Your Knowledge Will Blindfold You
By: Wenshan Cao
Tags: Research, Visualization

Have you ever experienced a situation where you were given a presentation for a better understanding of something of interest, but you felt perplexed during the presentation and started to worry about your ability to understand the subject? If your answer is yes, you shouldn’t worry. It’s very likely that the presenter omitted vital background information that should have been included in the presentation because they assumed you already knew that. This is a common psychological phenomenon called the “curse of knowledge”, which can seriously hinder the effectiveness of communication when someone predicts if other people have certain knowledge based on their own background and expertise.

With the advent of big data, the data visualization has become an increasingly important way of getting across the findings and patterns extracted from data. Will the curse of knowledge also affect this type of communication so that graph viewers could selectively focus on some features within a visualization while ignoring others and assume others would focus on the same? There is less direct research in this specific domain, although the curse of knowledge has been well-studied in the psychology of language, decision making and reasoning. Recently, a group of researchers conducted the first examination of the curse of knowledge in data visualization, focusing on whether well-informed people will think other viewers see the same patterns and features in a visualization given other viewers don’t have the same information they already have.

The Empirical Demonstration

The examination consisted of four experiments. In each experiment, there were three versions of a major story about public opinion poll and each version had 1 or 2 pre-determined features. Altogether the story had 5 pre-determined features. The participants were randomly given a version that included background information in a graph depicting polling data. Then they were told the experimenters would also show these graphs to other people who, however, would only read a brief introduction of what the graph was about and would not read the whole featured story. Next, the participants had 3 tasks to complete- first, they had to write down 5 salient features in descending order they predicted uninformed viewers would see; second, they needed to circle their 5 predicted features on the graph and indicated how salient they were to themselves; finally, they matched their 5 predictions with the 5 pre-determined features in the story. Essentially, the design of this experiment was to test whether an informed person (the participants) would base their predictions (5 predicted features) of what other uninformed viewers would see in the visualization on their own background knowledge (the 5 pre-determined features).

The major story was the same throughout the first 3 experiments and it was a different one in the last experiment. The stories can be found here.

In all of the first 3 experiments (Experiment 1a, 1b, 1c), researchers found that participants were more inclined to predict highlighted features in the story as visually salient to other uninformed viewers than features not highlighted. Furthermore, they considered those features salient to themselves as equally salient to other viewers who weren’t exposed to the story. There were minor differences in the design of the experiments- participants were shown the graph with annotations in Experiment 1a while the annotations were removed in Experiment 1b. The 3rd experiment 1c was a replication of Experiment 1a and 1b with a tweak to provide specific instructions to write down predictions. Some participants gave predictions irrelevant to the study in previous experiments.

Comparison between Expeirment 1a and 1b annotations.

To test the generalizability of the curse of knowledge, researchers used a different set of stories and type of graph in Experiment 4. As expected, the results were the same as the previous ones despite a different dataset and visualization in this experiment.

Conclusion

Throughout the 4 experiments, the researchers demonstrated the effect of the curse of knowledge in data visualization. While it’s unlikely to eliminate its effect, the researchers have some suggestions for mitigating it.