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The DOJ Misled a Judge About How It’s Using Voter Roll Data

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Last week in Rhode Island, in a hearing over the Trump administration’s efforts to access the state’s unredacted voter lists, US district judge Mary McElroy asked a Department of Justice lawyer what the agency had been doing with the voter roll data it already amassed from other states in recent months.

“We have not done anything yet,” said Eric Neff, the acting chief of the agency’s voting section, a core part of the DOJ’s civil rights division that focuses on enforcing federal laws that protect the right to vote. Neff added that the data the DOJ collected from states—which can include Social Security numbers, drivers licenses, dates of birth, and addresses—was being kept separate.

“The United States is taking extra concern to make sure that we’re complying with the Privacy Act in every conceivable way,” Neff added. The Privacy Act of 1974 regulates how government agencies collect and use personally identifiable information about US residents.

But Neff was not telling the truth: The DOJ, he later admitted, was pooling the data and already analyzing it to identify voting irregularities.

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In a court document filed on March 27, Neff walked back his claims. “The United States represented that each data set was stored separately,” Neff wrote. “The United States also stated that no analysis had yet been conducted on the data. To correct and clarify the record, preliminary internal data analysis of the nonpublic voter registration data has begun. In particular, the Civil Rights Division has begun the process of identifying and quantifying the number and type of duplicate and deceased registered voters in each state.”

The revelation confirms what was widely speculated, which is that the DOJ appears to be pooling the data and using it to identify potential issues with suspected voting irregularities ahead of the midterms, which is a core part of Trump’s broad attack on elections.

Neff and the DOJ did not respond to repeated requests for comment.

Critics have grown increasingly concerned about the DOJ’s voting section, which has undergone a stark transformation since President Donald Trump has retaken office. A newly installed coterie of inexperienced but ultra-loyal lawyers in the DOJ’s voting section, many of whom have supported election denial conspiracy theories, have spent their time on forcing states to hand over their voter roll information.

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The initiative began in May last year, when the Department of Justice sent letters to election officials in at least 48 states and Washington, DC, asking for unredacted voter rolls. Some Republican-led states immediately handed over the information, but dozens of others pushed back. As a result, Neff and his colleagues have sued 30 states, asking courts to force them to hand over the information. So far, courts have sided with the states, with judges already dismissing cases in California, Michigan, and Oregon.

In many of the lawsuits, state election officials pointed out the huge security risk involved in sharing such sensitive data, especially when it was unclear how the data would be stored or who it would be shared with. “We still have no idea what the government is doing with this data,” says David Becker, the head of the Center for Election Innovation and Research and a former Justice Department lawyer. “No idea where it is being stored, how it is being protected, or who has access to it. This data is incredibly sensitive. If someone has any of these three data points on any of us, Social Security number, driver’s license number, or date of birth, they can wreck us financially. This is why the states protect this data, and they do a good job of it.”

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AI agents that automatically prevent, detect and fix software issues are here as NeuBird AI launches Falcon, FalconClaw

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The mantra of the modern tech industry was arguably coined by Facebook (before it became Meta): “move fast and break things.”

But as enterprise infrastructure has shifted into a dizzying maze of hybrid clouds, microservices, and ephemeral compute clusters, the “breaking” part has become a structural tax that many organizations can no longer afford to pay. Today, two-year-old startup NeuBird AI is launching a full-scale offensive against this “chaos tax,” announcing a $19.3 million funding round alongside the release of its Falcon autonomous production operations agent.

The launch isn’t just a product update; it is a philosophical pivot. For years, the industry has focused on “Incident Response”—making the fire trucks faster and the hoses bigger. NeuBird AI is arguing that the only sustainable path forward is “Incident Avoidance”.

As Venkat Ramakrishnan, President and COO of NeuBird AI, put it in a recent interview: “Incident management is so old school. Incident resolution is so old school. Incident avoidance is what is going to be enabled by AI”.

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By grounding AI in real-time enterprise context rather than just large language model reasoning, the company aims to move site reliability engineering and devops teams from a reactive posture to a predictive one.

The AI divide: a reality check on automation

Accompanying the launch is NeuBird AI’s 2026 State of Production Reliability and AI Adoption Report, a survey of over 1,000 professionals that reveals a massive disconnect between the boardroom and the server room.