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Navigating Generative AI Risks for Leaders

Jeff Maggioncalda, Coursera CEO

This course delves into the various risks and concerns associated with Generative AI, including business model risks, inaccuracies in AI-generated content, data security, and privacy concerns.

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This course delves into the various risks and concerns associated with Generative AI, including business model risks, inaccuracies in AI-generated content, data security, and privacy concerns.

It emphasizes the importance of the CEO in understanding and addressing these risks. A significant part of this course is dedicated to exploring the ethical considerations for using GenAI. It highlights the importance of developing responsible AI principles and practices, guiding CEOs in creating ethical principles for Responsible AI tailored specifically to their own companies. The course also focuses on the critical issues of data security and privacy in the use of GenAI. It concludes by providing an overview of the legal and regulatory landscape for GenAI, offering guidance on how to navigate this landscape effectively and ensure legal and regulatory compliance in the use of GenAI.

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What's inside

Syllabus

Ethical, data, and legal considerations for GenAI
This short course discusses the various risks and concerns associated with Generative AI, including business model risks, inaccuracies in AI-generated content, data security, and privacy concerns. It emphasizes the importance of understanding and addressing these risks. A significant part of this module is dedicated to exploring the ethical considerations for using GenAI. It highlights the importance of developing responsible AI principles and practices, guiding CEOs in creating ethical principles for Responsible AI tailored specifically to their own companies. The course also focuses on the critical issues of data security and privacy in the use of GenAI. It concludes by providing an overview of the legal and regulatory landscape for GenAI, offering guidance on how to navigate this landscape effectively and ensure legal and regulatory compliance in the use of GenAI.

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Provides an overview of the ethical, data, and legal considerations associated with Generative AI
Emphasizes the importance of the CEO in understanding and addressing risks associated with Generative AI
Guides CEOs in creating ethical principles for Responsible AI tailored to their companies
Covers the critical issues of data security and privacy in the use of Generative AI
Provides an overview of the legal and regulatory landscape for Generative AI
Offers guidance on navigating the legal and regulatory landscape for Generative AI

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Career center

Learners who complete Navigating Generative AI Risks for Leaders will develop knowledge and skills that may be useful to these careers:
AI Policy Advisor
AI Policy Advisors use their expertise to craft policy that governs AI development and deployment. A solid understanding of the ethical and legal concerns surrounding Generative AI is vital to an AI Policy Advisor's ability to create these policies. This course, therefore, helps provide the ethical framework for success in this role.
AI Risk Analyst
AI Risk Analysts are responsible for identifying and mitigating risks associated with AI systems. The risks and concerns this course covers are all within the scope of an AI Risk Analyst's work. This course may help AI Risk Analysts avoid costly risks by increasing their knowledge of the field.
AI Auditor
AI Auditors are tasked with assessing the risks and vulnerabilities of AI systems. This course provides the foundational knowledge of risks and concerns needed to be successful in this role.
Data Privacy Officer
Data Privacy Officers develop and implement policies that ensure an organization complies with privacy regulations. This course may help Data Privacy Officers understand the privacy concerns associated with Generative AI, a rapidly developing field.
Machine Learning Engineer
Machine Learning Engineers design and develop AI systems. While this course does not teach the technical skills required to be a Machine Learning Engineer, it may be helpful for understanding the ethical and legal considerations of Generative AI, an increasingly popular machine learning technique.
AI Compliance Officer
AI Compliance Officers develop strategies to ensure that AI systems comply with relevant laws and regulations. This course may help AI Compliance Officers stay up-to-date on emerging legal and regulatory issues surrounding Generative AI.
AI Governance Specialist
AI Governance Specialists are responsible for developing and implementing governance frameworks for AI systems. This course may help AI Governance Specialists understand the ethical and legal considerations of Generative AI, a powerful tool which needs to be used responsibly.
Data Scientist
Data Scientists collect and analyze data to uncover insights. This course may help Data Scientists understand the potential risks and biases associated with Generative AI, a tool that can generate new data.
AI Project Manager
AI Project Managers oversee the planning and execution of AI projects. This course may help AI Project Managers identify and mitigate the risks associated with Generative AI, which can be used in a wide variety of applications.
AI Consultant
AI Consultants advise organizations on the development and implementation of AI systems. This course may help AI Consultants understand the legal and regulatory risks associated with Generative AI.
Technical Writer
Technical Writers create documentation for AI systems. This course may help Technical Writers understand the ethical and legal considerations of Generative AI, which can be used to generate text and other forms of content.
Business Analyst
Business Analysts identify and analyze business needs. This course may help Business Analysts understand the potential benefits and risks of Generative AI.
CIO
CIOs oversee the information technology (IT) operations of an organization. This course may be helpful for CIOs who want to understand the risks and opportunities associated with Generative AI.
CTO
CTOs are responsible for the technology strategy of an organization. This course may be helpful for CTOs who want to understand the risks and opportunities associated with Generative AI.
CEO
CEOs are responsible for the overall success of an organization. This course may be helpful for CEOs who want to understand the risks and opportunities associated with Generative AI.

Reading list

We've selected eight books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Navigating Generative AI Risks for Leaders.
Provides a comprehensive overview of the ethical and societal implications of AI, with a particular focus on the development and use of responsible AI systems. It covers topics such as fairness, accountability, transparency, and privacy, and offers practical guidance on how to design and implement AI systems that align with human values.
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Provides a comprehensive overview of the safety and security risks associated with AI, and offers practical guidance on how to mitigate these risks. It covers topics such as AI safety, AI security, and AI ethics.
Provides a comprehensive overview of AI, covering topics such as machine learning, natural language processing, and computer vision. It valuable resource for anyone who wants to learn more about the technical foundations of AI.
Provides a comprehensive overview of deep learning, a subfield of AI that has achieved remarkable success in recent years. It covers topics such as neural networks, convolutional neural networks, and recurrent neural networks.
Provides a comprehensive overview of computer vision, a subfield of AI that deals with the understanding of images and videos. It covers topics such as image formation, image processing, and object recognition.
Provides a comprehensive overview of reinforcement learning, a subfield of AI that deals with the learning of optimal behavior in complex environments. It valuable resource for anyone who wants to learn more about the theoretical foundations of reinforcement learning.
Provides a practical introduction to machine learning for data scientists. It covers topics such as supervised learning, unsupervised learning, and deep learning. It valuable resource for anyone who wants to learn how to apply machine learning to real-world problems.
Provides a comprehensive overview of deep learning for natural language processing. It covers topics such as word embeddings, recurrent neural networks, and transformer models. It valuable resource for anyone who wants to learn more about the theoretical foundations of deep learning for natural language processing.

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