In my last blog post I promised to talk more about the issue of data “processes” and some of the changes I believe pollsters, media outlets and individuals should start using in order to stay accountable when using data/statistics in their work.
This topic is quite immense. In order to keep it concise, I will be discussing just one point, the media’s use of statistics and data in their articles. While there is quite a bit of work on the use of data ethics (journalistic standards), there is very little that media outlets academics and even private companies (especially technology companies) disclose in terms of their “processes” in collecting data (Gelfond, Jonathan & Ethics in Statistics – Avoid Mispresentation of Data in Research).
This I believe, could be a problem easily mediated by the media by allowing the “processes” of the data they collect to be made public. What do I mean by the “processes”? Information such as how the data was collected, which questions were asked, and why they decided to visually display the data in one particular way as opposed to another and so forth (8 Tips For Asking The Right Data Analysis Questions).
This information can play a large role in allowing individuals to keep the media watchdogs accountable in what they report, highlighting any bias and/or intentional smudging of the data to make an argument look more appealing. By making this information more readily available, consumers of information would then able to discern exactly what they are taking in and absorbing with their minds. If we require nutrition facts to be placed on all of our food items, shouldn’t we require the same for the news we consume with our minds?
While there is very little information as to why media outlets have not already undertaken this approach, I was able to find a few key reasons as to why they may have hesitations in implementing it.
1. Many companies compiling data consider some of the information in their “processes” as a breach of data privacy and therefore consider it a liability.
2. Many organizations use complex algorithms in processing the data. This is often a large expense in research and development which then makes companies consider it proprietary information. Therefore it is not given to the general public (Massey, Grayson).
While these excuses may give media outlets and other institutions an alibi for now, it will only be a matter of time before citizens demand more accountability from private enterprise, the government, academic institutions or anyone that uses data and statistics. This will be a welcome change in an age of disinformation and manipulation (Marwick, Alice, and Rebecca Lewis).
Gelfond, Jonathan. What Makes Data Analysis Good: Ethics and Accountability. What Makes Data Analysis Good: Ethics and Accountability.
“Ethics in Statistics – Avoid Mispresentation of Data in Research.” Explorable – Think Outside The Box – Research, Experiments, Psychology, Self-Help, explorable.com/ethics-in-statistics.
“8 Tips For Asking The Right Data Analysis Questions.” BI Blog | Data Visualization & Analytics Blog | Datapine, 22 Dec. 2017, http://www.datapine.com/blog/data-analysis-questions/.
Massey, Grayson. WordPress.com, wordpress.com/post/datasocietydecisionmakingsp2018.wordpress.com/592.
Marwick, Alice, and Rebecca Lewis. Media Manipulation and Disinformation Online. Media Manipulation and Disinformation Online.
Data/Society/Decision-Making SP2018 