Domain: Transportation/Gig Economy
Description: Pandey & Caliskan (2021) analyzed 100+ million rideshare samples in Chicago, finding that dynamic pricing algorithms systematically discriminate against neighborhoods with non-white and low-income populations.

Ethical Challenges:

• Geographic Bias: Neighborhoods with larger non-white populations charged significantly higher fares
• Socioeconomic Bias: Higher poverty areas face pricing discrimination
• Algorithmic Opacity: Dynamic pricing systems without transparency
• Historical Discrimination Reinforcement: Perpetuation of historical transportation discrimination

Public Datasets:

• Primary: Chicago Transportation Network Provider (TNP) Trips Dataset
• URL: https://data.cityofchicago.org/Transportation/Transportation-Network-Providers-Trips/m6dm-c72p
• Source: City of Chicago Open Data Portal
• GitHub Analysis: https://github.com/toddwschneider/chicago-taxi-data
• Dashboard: https://toddwschneider.com/dashboards/chicago-taxi-ridehailing-data/
• Content: 100+ million rideshare samples analyzed (2018-present)
• Includes: Uber, Lyft, Via data with anonymized fare, time, and census tract location information