What is it about?
It is a field experiment on a novel data collection method that pays for the provision of high-quality data and discourages biased and inaccurate data. Extreme noise can be avoided by design, for example by cross-checking whether data is realistic at all. The remaining inaccuracy is decreased by the incentive design, which is transparent and provides a good user experience.
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Why is it important?
If data gets collected from crowds, it should be done responsibly. Responsibly collected data is of high quality, else it would be useless or lead to biased data-based conclusions. Incentivized data collection has many advantages, for example that individuals providing the data keep autonomy over what data is collected and tracing people becomes unnecessary, even if the data is personally measured, like fitness data.
Perspectives
Platform design, design of incentives, and transparency open up new ways for feasible and responsible data collection. Real-world applications might include learning through repeated interaction and individual as well as platform reputation as additional stakes.
Christina Timko
Read the Original
This page is a summary of: Incentive Mechanism Design for Responsible Data Governance: A Large-Scale Field Experiment, Journal of Data and Information Quality, April 2023, ACM (Association for Computing Machinery),
DOI: 10.1145/3592617.
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