UNIT 2 DIGITAL FRAMEWORK AND MODELS.pptx

UNIT 2 DIGITAL FRAMEWORK AND MODELS.pptx

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  UNIT II FRAMEWORK AND MODELS
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  Introduction to AI Governance AIgovernance is a critical framework for managing the ethical use of artificial intelligence. It involves creating policies, guidelines, and regulations to ensure that AI systems are developed and used in a responsible and fair manner.
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  Human-right centered designin AI Governance 1 Human Rights Integration Integrating human rights principles into AI governance ensures that the design, development, and deployment of AI systems respect and protect fundamental human rights. 2 Community Engagement Engaging diverse communities in the design process helps prioritize the rights and needs of marginalized groups, promoting inclusivity and fairness in AI governance. 3 Ethical Impact Assessment Conducting comprehensive ethical impact assessments ensures that human rights considerations are deeply embedded in AI governance processes at all stages.
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  Normative models forAI Governance Legal Frameworks Establishing legal and regulatory frameworks helps define the boundaries and responsibilities of AI development and use within a society. Technical Standards Developing technical standards provides a basis for consistent and ethical AI governance practices, ensuring interoperability and compatibility across systems. Ethical Guidelines Formulating ethical guidelines contributes to creating a moral compass for developers and users, guiding the ethical use of AI technologies.
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  Role of professionalnorms in AI Governance 1 Ethical Education Professional norms provide the foundation for ethical education, shaping the behavior and decision-making of AI professionals. 2 Accountability Frameworks Establishing accountability frameworks ensures that AI professionals are held responsible for the ethical implications of their work, fostering trust and transparency in AI governance. 3 Peer Review Mechanisms Implementing peer review mechanisms enables professionals to assess each other's work, encouraging quality and ethical standards in AI development and deployment.
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  Teaching Machines andAI Governance Educational Curricula Educational programs and curricula focusing on AI governance are essential to equip future professionals with ethics-driven AI design and management skills. Ethics Integration Integrating ethical considerations into machine learning and AI algorithm design is crucial for embedding responsible decision-making into AI systems. Training Initiatives Developing specialized training initiatives for AI governance fosters a culture of responsibility and awareness among AI practitioners and developers.
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  Challenges in implementingAI Governance Algorithmic Bias Addressing and mitigating algorithmic bias remains a crucial challenge to ensure fairness and equity in AI governance and decision-making processes. Data Privacy Protecting user privacy and ensuring data transparency pose significant challenges in the implementation of effective AI governance policies and practices. Regulatory Compliance Navigating complex and evolving regulatory landscapes presents challenges for organizations in complying with AI governance standards and regulations.
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  Case studies inAI Governance Healthcare Applications Exploring AI governance case studies in healthcare highlights challenges and best practices in applying ethical AI principles to life-critical systems. Financial Sector Examining AI governance in the financial sector reveals strategies and implications for responsible AI implementation and risk management. Smart City Solutions Smart city initiatives present AI governance case studies that demonstrate the balance between innovation, privacy, and public interest in urban environments.
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  Conclusion and keytakeaways 3 Ethical Principles The foundation of AI governance lies in promoting ethical principles, transparency, and accountability across all AI initiatives. 10 Global Impact AI governance has a global impact, influencing economic, social, and legal landscapes worldwide. 100K+ Future Prospects AI governance shapes the future, with projections of exponential growth and continuous evolution in ethical AI practices and regulations.