Amazon Scraps Secret AI Recruiting Tool that Showed Bias against Women
Bibliographic Data
| ID | 20046865 |
|---|---|
| Authors | Jeffrey Dastin (corresponding author) |
| Year | 2022 |
| Pages | 296-299 |
| Publication date | 2022-03-16 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | CHAPTER |
| Venue | Ethics of Data and Analytics (SOURCE_BOOK) |
| Publisher | Auerbach Publications (PUBLISHER) |
| DOI | 10.1201/9781003278290-44 |
| OpenAlex | W4220820301 |
| ISBN | 9781003278290 |
| Language | EN |
| Citations received | 111 |
Automation has been key to Amazon's e-commerce dominance, be it inside warehouses or driving pricing decisions. The company's experimental hiring tool used artificial intelligence to give job candidates scores ranging from one to five stars - much like shoppers rate products on Amazon. In effect, Amazon's system taught itself that male candidates were preferable. It penalized resumes that included the word “women's,” as in “women's chess club captain.” And it downgraded graduates of two all-women's colleges, according to people familiar with the matter. Amazon's experiment began at a pivotal moment for the world's largest online retailer. Machine learning was gaining traction in the technology world. The American civil liberties union is currently challenging a law that allows criminal prosecution of researchers and journalists who test hiring websites' algorithms for discrimination
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| Unique citing works | 111 |
|---|---|
| Citations per year | 15,86 |
| Citation span | 2019 - 2026 (8) |
| Citation velocity | current |
| Highly cited | Yes |
| Citation types | Neutral: 81 |