Designing Resource Allocation Tools to Promote Fair Allocation: Do Visualization and Information Framing Matter?

TL;DR

This study investigates how interactive resource-allocation tools can mitigate cognitive biases in humanitarian decision-making by examining presentation format (text vs visualization) and information framing (group vs individual). Through three preregistered crowdsourced experiments using two charitable programs (Alpha and Zefa), the authors show that individual framing—whether in text or in visuals—tends to yield fairer allocations, and that visualization can help mainly when paired with individual framing. The results reveal a nuanced interaction between visualization and framing, with limited, context-dependent benefits from adding visuals and stronger effects for per-individual framing. The findings offer practical guidance for designing decision-support tools that promote fairness, while highlighting limitations and directions for richer metrics and broader, more realistic scenarios in future work.

Abstract

Studies on human decision-making focused on humanitarian aid have found that cognitive biases can hinder the fair allocation of resources. However, few HCI and Information Visualization studies have explored ways to overcome those cognitive biases. This work investigates whether the design of interactive resource allocation tools can help to promote allocation fairness. We specifically study the effect of presentation format (using text or visualization) and a specific framing strategy (showing resources allocated to groups or individuals). In our three crowdsourced experiments, we provided different tool designs to split money between two fictional programs that benefit two distinct communities. Our main finding indicates that individual-framed visualizations and text may be able to curb unfair allocations caused by group-framed designs. This work opens new perspectives that can motivate research on how interactive tools and visualizations can be engineered to combat cognitive biases that lead to inequitable decisions.

Figures (9)

• Figure 1: Screenshot of our instance of an interactive resource allocation tool featuring two charitable programs, used in Experiment 1 of our study. With the help of the legend (a), a donor can directly assess the result of resource allocation presented in the information display (b). Here both text and visualization representations are displayed, each presenting allocations with an individual framing. The donor can dynamically adjust how the resources are split between the two programs, using the slider (c), which automatically updates the information presented in the information display.
• Figure 2: Experiment 1: Stimulus used in the different conditions. See a demo of the tool at https://resallocdesign.github.io/
• Figure 3: Results of Experiment 1: (a) Distribution of allocation strategy chosen by participants, by Presentation Format and Framing. (b) Mean allocation granted to Zefa by condition. Error bars are 95% CIs.
• Figure 4: Results of Experiment 1: Effect of Presentation Format (a) and Framing (b) on the mean allocation (here in $), and interaction between our different factors (c). Error bars are 95% CIs.
• Figure 5: Results of Experiment 2: (a) Distribution of allocation strategy chosen by participants, by Presentation Format and Framing (see § \ref{['sec:tool']}). (b) Mean proportion of people making a fair allocation by condition. Error bars are 95% CIs.