Question

Discuss the ethical issues one should consider when creating a graph from data. Provide two examples of how individuals could be unethical in the graphical display of data and explain why each is unethical.

Answer 1

Ethics in data visualization is not a new concept and the desire to alter statistics to shape the message has been in discussion for some time (Sue & Griffin 2016). Many have discussed the importance of standards and best practices for the development of data visualizations (Schriver, 1997). Scholars have long talked about the importance of ethically representing data. In the 1950s, "How to Lie with Statistics" discussed various ways in which statistical information could be misinterpreted (Huff, 1954). In the 1980s, Eduard Tufte discussed the concept of graphical integrity and the lie factor to described ways that visual information could alter the reader’s perception of information (1983). Similarly, two other publications expanded on the same concepts: "How to Lie with Charts" (Jones 2011), and "How to Lie with Maps" (Monmonier, 1991). Researchers have studied the distortion of information caused by visual encoding. Such research has looked at how visual encoding of data is perceived and compared when the position, size, color, and angle of the data visual were represented differently (Bertin, 1983; Cleveland & McGill, 1984; Rogowitz, Treinish, & Bryson, 1996). While these pivotal works all provide valuable information on the proper application and practice for the creation of data visualizations, researchers have only 9 recently started to study to what extent would someone’s perception of the information be affected when distortion techniques were utilized in a data visualization. Linda, Martin, Cantor, and Rubenstein conducted a research project that looked at how physician’s decisions regarding continuation of clinical trials could be influenced depending on the type of data visualization presented (1999). The results determined that the type of data display affected the physicians’ decisions regarding the continuation of clinic trials. Additionally, the study found that more accurate recommendations were made when physicians observed icon displays versus traditional chart types like tables, pie, and bar charts (Linda, Martin, Cantor, & Rubenstein, 1999). A recent study tested the deceptive nature of visualizations by looking solely at the way people interpreted information presented to them through a variety of data visualizations (Pandey et al., 2015). The study consisted of a user survey in which participants were randomly selected to analyze “control” and “test” data visualizations. The “test” data visualizations incorporated deceptive practices commonly utilized in data visualizations, such as Message Exaggeration/Understatements and Message Reversal. The results of the study determined that participants were more likely to be misled in their interpretations and incorrectly answer questions pertaining to the visualization when deceptive practices were used. It has been pointed out that data is a representation of real life (Yau, 2013). This statement implies that data or the representation of data is a mirror of fact-based events within real life. One definition of data visualization states “[t]he representation and presentation of data that exploits our visual perception abilities in order to amplify cognition” (Kirk, 2012, p. 17). Analyzing these two statements together, the role of the 10 information developer is to ensure data visualizations are both truthful to real life and represented in a way that it is easy to comprehend. Knowing that the goal of information design is to represent understood data for the purpose of amplifying cognition, information developers should be mindful of ethical issues surrounding data visualization to ensure they are not exploiting the reader’s perceptions of fact by injecting fiction or representing the data incorrectly. Furthermore, our ethical codes of conduct as information developers mandates that we provide truthful information to our audience.

1. Message Exaggeration/Understatement

Message Exaggeration/Understatement occurs when the facts are not distorted, but the way the information is presented is altered to intentionally or unintentionally exaggerate the facts. Types of ethical transgressions or deceptive techniques used in Message Exaggeration/Understatement include a truncated axis, area as quantity, and aspect ratio. Each of these examples employs altering some element of the visual to exaggerate or reduce the appearance of visual for the desired appearance.

2. Message Reversal

Message Reversal encourages the user to interpret the fact in the message incorrectly, The most common ethical transgression or deceptive technique used for Message Reversal is when the axis of a chart is inverted or flipped.

quantity/time 3 100 2 4 2 4 100 quantity/time Control