rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Machine learning for high-risk applications
    sub title: approaches to responsible AI
  name:
    name part: Hall, Patrick
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: Curtis, James
    role:
      role term: author.
  name:
    name part: Pandey, Parul
    role:
      role term: author.
  name:
    name part: Sudjianto, Agus
    role:
      role term: writer of foreword.
  name:
    name part: Safari, an O'Reilly Media Company
  type of resource: text
  genre: Electronic books.
  origin info:
    place:
      place term: cau
    date issued: 2023
    edition: [First edition].
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource (466 pages) : illustrations
  abstract: The past decade has witnessed the broad adoption of artificial intelligence and machine learning (AI/ML) technologies. However, a lack of oversight in their widespread implementation has resulted in some incidents and harmful outcomes that could have been avoided with proper risk management. Before we can realize AI/ML's true benefit, practitioners must understand how to mitigate its risks. This book describes approaches to responsible AI--a holistic framework for improving AI/ML technology, business processes, and cultural competencies that builds on best practices in risk management, cybersecurity, data privacy, and applied social science. Authors Patrick Hall, James Curtis, and Parul Pandey created this guide for data scientists who want to improve real-world AI/ML system outcomes for organizations, consumers, and the public.
  note: Patrick Hall, James Curtis, and Parul Pandey ; foreword by Agus Sudjianto.
  note: Includes index.
  subject:
    topic: Machine learning
  subject:
    topic: Risk management
  subject:
    topic: Artificial intelligence
  classification: Q325.5 .H35 2023
  classification: 006.3/1
  identifier: 9781098102395
  identifier: 1098102398
  identifier: 9781098102401
  identifier: 1098102401
  identifier: 9781098102432
  identifier: 9781098102425 O'Reilly Media
  identifier: https://proxy.library.tamu.edu/login
  record info:
    record content source: ORMDA
    record creation date: 230425
    record change date: 20260128152201.3
    record identifier: in00004719935
    language of cataloging:
      language term: eng