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E-scores and e-scoring systems aggregate everything from zip codes to internet behavior to purchase history to create unregulated algorithms. These algorithms are then used to determine whether a person is worthy of things like credit cards, loans, or insurance policies.
E-scores/E-scoring Quotes in Weapons of Math Destruction
The Weapons of Math Destruction quotes below are all either spoken by E-scores/E-scoring or refer to E-scores/E-scoring. For each quote, you can also see the other terms and themes related to it (each theme is indicated by its own dot and icon, like this one:
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Chapter 8: Collateral Damage
Quotes
Since [the invention of the FICO score], the use of scoring has of course proliferated wildly. Today we’re added up in every conceivable way as statisticians and mathematicians patch together a mishmash of data, from our zip codes and Internet surfing patterns to our recent purchases. Many of their pseudoscientific models attempt to predict our creditworthiness, giving each of us so-called e-scores. These numbers, which we rarely see, open doors for some of us, while slamming them in the face of others. Unlike the FICO scores they resemble, e-scores are arbitrary, unaccountable, unregulated, and often unfair—in short, they’re WMDs.
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E-scores/E-scoring Term Timeline in Weapons of Math Destruction
The timeline below shows where the term E-scores/E-scoring appears in Weapons of Math Destruction. The colored dots and icons indicate which themes are associated with that appearance.
Chapter 8: Collateral Damage
...backed by consistently updated data, the use of scoring has changed significantly over the years. “E-scores” now aggregate everything from zip codes to internet behavior to purchase history to create arbitrary,...
(full context)
E-scores are taking society several steps backward from the fairness and transparency of the FICO scoring...
(full context)
...their operations. These companies can analyze any data they choose to and develop their own e-scores and risk correlations without explaining the methodologies behind them. O’Neil suggests that compared to the...
(full context)
Chapter 9: No Safe Zone
...proxies for responsible driving (like zip code and income) to create their own ratings, or e-scores—but because a lot of the information they use is based on credit and capital, insurance...
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