HCOct 10, 2016

Accounting for Availability Biases in Information Visualization

arXiv:1610.02857v114 citations
Originality Synthesis-oriented
AI Analysis

This work addresses decision-making biases for users of information visualization tools, but it is incremental as it builds on existing heuristics without introducing a new method.

The paper tackles the problem of availability biases in decision-making by proposing three ways visualizations can facilitate unbiased decisions, such as altering memory storage for better long-term intuitions and suggesting intuitive approximations instead of exhaustive comparisons.

The availability heuristic is a strategy that people use to make quick decisions but often lead to systematic errors. We propose three ways that visualization could facilitate unbiased decision-making. First, visualizations can alter the way our memory stores the events for later recall, so as to improve users' long-term intuitions. Second, the known biases could lead to new visualization guidelines. Third, we suggest the design of decision-making tools that are inspired by heuristics, e.g. suggesting intuitive approximations, rather than target to present exhaustive comparisons of all possible outcomes, or automated solutions for choosing decisions.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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