Sentiment Bias in Predictive Text Recommendations Results in Biased Writing

Prior research has demonstrated that intelligent systems make biased decisions because they are trained on biased data. As people increasingly leverage intelligent systems to enhance their productivity and creativity, could system biases affect what people create? We demonstrate that in at least one domain (writing restaurant reviews), biased system behavior leads to biased human behavior: People presented with phrasal text entry shortcuts that were skewed positive wrote more positive reviews than they did when presented with negative-skewed shortcuts. This result contributes to the pertinent debate about the role of intelligent systems in our society.

• Authors' version (pdf)
• Publisher's version (Canadian Human-Computer Communications Society / Societe canadienne du dialogue humain-machine)

Kenneth Arnold, Krysta Chauncey, and Krzysztof Gajos. Sentiment bias in predictive text recommendations results in biased writing. In Proceedings of Graphics Interface 2018, GI 2018, pages 33 - 40. Canadian Human-Computer Communications Society / Societe canadienne du dialogue humain-machine, 2018.

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