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Approximating Accessibility of Regions from Incomplete Volunteered Data

Author: Asghari, H., Stolberg-Larsen, J., & Züger, T.
Published in: CHI EA '22: Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems, 1-6
Year: 2022
Type: Academic articles
DOI: 10.1145/3491101.3519706

Being informed about the accessibility of neighborhoods, cities, and regions can help persons with disabilities in making travel and daily decisions. This information can also be useful and a pushing factor for supportive public policies. While accessibility mapping initiatives, such as Wheelmap.org, have enjoyed tremendous success and scale, they are still far from exhaustive, and their coverage contains biases stemming from volunteer practices. With the aid of the framework of causal statistics, we suggest approaches to adjust for these biases, with the end goal of providing helpful approximations of overall accessibility in different European geographical regions.

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Connected HIIG researchers

Jakob Stolberg-Larsen

Ehem. Wissenschaftlicher Mitarbeiter: AI & Society Lab

Hadi Asghari, Dr.

Wissenschaftlicher Mitarbeiter: AI & Society Lab

Theresa Züger, Dr.

Forschungsgruppenleiterin Public Interest AI | AI & Society Lab

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