{
  "id": 8623,
  "url": "https://doi.org/10.1145/3359246",
  "title": "How Computers See Gender",
  "summary": "Investigations of facial analysis (FA) technologies-such as facial detection and facial recognition-have been central to discussions about Artificial Intelligence's (AI) impact on human beings. Research on automatic gender recognition, the classification of gender by FA technologies, has raised potential concerns around issues of racial and gender bias. In this study, we augment past work with empirical data by conducting a systematic analysis of how gender classification and gender labeling in ",
  "authors": "Morgan Klaus Scheuerman, Jacob M. Paul, Jed R. Brubaker",
  "category": "research",
  "topics": "bias-fairness,privacy-surveillance,finance-investment",
  "orgs": null,
  "regions": null,
  "published_at": "2019-11-07T00:00:00.000Z",
  "fetched_at": "2026-07-14T16:33:39.877Z",
  "source_slug": "openalex",
  "source_name": "OpenAlex",
  "source_homepage": "https://openalex.org",
  "ethics_ai_record_url": "https://ethics.ai/record/8623",
  "original_url": "https://doi.org/10.1145/3359246",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}