AI+ Ethics™

  • Responsible AI Focus: Master ethical AI use aligned with business and societal values
  • Risk Mitigation: Learn to manage compliance, transparency, and AI decision-making
  • Strategic Guidance: Integrate ethical practices into AI adoption and leadership
  • Reputation Builder: Build organisational trust and credibility in AI deployments

 

¡Reserva ya!

    Incluye:

    Candidatos ideales para este curso:

    Ethics Advisor. Advise on AI development and deployment ethical issues. Ensure justice, openness, and accountability in AI technology, supporting responsible innovation.
    Policy Developer. Formulate and implement ethical and regulatory frameworks for AI adoption and governance to ensure responsible and equitable deployment.
    Ethical Standards Advisor. Provide guidance on ethical considerations in AI development and deployment, ensuring adherence to ethical principles and societal values.
    Audit Architect. Design and implement systems for ethical compliance and accountability in AI applications, conducting audits to detect and mitigate ethical risks.

    • Basic knowledge of artificial intelligence, machine learning concepts, and their applications. 
    • Understanding of the social, cultural, and political implications of AI technologies. 
    • Understanding of professional ethics, including honesty, integrity, and responsibility. 
    • Exposure to real-world case studies that highlight ethical dilemmas in AI, promoting practical understanding. 
    • Ability to critically assess AI technologies and make ethical decisions in designing, deploying, and managing AI systems. 
    • Familiarity with relevant laws, regulations, and industry standards that govern AI usage. 

    Course Overview.

    1. Course Introduction Preview

    Module 1: Overview of AI Ethics & Societal Impact.

    1. 1.1 Introduction to Ethical Considerations in AI Preview
    2. 1.2 Understanding The Societal Impact of AI Technologies Preview
    3. 1.3 Strategies for Conducting Social and Ethical Impact Assessments

    Module 2: Bias and Fairness in AI.

    1. 2.1 Exploration of Biases in Data and Algorithms Preview
    2. 2.2 Strategies for Mitigating Bias and Ensuring Fairness in AI Systems

    Module 3: Transparency and Explainable AI.

    1. 3.1 Importance of Transparent AI Systems Preview
    2. 3.2 Techniques for Explaining AI Models to Diverse Stakeholders Preview
    3. 3.3 Guided Projects on Designing and Analysis of AI Systems with Ethical Considerations

    Module 4: Privacy and Security Issues in AI.

    1. Study frameworks for holding organizations accountable for the ethical use of AI.
    2. Why it matters: Ensures ethical AI deployment and helps mitigate the consequences of potential misuse or harm.

    Module 5: Accountability and Responsibility.

    1. 5.1 Concepts of Accountability in AI Development and Deployment
    2. 5.2 Responsibilities of AI Practitioners and Organizations

    Module 6: Legal and Regulatory Issues.

    1. 6.1 Overview of Relevant Laws and Regulations Pertaining to AI
    2. 6.2 Understanding the Global Regulatory Issues for AI Technologies
    3. 6.3 Case Studies: GDPR Compliance
    4. 6.4 Legal Compliance of AI Tools

    Module 7: Ethical Decision-Making Frameworks.

    1. 7.1 Introduction to Frameworks for Making Ethical Decisions in AI
    2. 7.2 Case Studies and Applications of Ethical Decision-Making
    3. 7.3 Use of Simulation Platforms in Ethical Decision-Making

    Module 8: AI Governance & Best Practices.

    1. 8.1 Principles and Functions of International AI Governance
    2. 8.2 Best Practices for Integrating AI Ethics into Organizational Policies
    3. 8.3 Case Studies on AI Governance

    Module 9: Global AI Ethics Standards.

    1. 9.1 Explore Standards: IEEE’s Ethically Aligned Design
    2. 9.2 Comparative Case Studies on Standard Implementations
    3. 9.3 Tools for Evaluating AI Systems Against Global Standards

    Optional Module: AI Agents for Ethics and Its Implications.

    1. 1. Understanding AI Agents
    2. 2. Case Studies
    3. 3. Hands-On Practice with AI Agents

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