The color of money.
By Tinker Ready. 2003
140 citations recorded by the source corpus.
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
- L. Elisa Celis
- Lingxiao Huang
- Nisheeth K. Vishnoi
- Vijay Keswani
- Ari Juels
- Ravikanth Pappu
- G. Dymski
- Jean-Pierre Hubaux
Citations in the corpus
- Stable and Fair Classification (2019, background): “, against African-Americans while predicting future criminals [31, 5, 8], granting loans [22], or NYPD stop-and-frisk [35].”
- RFID security and privacy: a research survey (2006, background): “• Euro banknotes: As early as 2001 [85], the media reported plans by the European Central Bank to embed RFID tags in banknotes as an anti-counterfeiting measure.”
- Squealing Euros: Privacy Protection in RFID-Enabled Banknotes (2003, background): “Even before the introduction of the Euro, concern arose that the 500 Euro banknote might emerge as a magnet for international crime [31].”
- Classification with Fairness Constraints: A Meta-Algorithm with Provable Guarantees (2018, background): “, against black people while predicting future criminals [27, 5, 7], granting loans [19] or NYPD stop-and-frisk [30], and against women while recommending jobs [18].”
- Discrimination in the Credit and Housing Markets: Findings and Challenges (2006, methodology): “The well-known Atlanta study (Dedman (1988)) divided tracts into five tiers based on median income, and three distinct tiers based on minority population. A subsequent study of Los Angeles (Dymski and Veitch (1994)) divided that city’s census tracts into quintiles based on median income and on minor”