'Software error' led to around 400 noncitizens voting in New Jersey, Gov. Sherrill says 54%

By Molly McVety42%

7/21/2026, 7:56:41 PM

BS Summary: This article contains 18 faulty reasoning types, including Self-Serving Bias, Negativity Bias, and Halo Effect, with Appeal to Emotion as the most egregious example at 27.5% saturation with 100 hits. Analysis detected 522 faulty-reasoning hits from 363 analyzed words, generating a BS Score of 53% and a BS Rank of 54% (8,963 of 19,441 articles). This article is worse (more manipulative) than 53.90% of the article peer group.

Hundreds of New Jersey residents who are not U.S. citizens voted in previous elections after a "serious software error" in the state’s Motor Vehicle Commission, Gov. 
Mikie Sherrill said Tuesday. 
Between June 2023 and June 2024, roughly 6,600 people applying for driver's licenses or identification cards were registered to vote despite answering "no" when asked if they were a U.S. citizen. 
Sherrill (D), who assumed office in January, said that she learned about the defect last week and ordered her chief counsel to launch an investigation into the matter. 
Preliminary analyses found that fewer than 400 of the erroneously registered people voted. 
During a news conference Tuesday afternoon, Sherrill called the situation "unacceptable," criticizing the administration of former Gov. 
Phil Murphy, a fellow Democrat, for not taking action previously. 
"I want to underscore how seriously I take this matter," Sherrill said. 
"... 
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. 
This failure didn't occur under my watch, but accountability starts now. 
I am taking action to prevent anything like it from occurring in the future and make sure those responsible are held accountable." 
Letters will begin being sent to the people affected notifying them of the error and that they will be removed from the state’s voter rolls. 
Preliminary findings do not suggest that the votes significantly swayed any elections since June 2023, according to state officials. 
The residents were registered as Democrats, Republicans and unaffiliated voters and were scattered across the state. 
The illegitimate votes could have occurred at any point since the time they were registered, Sherrill said, and the timing will be subject to the state’s investigation. 
French security company IDEMIA was identified as the vendor responsible for registering voters for the MVC. 
"New Jerseyans should have confidence that every eligible citizen can vote, every lawful vote will be counted and every reasonable step will be taken to protect the integrity of our elections," Sherrill said. 
"That's my responsibility, and it's one I will never stop fighting to uphold." 
Confirmation Bias
8.8%
Anchoring Bias
7.4%
Availability Heuristic
8.5%
Representativeness Heuristic
4.4%
Hindsight Bias
0%
Overconfidence Bias
4.4%
Framing Effect
0%
Loss Aversion
0%
Status Quo Bias
0%
Sunk Cost Effect
0%
Optimism Bias
6.1%
Pessimism Bias
6.9%
Negativity Bias
11.3%
Self-Serving Bias
14.3%
Fundamental Attribution Error
7.2%
Actor-Observer Bias
0%
In-Group Bias
2.8%
Out-Group Homogeneity Bias
0%
Halo Effect
9.1%
Horn Effect
0%
Dunning-Kruger Effect
0%
Recency Bias
0%
Primacy Effect
0%
Blind-Spot Bias
0%
Ad Hominem
2.8%
Straw Man
0%
Appeal to Authority
0%
False Dilemma
0%
Slippery Slope
0%
Circular Reasoning
0%
Hasty Generalization
8.5%
Red Herring
0%
Bandwagon
0%
Appeal to Emotion
27.5%
Begging the Question
0%
Post Hoc (False Cause)
0%
Tu Quoque
0%
Burden of Proof
0%
Appeal to Nature
0%
Composition/Division
0%
Anecdotal
0%
No True Scotsman
0%
Ambiguity (Equivocation)
7.4%
Gambler’s Fallacy
0%
Middle Ground
0%
Personal Incredulity
0%
Special Pleading
6.1%
Genetic Fallacy
0%
Unattributed Quote
0.3%
Quote-first Misdirection
0%
Biased Writer Voice
0%
Indoctrination
0%
Politically Left Leaning Bias
0%
Politically Right Leaning Bias
0%
Attempt to Sell a Product or Service
0%

363 words analyzed.

Analysis

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