Generative AI Foundations: Ethical & Responsible Use of AI in IT

Generative AI    |    Intermediate
  • 15 videos | 1h 19m 23s
  • Includes Assessment
  • Earns a Badge
The rapid integration of artificial intelligence (AI) in information technology (IT) brings forth ethical responsibilities that demand critical attention. This course delves into the ethical and responsible use of AI in IT, providing IT professionals, developers, and decision-makers with the knowledge and tools needed to ensure AI models are designed and deployed ethically. Begin by exploring ethical considerations and biases and the implications of biased AI models. Then you will learn how to design an AI model while incorporating legal and compliance considerations and use anonymization to ensure privacy. You will configure content safety filters in Azure OpenAI Studio to prevent the generation of harmful content. You will discover strategies, guidelines, and legal and compliance considerations for ethical AI model development, as well as the ethical impact of AI models. Next, you will examine common AI principles and goals and dive into approaches and algorithms to help identify and reduce biases. Finally, you will investigate how ignoring sensitive features when training a predictor does not necessarily address AI model disparities.

WHAT YOU WILL LEARN

  • Discover the key concepts covered in this course
    Describe ethical considerations and biases in ai, with a focus on their impact on responsible ai model development
    Identify real-world implications of biased ai models, addressing their ethical and social consequences
    Design an ai model with a strong focus on legal and compliance considerations, ensuring alignment with regulatory requirements
    Anonymize and pseudonymize data to ensure the privacy and security of personally identifiable information (pii)
    Configure content safety filters in azure openai to prevent generative ai from producing harmful content
    Identify strategies to develop ai models that adhere to ethical standards, promoting fairness and ethical behavior
    Describe ethical guidelines and best practices for developing ai models that meet ethical and societal expectations
  • Describe and assess the ethical impacts of ai models on individuals, society, and various stakeholders
    Identify legal and compliance considerations when developing ai models with a strong ethical focus
    Identify the goals associated with each ai principle identified in the responsible ai standard
    Analyze an ai model to detect and identify biases
    Reduce the correlation between sensitive features (like race) and other variables to mitigate bias affecting model predictions
    Describe how ignoring sensitive features when training a predictor doesn’t necessarily address disparities
    Summarize the key concepts covered in this course

IN THIS COURSE

  • 1m 34s
    In this video, we will discover the key concepts covered in this course. FREE ACCESS
  • 5m 8s
    After completing this video, you will be able to describe ethical considerations and biases in AI, with a focus on their impact on responsible AI model development. FREE ACCESS
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    3.  Implications of Biased AI Models
    6m 42s
    Upon completion of this video, you will be able to identify real-world implications of biased AI models, addressing their ethical and social consequences. FREE ACCESS
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    4.  Designing AI Model with Legal and Compliance Considerations
    7m 58s
    In this video, find out how to design an AI model with a strong focus on legal and compliance considerations, ensuring alignment with regulatory requirements. FREE ACCESS
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    5.  Anonymizing Sensitive Information for AI Systems
    7m 12s
    Learn how to anonymize and pseudonymize data to ensure the privacy and security of personally identifiable information (PII). FREE ACCESS
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    6.  Preventing Harmful Content Generation
    4m 51s
    During this video, discover how to configure content safety filters in Azure OpenAI to prevent generative AI from producing harmful content. FREE ACCESS
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    7.  Strategies for Ethical AI Model Development
    7m 5s
    After completing this video, you will be able to identify strategies to develop AI models that adhere to ethical standards, promoting fairness and ethical behavior. FREE ACCESS
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    8.  Ethical Guidelines for AI Model Development
    6m 1s
    Upon completion of this video, you will be able to describe ethical guidelines and best practices for developing AI models that meet ethical and societal expectations. FREE ACCESS
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    9.  Ethical Impacts of AI Models
    8m 52s
    After completing this video, you will be able to describe and assess the ethical impacts of AI models on individuals, society, and various stakeholders. FREE ACCESS
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    10.  Legal and Compliance Considerations in Ethical AI Model Development
    3m 54s
    Upon completion of this video, you will be able to identify legal and compliance considerations when developing AI models with a strong ethical focus. FREE ACCESS
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    11.  AI Principles and Goals
    6m 3s
    After completing this video, you will be able to identify the goals associated with each AI principle identified in the Responsible AI Standard. FREE ACCESS
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    12.  Identifying Biases in AI Models
    4m 53s
    In this video, you will learn how to analyze an AI model to detect and identify biases. FREE ACCESS
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    13.  Reducing Potential Biases from Sensitive Features
    4m 21s
    Find out how to reduce the correlation between sensitive features (like race) and other variables to mitigate bias affecting model predictions. FREE ACCESS
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    14.  Ignoring Sensitive Features
    3m 44s
    Upon completion of this video, you will be able to describe how ignoring sensitive features when training a predictor doesn’t necessarily address disparities. FREE ACCESS
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    15.  Course Summary
    1m 7s
    In this video, we will summarize the key concepts covered in this course. FREE ACCESS

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