Data journalism can be so valuable at aiding the understanding of complex issues. It has the potential to create policy change and hold wrong doers accountable, while using data to back and create credibility. However, data can be used to cause harm if not handled properly. The reading below explore further concepts that should be considered in data collection and usage.  

Becoming Data: Data and Humanity podcast episode dives into the ethical and moral uses of data and how data can be used for good or evil. It uncovers how data collection practices are often not legal. The data collected is then subjected to the collectors own morality and through this, the podcasts exposes that data can be used for harm. They bring a vital perspective of  questioning how can we use data to nurture instead of punish. They raise important aspects to consider for data journalism, where the data is coming from and ultimately when exposed will it do harm to certain groups. 

Alex Howard’s talk on Data Journalism in the Second Machine Age discusses the new technologies that can be applied and through the evolution of technology how data is being integrated instead of people. Similarly to the Becoming Data podcast, he raises valid points about the ethics of using people’s data. Alex Howard uses several examples to highlight that privacy and security of sensitive data must still be protected and cannot be released, similar to how journalist would use an anonymous source to protect their identity. 

Data Set Failures and Intersectional Data by Nikki Stevens discusses intersectionality which is an important analytical framework which can be used in data journalism. Nikki discusses the common eight lifecycle phases of data and where failure has been seen. Intersectional research can aid data journalism by exposing power structures, systemic inequalities and social inequality.  

Data journalism often addresses complex issues and because of this it is important to ensure the data is credible, is fact-checked, and transparent while protecting the identity of those involved. It is  important that data is not being used to continue systemic biases through collection methods. Data can be used for harm, but it can also be used to hold certain groups accountable (ex. governments) or to facilitate public policy, while aiding and elevating marginalized voices.