Sam Burdette, 19, senior, University of Arizona, Tucson, Ariz.

Burdette is studying journalism and serves as editor-in-chief of the university’s student-run paper, The Daily Wildcat. She plans to pursue a master’s degree and hopes to work in breaking news after college. 

I’m not sure newsrooms should be using polling information less in the future, but they should instead present the results as they actually are—mere estimates. Only after the polls were deemed to be obviously flawed—i.e. after President Trump took his surprising win in 2016—did we start hearing about why those polling results may have been flawed. However, we should have known all along those poll results could certainly misrepresent the truth of the public’s opinion.

In my statistics classes following the election, the 2016 polls were a popular topic of discussion, especially because it was easy for senior high school stats students to pick out where things may have gone wrong. Over the course of maybe a week, we learned how polls may have only targeted those on the extremes of the political spectrum, how leading questions may have confused participants and how the media’s omission or lack of attention to confidence intervals may have misrepresented the actual results. Whatever the cause, the point is I believe news media should be upfront and very clear with their audience about the level of exactness the polling results actually have.

I think this can be as simple as an extra paragraph or an editor’s note in a story that references poll results, or a one-sentence disclaimer before or after a presentation of the results on television or over the radio. One of the primary jobs of the news media is to promote democracy, to inform the public of what they need to know so they can make informed decisions about their government and the world around them. In order to do this, we need to be transparent that a lead in the polls is not an exact percentage by any means but an estimate of a huge number of voters that is prone to both statistical and human bias.