  With the spread of false and misleading information in current news, many
algorithmic tools have been introduced with the aim of assessing bias and
reliability in written content. However, there has been little work exploring
how effective these tools are at changing human perceptions of content. To this
end, we conduct a study with 654 participants to understand if algorithmic
assistance improves the accuracy of reliability and bias perceptions, and
whether there is a difference in the effectiveness of the AI assistance for
different types of news consumers. We find that AI assistance with
feature-based explanations improves the accuracy of news perceptions. However,
some consumers are helped more than others. Specifically, we find that
participants who read and share news often on social media are worse at
recognizing bias and reliability issues in news articles than those who do not,
while frequent news readers and those familiar with politics perform much
better. We discuss these differences and their implication to offer insights
for future research.
