Political Consultant Behind Fake Biden Robocalls Faces $6 Million Fine, Criminal Charges

Political consultant Steven Kramer faces a $6 million fine and over two dozen criminal charges for using AI-generated robocalls mimicking President Joe Biden’s voice to mislead New Hampshire voters ahead of the presidential primary. The Associated Press reports: The Federal Communications Commission said the fine it proposed Thursday for Steven Kramer is its first involving generative AI technology. The company accused of transmitting the calls, Lingo Telecom, faces a $2 million fine, though in both cases the parties could settle or further negotiate, the FCC said. Kramer has admitted orchestrating a message that was sent to thousands of voters two days before the first-in-the-nation primary on Jan. 23. The message played an AI-generated voice similar to the Democratic president’s that used his phrase “What a bunch of malarkey” and falsely suggested that voting in the primary would preclude voters from casting ballots in November.

Kramer is facing 13 felony charges alleging he violated a New Hampshire law against attempting to deter someone from voting using misleading information. He also faces 13 misdemeanor charges accusing him of falsely representing himself as a candidate by his own conduct or that of another person. The charges were filed in four counties and will be prosecuted by the state attorney general’s office. Attorney General John Formella said New Hampshire was committed to ensuring that its elections “remain free from unlawful interference.”

Kramer, who owns a firm that specializes in get-out-the-vote projects, did not respond to an email seeking comment Thursday. He told The Associated Press in February that he wasn’t trying to influence the outcome of the election but rather wanted to send a wake-up call about the potential dangers of artificial intelligence when he paid a New Orleans magician $150 to create the recording. “Maybe I’m a villain today, but I think in the end we get a better country and better democracy because of what I’ve done, deliberately,” Kramer said in February.

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Mark Zuckerberg Assembles Team of Tech Execs For AI Advisory Council

An anonymous reader quotes a report from Quartz: Mark Zuckerberg has assembled some of his fellow tech chiefs into an advisory council to guide Meta on its artificial intelligence and product developments. The Meta Advisory Group will periodically meet with Meta’s management team, Bloomberg reported. Its members include: Stripe CEO and co-founder Patrick Collison, former GitHub CEO Nat Friedman, Shopify CEO Tobi Lutke, and former Microsoft executive and investor Charlie Songhurst.

“I’ve come to deeply respect this group of people and their achievements in their respective areas, and I’m grateful that they’re willing to share their perspectives with Meta at such an important time as we take on new opportunities with AI and the metaverse,” Zuckerberg wrote in an internal note to Meta employees, according to Bloomberg. The advisory council differs from Meta’s 11-person board of directors because its members are not elected by shareholders, nor do they have fiduciary duty to Meta, a Meta spokesperson told Bloomberg. The spokesperson said that the men will not be paid for their roles on the advisory council. TechCrunch notes that the council features “only white men on it.” This “differs from Meta’s actual board of directors and its Oversight Board, which is more diverse in gender and racial representation,” reports TechCrunch.

“It’s telling that the AI advisory council is composed entirely of businesspeople and entrepreneurs, not ethicists or anyone with an academic or deep research background. … it’s been proven time and time again that AI isn’t like other products. It’s a risky business, and the consequences of getting it wrong can be far-reaching, particularly for marginalized groups.”

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‘Pay Researchers To Spot Errors in Published Papers’

Borrowing the idea of “bug bounties” from the technology industry could provide a systematic way to detect and correct the errors that litter the scientific literature. Malte Elson, writing at Nature: Just as many industries devote hefty funding to incentivizing people to find and report bugs and glitches, so the science community should reward the detection and correction of errors in the scientific literature. In our industry, too, the costs of undetected errors are staggering. That’s why I have joined with meta-scientist Ian Hussey at the University of Bern and psychologist Ruben Arslan at Leipzig University in Germany to pilot a bug-bounty programme for science, funded by the University of Bern. Our project, Estimating the Reliability and Robustness of Research (ERROR), pays specialists to check highly cited published papers, starting with the social and behavioural sciences (see go.nature.com/4bmlvkj). Our reviewers are paid a base rate of up to 1,000 Swiss francs (around US$1,100) for each paper they check, and a bonus for any errors they find. The bigger the error, the greater the reward — up to a maximum of 2,500 francs.

Authors who let us scrutinize their papers are compensated, too: 250 francs to cover the work needed to prepare files or answer reviewer queries, and a bonus 250 francs if no errors (or only minor ones) are found in their work. ERROR launched in February and will run for at least four years. So far, we have sent out almost 60 invitations, and 13 sets of authors have agreed to have their papers assessed. One review has been completed, revealing minor errors. I hope that the project will demonstrate the value of systematic processes to detect errors in published research. I am convinced that such systems are needed, because current checks are insufficient. Unpaid peer reviewers are overburdened, and have little incentive to painstakingly examine survey responses, comb through lists of DNA sequences or cell lines, or go through computer code line by line. Mistakes frequently slip through. And researchers have little to gain personally from sifting through published papers looking for errors. There is no financial compensation for highlighting errors, and doing so can see people marked out as troublemakers.

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