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    TOWARDS SUSTAINABLE ARTIFICIAL INTELLIGENCE

    Ref:
    959021

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    So far, little effort has been devoted to developing practical approaches on how to develop and deploy AI systems that meet certain standards and principles. This is despite the importance of principles such as privacy, fairness, and social equality taking centre stage in discussions around AI. However, for an organization, failing to meet those standards can give rise to significant lost opportunities. It may further lead to an organization's demise, as the example of Cambridge Analytica demonstrates. It is, however, possible to pursue a practical approach for the design, development, and deployment of sustainable AI systems that incorporates both business and human values and principles. This book discusses the concept of sustainability in the context of artificial intelligence. In order to help businesses achieve this objective, the author introduces the sustainable artificial intelligence framework (SAIF), designed as a reference guide in the development and deployment of AI systems. The SAIF developed in the book is designed to help decision makers such as policy makers, boards, C-suites, managers, and data scientists create AI systems that meet ethical principles. By focusing on four pillars related to the socio-economic and political impact of AI, the SAIF creates an environment through which an organization learns to understand its risk and exposure to any undesired consequences of AI, and the impact of AI on its ability to create value in the short, medium, and long term.
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    ISBN9781484272138
    SubtítuloA FRAMEWORK TO CREATE VALUE AND UNDERSTAND RISK
    Pré vendaNão
    Peso230g
    Autor para link
    Livro disponível - pronta entregaNão
    Dimensões23.5 x 15.49 x 0.91
    IdiomaInglês
    Tipo itemLivro Importado
    Número de páginas140
    Número da edição1ª EDIÇÃO - 2021
    Código Interno959021
    Código de barras9781484272138
    AcabamentoPAPERBACK
    AutorTSAFACK CHETSA, GHISLAIN LANDRY
    EditoraAPRESS
    Sob encomendaSim
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