elections

Election officials are taking steps to mitigate potential chaos and distrust caused by prediction markets in the midterms, including new oaths for workers to prevent manipulation and aggression.

This paper introduces a reproducible auditing framework for detecting systematic political preferences in LLMs, demonstrated through an Italian case study evaluating parties and leaders across nine criteria.

This paper introduces Polistemics, a theory-grounded benchmark for evaluating how LLMs mediate political information in elections, and finds that while aggregate scores look good, models systematically fail under ambiguous or contradictory information.

A national survey finds 63% of Americans uncomfortable with AI helping choose candidates and 80% worried about AI bots answering political surveys, highlighting public trust issues at the intersection of AI and democracy.

An anti-data-center movement is gaining traction in Michigan politics, with candidate Will Lawrence running on a platform opposing data center development, reflecting broader grassroots resistance and reshaping local elections.

AI-generated deepfakes are becoming more realistic and harder to detect, raising concerns about their use in spreading misinformation during midterm elections.

The article reports on the growing political rivalry between AI companies, as Democratic candidate Alex Bores challenges the OpenAI-backed super PAC Leading the Future to a debate, highlighting how AI super PACs are becoming distinct political entities.

OpenAI publishes a threat intelligence report detailing efforts to disrupt over 20 deceptive AI operations globally, with a focus on state-linked actors and influence campaigns particularly concerning given global elections.