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
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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
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1m 34sIn this video, we will discover the key concepts covered in this course. FREE ACCESS
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5m 8sAfter 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 Models6m 42sUpon 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 Considerations7m 58sIn 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 Systems7m 12sLearn 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 Generation4m 51sDuring 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 Development7m 5sAfter 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 Development6m 1sUpon 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 Models8m 52sAfter 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 Development3m 54sUpon 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 Goals6m 3sAfter 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 Models4m 53sIn 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 Features4m 21sFind 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 Features3m 44sUpon 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 Summary1m 7sIn this video, we will summarize the key concepts covered in this course. FREE ACCESS
EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE
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