Datasheets for Datasets.

The authors discuss the use of datasheets for the collection and use of datasets in machine learning. They mention the need for datasheets by both data creators and data consumers, the kinds of questions that should be asked about the motivation, collection, and processing of the data, and the chall...

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Publicado en:Communications of the ACM Vol. 64; no. 12; pp. 86 - 93
Autores principales: GEBRU, TIMNIT, MORGENSTERN, JAMIE, VECCHIONE, BRIANA, VAUGHAN, JENNIFER WORTMAN, WALLACH, HANNA, III, HAL DAUMÉ, CRAWFORD, KATE
Formato: Artículo
Publicado: Association for Computing Machinery Dec2021
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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        atl: Datasheets for Datasets.
      aug:
        au:
          GEBRU, TIMNIT
          MORGENSTERN, JAMIE
          VECCHIONE, BRIANA
          VAUGHAN, JENNIFER WORTMAN
          WALLACH, HANNA
          III, HAL DAUMÉ
          CRAWFORD, KATE
        affil:
          Founder of DAIR Institute, Palo Alto, CA, USA.
          Assistant professor at the University of Washington, Seattle, WA, USA.
          Ph.D. student at Cornell University, Ithaca, NY, USA.
          Senior Principal Researcher at Microsoft Research, New York, NY, USA.
          Partner Research Manager at Microsoft Research, New York, NY, USA.
          Senior Principal Researcher at Microsoft Research MD, USA.
          Professor at the University of Maryland, College Park, MD, USA.
          Senior Principal Researcher at Microsoft Research, CA, USA.
          Research Professor at USC Annenberg, CA, USA.
      su:
        Machine learning
        Electronic data processing documentation
        Acquisition of data
        Motivation (Psychology)
        Standardization
      sug:
        subj:
          Machine learning
          Electronic data processing documentation
          Acquisition of data
          Motivation (Psychology)
          Standardization
      ab: The authors discuss the use of datasheets for the collection and use of datasets in machine learning. They mention the need for datasheets by both data creators and data consumers, the kinds of questions that should be asked about the motivation, collection, and processing of the data, and the challenges in creating more standardized datasheets.
      pubtype: Periodical
      doctype: Article
      src: R
    language: English
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