With COVID-19 dominating the national conversation, there has been growing discussion about how to reduce crowds and lines at polling places during the 2020 election cycle. One possibility is to enable voting via smartphones. However, cybersecurity experts remain incredibly cautious given security concerns.

A group of graduate researchers from the University of California-Berkeley trained a machine learning model to predict voter preferences using only readily available personal information, suggesting further-reaching implications on the use of AI to infer voter behavior and potentially influence elections.

State and local election officials said at the RSA security conference in San Francisco on Feb. 24 that Federal election assistance funding has been vital to their efforts to shore up election infrastructure security over the past few years.