Isbn: 9780138073923 - responsible ai: best practices for creating trustworthy ai systems (29 resultados)

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Paperback. Condición: new. Paperback. AI systems are solving real-world challenges and transforming industries, but there are serious concerns about how responsibly they operate on behalf of the humans that rely on them. Many ethical principles and guidelines have been proposed for AI systems, but they're often too 'high-level' to be translated into practice. Conversely, AI/ML researchers often focus on algorithmic solutions that are too 'low-level' to adequately address ethics and responsibility. In this timely, practical guide, pioneering AI practitioners bridge these gaps. The authors illuminate issues of AI responsibility across the entire system lifecycle and all system components, offer concrete and actionable guidance for addressing them, and demonstrate these approaches in three detailed case studies. Samples Preview sample pages from Responsible AI: Best Practices for Creating Trustworthy AI Systems > Writing for technologists, decision-makers, students, users, and other stake-holders, the topics cover: Governance mechanisms at industry, organisation, and team levelsDevelopment process perspectives, including software engineering best practices for AISystem perspectives, including quality attributes, architecture styles, and patternsTechniques for connecting code with data and models, including key tradeoffsPrinciple-specific techniques for fairness, privacy, and explainabilityA preview of the future of responsible AI Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Paperback. Condición: New. 1st. AI systems are solving real-world challenges and transforming industries, but there are serious concerns about how responsibly they operate on behalf of the humans that rely on them. Many ethical principles and guidelines have been proposed for AI systems, but they're often too 'high-level' to be translated into practice. Conversely, AI/ML researchers often focus on algorithmic solutions that are too 'low-level' to adequately address ethics and responsibility. In this timely, practical guide, pioneering AI practitioners bridge these gaps. The authors illuminate issues of AI responsibility across the entire system lifecycle and all system components, offer concrete and actionable guidance for addressing them, and demonstrate these approaches in three detailed case studies. Writing for technologists, decision-makers, students, users, and other stake-holders, the topics cover: Governance mechanisms at industry, organisation, and team levelsDevelopment process perspectives, including software engineering best practices for AISystem perspectives, including quality attributes, architecture styles, and patternsTechniques for connecting code with data and models, including key tradeoffsPrinciple-specific techniques for fairness, privacy, and explainabilityA preview of the future of responsible AI.…

Paperback. Condición: Good. AI systems are solving real-world challenges and transforming industries, but there are serious concerns about how responsibly they operate on behalf of the humans that rely on them. Many ethical principles and guidelines have been proposed for AI systems, but they're often too 'high-level' to be translated into practice. Conversely, AI/ML researchers often focus on algorithmic solutions that are too 'low-level' to adequately address ethics and responsibility. In this timely, practical guide, pioneering AI practitioners bridge these gaps. The authors illuminate issues of AI responsibility across the entire system lifecycle and all system components, offer concrete and actionable guidance for addressing them, and demonstrate these approaches in three detailed case studies. Writing for technologists, decision-makers, students, users, and other stake-holders, the topics cover: Governance mechanisms at industry, organisation, and team levelsDevelopment process perspectives, including software engineering best practices for AISystem perspectives, including quality attributes, architecture styles, and patternsTechniques for connecting code with data and models, including key tradeoffsPrinciple-specific techniques for fairness, privacy, and explainabilityA preview of the future of responsible AI.…

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Taschenbuch. Condición: Neu. Neuware - AI systems are solving real-world challenges and transforming industries, but there are serious concerns about how responsibly they operate on behalf of the humans that rely on them. Many ethical principles and guidelines have been proposed for AI systems, but they're often too 'high-level' to be translated into practice. Conversely, AI/ML researchers often focus on algorithmic solutions that are too 'low-level' to adequately address ethics and responsibility. In this timely, practical guide, pioneering AI practitioners bridge these gaps. The authors illuminate issues of AI responsibility across the entire system lifecycle and all system components, offer concrete and actionable guidance for addressing them, and demonstrate these approaches in three detailed case studies.Writing for technologists, decision-makers, students, users, and other stake-holders, the topics cover:- Governance mechanisms at industry, organisation, and team levels- Development process perspectives, including software engineering best practices for AI- System perspectives, including quality attributes, architecture styles, and patterns- Techniques for connecting code with data and models, including key tradeoffs- Principle-specific techniques for fairness, privacy, and explainability- A preview of the future of responsible AI.…

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Condición: New. &Uumlber den AutorDr. Qinghua Lu is a principal research scientist and leads the Responsible AI science team at CSIROs Data61. She received her PhD from University of New South Wales in 2013. Her current research int.

Paperback. Condición: New. 1st. AI systems are solving real-world challenges and transforming industries, but there are serious concerns about how responsibly they operate on behalf of the humans that rely on them. Many ethical principles and guidelines have been proposed for AI systems, but they're often too 'high-level' to be translated into practice. Conversely, AI/ML researchers often focus on algorithmic solutions that are too 'low-level' to adequately address ethics and responsibility. In this timely, practical guide, pioneering AI practitioners bridge these gaps. The authors illuminate issues of AI responsibility across the entire system lifecycle and all system components, offer concrete and actionable guidance for addressing them, and demonstrate these approaches in three detailed case studies. Writing for technologists, decision-makers, students, users, and other stake-holders, the topics cover: Governance mechanisms at industry, organisation, and team levelsDevelopment process perspectives, including software engineering best practices for AISystem perspectives, including quality attributes, architecture styles, and patternsTechniques for connecting code with data and models, including key tradeoffsPrinciple-specific techniques for fairness, privacy, and explainabilityA preview of the future of responsible AI.…

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Paperback. Condición: new. Paperback. AI systems are solving real-world challenges and transforming industries, but there are serious concerns about how responsibly they operate on behalf of the humans that rely on them. Many ethical principles and guidelines have been proposed for AI systems, but they're often too 'high-level' to be translated into practice. Conversely, AI/ML researchers often focus on algorithmic solutions that are too 'low-level' to adequately address ethics and responsibility. In this timely, practical guide, pioneering AI practitioners bridge these gaps. The authors illuminate issues of AI responsibility across the entire system lifecycle and all system components, offer concrete and actionable guidance for addressing them, and demonstrate these approaches in three detailed case studies. Samples Preview sample pages from Responsible AI: Best Practices for Creating Trustworthy AI Systems > Writing for technologists, decision-makers, students, users, and other stake-holders, the topics cover: Governance mechanisms at industry, organisation, and team levelsDevelopment process perspectives, including software engineering best practices for AISystem perspectives, including quality attributes, architecture styles, and patternsTechniques for connecting code with data and models, including key tradeoffsPrinciple-specific techniques for fairness, privacy, and explainabilityA preview of the future of responsible AI Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…

Taschenbuch. Condición: Neu. Responsible AI | Best Practices for Creating Trustworthy AI Systems | Csiro (u. a.) | Taschenbuch | Kartoniert / Broschiert | Englisch | 2024 | Pearson Education (US) | EAN 9780138073923 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu. …

Paperback. Condición: Brand New. 320 pages. 9.06x7.36x0.71 inches. In Stock. This item is printed on demand.