Ai Risk Management Framework
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Ai Rmf A Practical Guide For Nist Ai Risk Management Framework
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Author : Bobby Jenkins
language : en
Publisher:
Release Date : 2024-05-30
Ai Rmf A Practical Guide For Nist Ai Risk Management Framework written by Bobby Jenkins and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-30 with Computers categories.
Unlock the Power of Responsible AI with "AI-RMF: A PracticalGuide for NIST AI Risk Management Framework".As artificial intelligence (AI) systems become increasinglyintegrated into our daily lives, organizations face the criticalchallenge of managing the associated risks and ensuring thetrustworthy development and deployment of AI technologies."AI-RMF: A Practical Guide" is your comprehensive handbook fornavigating the complexities of AI risk management using theNational Institute of Standards and Technology's ArtificialIntelligence Risk Management Framework (AI-RMF).This book offers a deep dive into the AI-RMF, providing step-by-step guidance on implementing this powerful framework acrossvarious industries. You'll explore the history and evolution of AIrisk management, understand the key components of the AI-RMF,and learn practical strategies for applying the framework to yourorganization's unique needs.Whether you're an AI developer, data scientist, securityprofessional, business leader, or system engineer, this book isyour essential guide to operationalizing AI risk management andunlocking the full potential of AI while safeguarding yourorganization and stakeholders.
Ai Risk Management Framework
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Author :
language : en
Publisher:
Release Date : 2022
Ai Risk Management Framework written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022 with Artificial intelligence categories.
This initial draft of the Artificial Intelligence Risk Management Framework (AI RMF, or Framework) builds on the concept paper released in December 2021 and incorporates the feedback received. The AI RMF is intended for voluntary use in addressing risks in the design, development, use, and evaluation of AI products, services, and systems. Part I of the AI RMF sets the stage for why the AI RMF is important and explains its intended use and audience. Part II includes the AI RMF Core and Profiles. Part III includes a companion Practice Guide to assist in adopting the AI RMF.
Ai Risk Management Framework Concept Paper
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Author :
language : en
Publisher:
Release Date : 2021
Ai Risk Management Framework Concept Paper written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with Artificial intelligence categories.
This concept paper describes the fundamental approach proposed for the National Institute of Standards and Technology (NIST) Artificial Intelligence Risk Management Framework (AI RMF or framework). The AI RMF is intended for voluntary use and to address risks in the design, development, use, and evaluation of AI products, services, and systems. AI risk management follows similar processes as other disciplines. Nevertheless, managing AI risks presents unique challenges. A voluntary consensus-driven framework can help create and safeguard trust at the heart of AI-driven systems and business models and permit the flexibility for innovation, allowing the framework to develop along with the technology.
Artificial Intelligence Risk Management Framework Ai Rmf 1 0
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Author : Elham Tabassi
language : en
Publisher:
Release Date : 2023
Artificial Intelligence Risk Management Framework Ai Rmf 1 0 written by Elham Tabassi and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023 with Artificial intelligence categories.
As directed by the National Artificial Intelligence Initiative Act of 2020 (P.L. 116-283), the goal of the AI RMF is to offer a resource to the organizations designing, developing, deploying, or using AI systems to help manage the many risks of AI and promote trustworthy and responsible development and use of AI systems. The Framework is intended to be voluntary, rights-preserving, non-sector specific, and use-case agnostic, providing flexibility to organizations of all sizes and in all sectors and throughout society to implement the approaches in the Framework. The AI RMF is intended to be practical, to adapt to the AI landscape as AI technologies continue to develop, and to be operationalized by organizations in varying degrees and capacities so society can benefit from AI while also being protected from its potential harms.
Risk Modeling
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Author : Terisa Roberts
language : en
Publisher: John Wiley & Sons
Release Date : 2022-09-20
Risk Modeling written by Terisa Roberts and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-09-20 with Business & Economics categories.
