The importance of information and the abilities of that information are increasing everyday. Now with modern technology and the vast wealth of data that is the internet, the power of information is at an all time high. In order to create greater equality, people must learn to analyze this information. The over reliance on information present like in data visualization can be harmful and influential.
Catherine D’Ignazio’s article addresses the mindless acceptance of data without comprehending the oppression and misrepresentation within the data. Her article, “What would feminist data visualization look like?” presents the misconception about the validly of data visualizations as well as the credibility of data sources. With the new trend of big data and data visualizations, fewer people question the validity of the data. People fail to critically think about the ethics and politics associated with representation. These means that sources of data like maps and infographics wields an immense rhetorical power in the perceptions of people. We often accept the charts as facts dismissing the bigger picture lacking to find the true representations. Similarly, maps present sources of power controlled by the creator’s rhetoric. The data will never reflect a whole world view but D’Ignazio details three possible solutions to improving the inequality in the data. She believes that, people must acknowledge the power of inclusion and exclusion flaws data visualization into a tool of oppression. Her first step to addressing this issue is to invent new ways to represent uncertainty, outsides, missing data, and flawed methods. We must explore the limitations and understand the missing data including fact-checking and possible exclusion. Data visualizers must take the time to critically analyze what is represented. The second step is creating new ways to reference the economy behind the data. This step is where you question the data. Who’s a stakeholder in the data? Who collected the data and where is it from? The final improvement being to make dissent possible to allow for diversity and inclusion. By allowing for multiple perspectives and creating others to contribute even contradict the data allows for a more complete representation. The link to D’Ignazio’s article on the politics and ethics on data visualization https://civic.mit.edu/feminist-data-visualization.
I sympathize with D’Ignazio’s concern for the misconceptions of data becoming tools for oppression through rhetoric. The misguided belief in the facts presented in visualization is careless and dangerous. The rhetoric visuals like maps and infographic hold is evident and more relevant than ever. With the modern age of big data, this crucial understanding of how rhetoric is weaponized. The problem occurs because the creator often wields the sole power in how the data is collected and displayed. One must be able to think critically by questioning the visuals. How reliable is the data? Why was the data displayed this way? What are the limits of the data? Often the creator’s bias or perspective can be found in the inclusion or exclusion of data and minorities. I also find immense value in D’Ignazio’s three solutions to do a more responsible way of representation. Her first proposal would add immense credibility to the visualizations by depicting elements such as the data’s limits, uncertainty, and missing data. This is evident in the work of Viktor Mayer-Schonberger and Kenneth Cukier, “Big Data: A Revolution That Will Transform How We Live, Work, and Think. The book details both the importance and value of data visuals and the necessity of comprehension. May-Schonberger explains, “Big data is about the what, not why”. The problem highlights the true lack of knowledge about understanding data. In addition to question the data collected, people also must acknowledge the financials of data. The economy behind data can help assess preconceptions and the overall objectivity of the representations. Data can be shaped and skewed with the rhetoric of the creator. D’Ignazio perfectly describes this value with a quote. The quote from of Denis Wood and John Krygier explains the power of rhetoric because the ability to choose what to include in a map “surfaces the problem of knowledge in an inescapable fashion as do symbolization, generalization and classification”. Lastly and possible her most crucial key to creating equal representation in data visualization is through dissent. Allowing for additional and even opposing data creates a more balanced approach reducing the power of misrepresentation. The depiction should aim to include the perspectives of all groups by promoting diversity. I believe that we should promote education surrounding the power of rhetoric especially in maps and visuals. A great example of the rhetorical power in maps is the numerous controversies like the borders of India and Pakistan in Google Maps. Google Maps exemplifies how even what is defined as a fact to some people may be viewed as false by another. A person must understand the controversy as well as oppressions in data to truly grasp its value. Donna haraway explains foolish nature of data, “Vision in this technological feast becomes unregulated gluttony; all seems not just mythically about the god trick of seeing everything from nowhere”. The concept of seeing everything from nowhere is the reason why data is not able to represent the whole world. I agree largely in part with D’Ignazio, and believe the problems and solutions spawned from big data will remain prevalent in the modern technological age. The ability to control and manipulate big data can be a powerful but flawed tool.