Lindsey Graham, who has died aged 71, was a political survivor. His career as a Republican senator served as a telling barometer for the dramatically changing climate in his political party - and America - in the Donald Trump era. While there were certain issues central to Graham's political identity - including a hawkish foreign policy that focused on containing Russian global ambitions, support for Israel and regime change in Iran - his 23-year career in the Senate was marked by a willingness to adapt to the gale-force change of political winds that accompanied Trump's rise to power. Shortly after being elected to represent South Carolina in the Senate in 2002, Graham became a close ally of Senator John McCain, the Arizona Republican who, while a staunch conservative, developed a national reputation for political independence. When Graham ran for president in 2015, the idea of cooling partisan tensions and working with political opponents was one of his central messages. If I get to be president, we're going to open up a bar in the White House, Graham said.

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Can AI equalize political campaign ads - or will it remain a tool for spreading lies? F rom the comfort of his bed, Jonathan Rinaldi, a political candidate for a city council seat in Queens, New York, tinkered away on his iPhone, prompting an artificial intelligence chatbot to mock up fake news hits and endorsements he had never received. During the campaign last October, Rinaldi shared one of those stories, made to appear real with a CNN logo, on his Facebook and Instagram. It stated that Lynn Schulman, his opponent and an incumbent Democrat, had been "forced to drop out of the race due to a series of critical mistakes". But Schulman had not quit her campaign, and in November, won by a landslide.

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Things to Do in L.A. Tap to enable a layout that focuses on the article. Rep. Nancy Pelosi (D-San Francisco) tours the UC Berkeley campus alongside Chancellor Rich Lyons ahead of announcing the Nancy Pelosi Institute for Representative Democracy. This is read by an automated voice. Please report any issues or inconsistencies here . See more from the L.A. Times in Google Search.

The movement to strengthen democracy in America is suffering as a surfeit of advocacy groups is crowding an ecosystem of nonprofits, coalitions, and think tanks.

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The use of large language models (LLMs) to simulate human behavior has gained significant attention, particularly through personas that approximate individual characteristics. Persona-based simulations hold promise for transforming disciplines that rely on population-level feedback, including social science, economic analysis, marketing research, and business operations. Traditional methods to collect realistic persona data face significant challenges: they are prohibitively expensive and logistically challenging due to privacy constraints, and often fail to capture multi-dimensional attributes, particularly subjective qualities. Consequently, synthetic persona generation with LLMs offers a scalable, cost-effective alternative. However, current approaches rely on ad hoc and heuristic generation techniques that do not guarantee methodological rigor or simulation precision, resulting in systematic biases in downstream tasks. Through extensive large-scale experiments including presidential election forecasts and general opinion surveys of the U.S. population, we reveal that these biases can lead to significant deviations from real-world outcomes. Based on the experimental results, this position paper argues that a rigorous and systematic science of persona generation is needed to ensure the reliability of LLM-driven simulations of human behavior. We call for not only methodological innovations and empirical foundations but also interdisciplinary organizational and institutional support for the development of this field. To support further research and development in this area, we have opensourced approximately one million generated personas, available for public access and analysis at Tianyi-Lab/Personas.