A wide-ranging overview of the use of machine learning and AI techniques in financial risk management, including practical advice for implementation Risk Modeling: Practical Applications of Artificial Intelligence, Machine Learning, and Deep Learning introduces readers to the use of innovative AI technologies for forecasting and evaluating financial risks. Providing up-to-date coverage of the practical application of current modelling techniques in risk management, this real-world guide also explores new opportunities and challenges associated with implementing machine learning and artificial intelligence (AI) into the risk management process. Authors Terisa Roberts and Stephen Tonna provide readers with a clear understanding about the strengths and weaknesses of machine learning and AI while explaining how they can be applied to both everyday risk management problems and to evaluate the financial impact of extreme events such as global pandemics and changes in climate. Throughout the text, the authors clarify misconceptions about the use of machine learning and AI techniques using clear explanations while offering step-by-step advice for implementing the technologies into an organization's risk management model governance framework. This authoritative volume: Highlights the use of machine learning and AI in identifying procedures for avoiding or minimizing financial risk Discusses practical tools for assessing bias and interpretability of resultant models developed with machine learning algorithms and techniques Covers the basic principles and nuances of feature engineering and common machine learning algorithms Illustrates how risk modeling is incorporating machine learning and AI techniques to rapidly consume complex data and address current gaps in the end-to-end modelling lifecycle Explains how proprietary software and open-source languages can be combined to deliver the best of both worlds: for risk models and risk practitioners Risk Modeling: Practical Applications of Artificial Intelligence, Machine Learning, and Deep Learning is an invaluable guide for CEOs, CROs, CFOs, risk managers, business managers, and other professionals working in risk management.
The Artificial Intelligence Risk Management Framework
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Author : Prof Mafor Edwan
language : en
Publisher:
Release Date : 2024-06-30
The Artificial Intelligence Risk Management Framework written by Prof Mafor Edwan and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-06-30 with Computers categories.
This compilation of NIST's Artificial Intelligence resources is a student companion to the Artificial Intelligence Risk Management Framework, Trustworthy and Responsible AI Course and serves as a source of information for awareness to non-scholars. It is a great resource for everybody since artificial intelligence is into everybody's business! We are all impacted, somehow!
Advancing Accountability In Ai
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Author :
language : en
Publisher:
Release Date : 2023
Advancing Accountability In Ai written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023 with categories.
This report presents research and findings on accountability and risk in AI systems by providing an overview of how risk-management frameworks and the AI system lifecycle can be integrated to promote trustworthy AI. It also explores processes and technical attributes that can facilitate the implementation of values-based principles for trustworthy AI and identifies tools and mechanisms to define, assess, treat, and govern risks at each stage of the AI system lifecycle. This report leverages OECD frameworks - including the OECD AI Principles, the AI system lifecycle, and the OECD framework for classifying AI systems - and recognised risk-management and due-diligence frameworks like the ISO 31000 risk-management framework, the OECD Due Diligence Guidance for Responsible Business Conduct, and the US National Institute of Standards and Technology's AI risk-management framework.
Taxonomy Of Ai Risk
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Author :
language : en
Publisher:
Release Date : 2021
Taxonomy Of Ai Risk written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with Artificial intelligence categories.
This paper has been developed to address and build on responses to the Request for Information (RFI) released by NIST to help develop the AI Risk Management Framework (AI RMF). Among other things, in that RFI, NIST proposed eight characteristics of trustworthy AI. This paper aims to provide context to the eight characteristics of trustworthy AI mentioned in the RFI, clarify the distinction between characteristics and principles, and advance discussions about AI risks and forge agreements across organizations and internationally to the benefit AI design, development, use, and evaluation. This white paper focuses on the preconditions of trust in AI and aims to further engage the AI community in a collaborative process to encourage consensus regarding terminology related to risk so that these types of risk may be identified and managed.
Powering The Digital Economy Opportunities And Risks Of Artificial Intelligence In Finance
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Author : El Bachir Boukherouaa
language : en
Publisher: International Monetary Fund
Release Date : 2021-10-22
Powering The Digital Economy Opportunities And Risks Of Artificial Intelligence In Finance written by El Bachir Boukherouaa and has been published by International Monetary Fund this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-22 with Business & Economics categories.
This paper discusses the impact of the rapid adoption of artificial intelligence (AI) and machine learning (ML) in the financial sector. It highlights the benefits these technologies bring in terms of financial deepening and efficiency, while raising concerns about its potential in widening the digital divide between advanced and developing economies. The paper advances the discussion on the impact of this technology by distilling and categorizing the unique risks that it could pose to the integrity and stability of the financial system, policy challenges, and potential regulatory approaches. The evolving nature of this technology and its application in finance means that the full extent of its strengths and weaknesses is yet to be fully understood. Given the risk of unexpected pitfalls, countries will need to strengthen prudential oversight.
Machine Learning For High Risk Applications
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Author : Patrick Hall
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2023-04-17
Machine Learning For High Risk Applications written by Patrick Hall and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-04-17 with Computers categories.
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. Learn technical approaches for responsible AI across explainability, model validation and debugging, bias management, data privacy, and ML security Learn how to create a successful and impactful AI risk management practice Get a basic guide to existing standards, laws, and assessments for adopting AI technologies, including the new NIST AI Risk Management Framework Engage with interactive resources on GitHub and Colab