity Bias22.3%This article: 21.6%Ebony Davis: 6.2%MS NOW: 2.4%Self-Serving Bias21.6%This article: 2.7%Ebony Davis: 1.1%MS NOW: 3.1%Fundamental Attribution Error2.7%This article: 0.0%Ebony Davis: 0.3%MS NOW: 0.3%Actor-Observer Bias0.0%This article: 3.5%Ebony Davis: 3.6%MS NOW: 3.5%In-Group Bias3.5%This article: 0.0%Ebony Davis: 1.9%MS NOW: 2.6%Out-Group Homogeneity Bias0.0%This article: 0.0%Ebony Davis: 2.3%MS NOW: 2.2%Halo Effect0.0%This article: 0.0%Ebony Davis: 0.1%MS NOW: 1.8%Horn Effect0.0%This article: 0.0%Ebony Davis: 0.0%MS NOW: 0.0%Dunning-Kruger Effect0.0%This article: 7.8%Ebony Davis: 2.8%MS NOW: 1.8%Recency Bias7.8%This article: 0.0%Ebony Davis: 0.7%MS NOW: 0.6%Primacy Effect0.0%This article: 0.0%Ebony Davis: 0.1%MS NOW: 0.2%Blind-Spot Bias0.0%This article: 0.0%Ebony Davis: 3.8%MS NOW: 4.8%Ad Hominem0.0%This article: 0.0%Ebony Davis: 0.0%MS NOW: 1.3%Straw Man0.0%This article: 9.9%Ebony Davis: 4.9%MS NOW: 5.4%Appeal to Authority9.9%This article: 2.3%Ebony Davis: 1.7%MS NOW: 2.2%False Dilemma2.3%This article: 0.0%Ebony Davis: 0.3%MS NOW: 2.2%Slippery Slope0.0%This article: 0.0%Ebony Davis: 0.2%MS NOW: 0.2%Circular Reasoning0.0%This article: 2.8%Ebony Davis: 3.8%MS NOW: 8.1%Hasty Generalization2.8%This article: 7.8%Ebony Davis: 1.3%MS NOW: 0.7%Red Herring7.8%This article: 0.0%Ebony Davis: 1.1%MS NOW: 0.9%Bandwagon0.0%This article: 9.9%Ebony Davis: 10.5%MS NOW: 9.9%Appeal to Emotion9.9%This article: 0.0%Ebony Davis: 1.6%MS NOW: 2.4%Begging the Question0.0%This article: 8.1%Ebony Davis: 2.3%MS NOW: 3.2%Post Hoc (False Cause)8.1%This article: 3.5%Ebony Davis: 0.2%MS NOW: 0.6%Tu Quoque3.5%This article: 4.4%Ebony Davis: 0.7%MS NOW: 0.9%Burden of Proof4.4%This article: 0.0%Ebony Davis: 0.0%MS NOW: 0.1%Appeal to Nature0.0%This article: 0.0%Ebony Davis: 0.1%MS NOW: 0.3%Composition/Division0.0%This article: 0.0%Ebony Davis: 1.1%MS NOW: 2.6%Anecdotal0.0%This article: 0.0%Ebony Davis: 0.3%MS NOW: 0.2%No True Scotsman0.0%This article: 0.0%Ebony Davis: 1.2%MS NOW: 1.7%Ambiguity (Equivocation)0.0%This article: 0.0%Ebony Davis: 0.0%MS NOW: 0.0%Gambler’s Fallacy0.0%This article: 0.0%Ebony Davis: 0.2%MS NOW: 0.1%Middle Ground0.0%This article: 0.0%Ebony Davis: 0.0%MS NOW: 0.3%Personal Incredulity0.0%This article: 0.0%Ebony Davis: 1.1%MS NOW: 0.3%Special Pleading0.0%This article: 0.0%Ebony Davis: 0.6%MS NOW: 1.3%Genetic Fallacy0.0%This article: 0.0%Ebony Davis: 1.5%MS NOW: 2.5%Unattributed Quote0.0%This article: 0.0%Ebony Davis: 2.0%MS NOW: 1.5%Quote-first Misdirection0.0%This article: 9.7%Ebony Davis: 5.0%MS NOW: 14.3%Biased Writer Voice9.7%This article: 4.8%Ebony Davis: 1.3%MS NOW: 2.1%Indoctrination4.8%This article: 0.0%Ebony Davis: 2.9%MS NOW: 5.4%Politically Left Leaning Bias0.0%This article: 0.0%Ebony Davis: 0.2%MS NOW: 0.6%Politically Right Leaning Bias0.0%This article: 0.0%Ebony Davis: 0.1%MS NOW: 0.4%Attempt to Sell a Product or S…0.0%

565 words analyzed.

Speakers

4speakers68%attributed speech179writer words
Voice mapSelect a segment to jump to its words
Writer's voice • 11 words • 100.0% coverageGov. • 26 words • 0.0% coverageMikie Sherrill • 4 words • 0.0% coverageMikie Sherrill • 46 words • 0.0% coverageWriter's voice • 29 words • 0.0% coverageMikie Sherrill • 21 words • 0.0% coverageMikie Sherrill • 17 words • 0.0% coverageMikie Sherrill • 23 words • 0.0% coverageMikie Sherrill • 15 words • 0.0% coverageMikie Sherrill • 27 words • 0.0% coverageMikie Sherrill • 11 words • 0.0% coverageHarmeet Dhillon • 27 words • 0.0% coverageHarmeet Dhillon • 25 words • 0.0% coverageHarmeet Dhillon • 19 words • 0.0% coverageWriter's voice • 44 words • 100.0% coverageWriter's voice • 29 words • 0.0% coverageWriter's voice • 16 words • 0.0% coverageWriter's voice • 13 words • 0.0% coverageAbigail Jackson • 10 words • 0.0% coverageMikie Sherrill • 16 words • 0.0% coverageMikie Sherrill • 29 words • 0.0% coverageMikie Sherrill • 20 words • 0.0% coverageWriter's voice • 21 words • 0.0% coverageWriter's voice • 16 words • 0.0% coverageMikie Sherrill • 23 words • 0.0% coverageMikie Sherrill • 16 words • 100.0% coverageMikie Sherrill • 11 words • 100.0% coverage
Selected voice

Gov.

100%flagged-word coverage
26 attributed words6.7% of attributed speech79% writer coverage
0%17.5%35.0%Biased Writer Voice-30.7 ptsWriter: 30.7%Gov.: 0.0%0.0%

Attribution is sentence-level. Pattern percentages are calculated only from words assigned to that voice.

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Analysis

Hover over highlighted words in the article to view the associated bias or fallacy analysis.