A typical solution isdirect democracywhich decides based on amajority vote, the so called "wisdom of the crowd."

Predictions that AI bot swarms were a threat to democracy weren't'fanciful', said Michael Wooldridge, professor of the foundations of AI at Oxford University. Predictions that AI bot swarms were a threat to democracy weren't'fanciful', said Michael Wooldridge, professor of the foundations of AI at Oxford University. Experts warn of threat to democracy from'AI bot swarms' infesting social media Political leaders could soon launch swarms of human-imitating AI agents to reshape public opinion in a way that threatens to undermine democracy, a high profile group of experts in AI and online misinformation has warned. The Nobel peace prize-winning free-speech activist Maria Ressa, and leading AI and social science researchers from Berkeley, Harvard, Oxford, Cambridge and Yale are among a global consortium flagging the new "disruptive threat" posed by hard-to-detect, malicious "AI swarms" infesting social media and messaging channels. A would-be autocrat could use such swarms to persuade populations to accept cancelled elections or overturn results, they said, amid predictions the technology could be deployed at scale by the time of the US presidential election in 2028.

Advances in artificial intelligence are creating a perfect storm for those seeking to spread disinformation at unprecedented speed and scale. And it's virtually impossible to detect. In 2016, hundreds of Russians filed into a modern office building on 55 Savushkina Street in St. Petersburg every day; they were part of the now-infamous troll farm known as the Internet Research Agency . Day and night, seven days a week, these employees would manually comment on news articles, post on Facebook and Twitter, and generally seek to rile up Americans about the then-upcoming presidential election. When the scheme was finally uncovered, there was widespread media coverage and Senate hearings, and social media platforms made changes in the way they verified users.

Ana Corina Sosa (second from left), receives the Nobel Peace Prize for her mother, Venezuelan opposition leader Maria Corina Machado, from the Chair of the Norwegian Nobel Committee Jorgen Watne Frydnes next to a photo of Machado, in Oslo on Wednesday. OSLO - Democracies must be prepared to fight for freedom in order to survive, Nobel Peace Prize laureate Maria Corina Machado said on Wednesday, in a speech delivered by her daughter during a ceremony Machado could not attend. The Venezuelan opposition leader said that the prize held profound significance, not only for her country but for the world. "It reminds the world that democracy is essential to peace," she said, via her daughter Ana Corina Sosa Machado. "And the most important, the lesson Venezuelans can share with the world, is a lesson forged on a long and difficult path: If we want democracy, we must be prepared to fight for freedom."

AI can influence voters' minds. What does that mean for democracy? AI chatbots may have the power to influence voters' opinions Does the persuasive power of AI chatbots spell the beginning of the end for democracy? In one of the largest surveys to date exploring how these tools can influence voter attitudes, AI chatbots were more persuasive than traditional political campaign tools including advertisements and pamphlets, and as persuasive as seasoned political campaigners. But at least some researchers identify reasons for optimism in the way in which the AI tools shifted opinions.

This happens in noisy settings when voters have limited information.

Fulkerson's algorithm, we develop a polynomial-time algorithm for computing the

Palantir's CEO is good with ICE and says he defends human rights. But will Israel and Trump ever go too far for him? Alex Karp and I would not seem to have much in common. I work for WIRED, which does tough reporting on Trumpworld; Karp is the CEO of Palantir, a $450 billion firm that has contracts with agencies like the CIA and ICE and worked for the Israeli military during its campaign in Gaza. I live in the East Village of New York City, and the home Karp spends the most time in is a 500-acre compound in rural New Hampshire. I was a plain old English major, and he's got a law degree and a PhD in philosophy, studying under the legendary Jürgen Habermas. I consider myself a progressive; Karp regards that stuff as "pagan religion." But we can bond over one shared status: Both of us are alumni of Central High School, a Philadelphia magnet school. I have some years on the 58-year-old executive.)

Social media has reshaped political discourse, offering politicians a platform for direct engagement while reinforcing polarization and ideological divides. This study introduces a novel topic evolution framework that integrates BERTopic-based topic modeling with Moral Foundations Theory (MFT) to analyze the longevity and moral dimensions of political topics in Twitter activity during the 117th U.S. Congress. We propose a methodology for tracking dynamic topic shifts over time and measuring their association with moral values and quantifying topic persistence. Our findings reveal that while overarching themes remain stable, granular topics tend to dissolve rapidly, limiting their long-term influence. Moreover, moral foundations play a critical role in topic longevity, with Care and Loyalty dominating durable topics, while partisan differences manifest in distinct moral framing strategies. This work contributes to the field of social network analysis and computational political discourse by offering a scalable, interpretable approach to understanding moral-driven topic evolution on social media.

Current frameworks for consensus statement generation with large language models lack the inherent structure needed to provide provable fairness guarantees when aggregating diverse free-form opinions. We model the task as a multi-objective, token-level Markov Decision Process (MDP), where each objective corresponds to an agent's preference. Token-level rewards for each agent are derived from their policy (e.g., a personalized language model). This approach utilizes the finding that such policies implicitly define optimal Q-functions, providing a principled way to quantify rewards at each generation step without a value function (Rafailov et al., 2024). This MDP formulation creates a formal structure amenable to analysis using principles from social choice theory. We propose two approaches grounded in social choice theory. First, we propose a stochastic generation policy guaranteed to be in the ex-ante core, extending core stability concepts from voting theory to text generation. This policy is derived from an underlying distribution over complete statements that maximizes proportional fairness (Nash Welfare). Second, for generating a single statement, we target the maximization of egalitarian welfare using search algorithms within the MDP framework. Empirically, experiments using language models to instantiate agent policies show that search guided by the egalitarian objective generates consensus statements with improved worst-case agent alignment compared to baseline methods, including the Habermas Machine (Tessler et al., 2024).