If popular online platforms systematically expose their users to partisan and unreliable news, they could potentially contribute to societal issues such as rising political polarization. This concern is central to the ‘echo chamber’ and ‘filter bubble’ debates, which critique the roles that user choice and algorithmic curation play in guiding users to different online information sources. These roles can be measured as exposure, defined as the URLs shown to users by online platforms, and engagement, defined as the URLs selected by users. However, owing to the challenges of obtaining ecologically valid exposure data—what real users were shown during their typical platform use—research in this vein typically relies on engagement data or estimates of hypothetical exposure. Studies involving ecological exposure have therefore been rare, and largely limited to social media platforms, leaving open questions about web search engines. To address these gaps, we conducted a two-wave study pairing surveys with ecologically valid measures of both exposure and engagement on Google Search during the 2018 and 2020 US elections. In both waves, we found more identity-congruent and unreliable news sources in participants’ engagement choices, both within Google Search and overall, than they were exposed to in their Google Search results. These results indicate that exposure to and engagement with partisan or unreliable news on Google Search are driven not primarily by algorithmic curation but by users’ own choices.