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Impact, Ethics, and Issues with Generative AI

Rav Ahuja

In this course, you will explore the impact of generative artificial intelligence (AI) on society, the workforce, organizations, and the environment.

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In this course, you will explore the impact of generative artificial intelligence (AI) on society, the workforce, organizations, and the environment.

This course is suitable for anyone interested in learning about the ethical, economic, and social implications of generative AI and how generative AI can be used responsibly. It will benefit professionals, executives, policymakers, and students.

In this course, you will learn about the ethical concerns of generative AI, including data privacy, biases, copyright infringement, and hallucination. You will identify the misuses related to generative AI, including deepfakes.

Further, in the course, you will examine the considerations for the responsible use of generative AI. You will explore the broader implications of generative AI on transparency, accountability, privacy, and safety. Finally, you will learn about the socioeconomic impacts of generative AI.

The examples and cases included in the course help to realize the considerations for generative AI in real-life scenarios. You will hear from practitioners about the realities, limitations, and ethical considerations of generative AI.

What's inside

Learning objectives

  • • describe the limitations of generative ai and the related concerns.
  • • discuss the ethical issues, concerns, and misuses associated with generative ai.
  • • explain the considerations for the responsible use of generative ai.
  • • discuss the economic and social impact of generative ai.
  • • explain the impact of generative ai on jobs and the workforce.

Syllabus

Module 1: Limitations and Ethical Issues of Generative AI
• Video: Course Introduction
• Reading: Course Overview
• Reading: Program Overview
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• Reading: Helpful Tips for Course Completion
• Video: Limitations of Generative AI
• Video: Issues and Concerns about Generative AI
• Video: Hallucinations of Text and Image-Generating LLMs
• Video: Hallucinations of Code-Generating LLMs
• Hands-on Labs: Hallucinations of LLMs
• Video: AI Portraits and Deepfakes
• Hands-on Labs: Creating AI Portraits
• Video 7: Legal Issues and Implications of Generative AI
• Reading: Module Summary
• Practice Quiz - Limitations, Concerns, and Issues of Generative AI
• Graded Quiz - Limitations and Ethical Issues of Generative AI
• Discussion Prompt: Ethical Issues about Generative AI
Module 2: Social and Economic Impact and Responsible Generative AI
• Video: Considerations for Responsible Generative AI
• Video: Implementing Responsible Generative AI across Domains
• Hands-on Lab: Ethical Considerations for Generative AI in Different Domains
• Video: AI Ethics: Perspective of Key Players
• Reading: Generative AI and Corporate Social Responsibility
• Video: Economic Implications of Generative AI
• Video: Social Implications of Generative AI
• Video: A Reimagined Workforce with Generative AI
• Reading: Module Summary
• Practice Quiz: Social and Economic Impact and Responsible Generative AI
• Graded Quiz: Social and Economic Impact and Responsible Generative AI
• Discussion Prompt: Generative AI’s Influence on Mental Health
Module 3: Course Quiz, Project, and Wrap-up
• Glossary - Generative AI: Introduction and Applications
• Reading: Implementing Responsible Generative AI
• Final Project: Preparing Your Mind for Generative AI
• Graded Quiz - Generative AI: Impact, Considerations, and Ethical Issues
• Reading: Congratulations and Next Steps
• Reading: Thanks from the Course Team

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Exploers the impact of generative AI across society, the workforce, organizations, and the environment
Provides ethical, economic, and social implications of generative AI
Suitable for professionals, executives, policymakers, and students
Covers ethical concerns including data privacy, biases, copyright infringement, and hallucination
Examines how generative AI can be used responsibly

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Activities

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Career center

Learners who complete Impact, Ethics, and Issues with Generative AI will develop knowledge and skills that may be useful to these careers:
AI Ethicist
AI Ethicists analyze the ethical implications of AI. They develop frameworks and guidelines for the responsible use of AI. This course can help AI Ethicists understand the ethical implications of generative AI. It can also help them develop strategies to mitigate potential risks and ensure the responsible use of AI.
AI Policy Advisor
AI Policy Advisors develop policies and regulations for the use of AI. They work with governments and organizations to ensure that AI is used in a responsible and ethical manner. This course can help AI Policy Advisors understand the ethical implications of generative AI. It can also help them develop strategies to mitigate potential risks and ensure the responsible use of AI.
AI Researcher
AI Researchers develop new AI algorithms and techniques. They explore the frontiers of AI and work to push the boundaries of what is possible. This course can help AI Researchers understand the ethical implications of developing and using generative AI. It can also help them develop strategies to mitigate potential biases and ensure the responsible use of AI.
Data Scientist
Data Scientists analyze and interpret large amounts of data to extract meaningful insights. They design and implement analytical models to solve complex business problems. This course on the impact, ethics, and issues with generative AI can help Data Scientists better understand the ethical implications of using AI-generated data in their models. It can also help them develop strategies to mitigate potential biases and ensure the responsible use of AI.
Machine Learning Engineer
Machine Learning Engineers design, develop, and deploy machine learning models. They work closely with Data Scientists to ensure that models are accurate and efficient. This course can help Machine Learning Engineers understand the ethical implications of using generative AI models. It can also help them develop strategies to mitigate potential biases and ensure the responsible use of AI.
Data Privacy Officer
Data Privacy Officers are responsible for protecting the privacy of personal data. They develop and implement policies and procedures to ensure that data is collected, used, and stored in a compliant manner. This course can help Data Privacy Officers understand the ethical implications of using generative AI to generate data. It can also help them develop strategies to mitigate potential privacy risks.
Software Engineer
Software Engineers design, develop, and maintain software applications. They work with a variety of technologies, including AI and machine learning. This course can help Software Engineers understand the ethical implications of using generative AI in their applications. It can also help them develop strategies to mitigate potential biases and ensure the responsible use of AI.
Risk Manager
Risk Managers are responsible for identifying, assessing, and mitigating risks. They work with a variety of stakeholders, including executives, managers, and employees. This course can help Risk Managers understand the ethical implications of using generative AI in their risk assessments. It can also help them develop strategies to mitigate potential risks and ensure the responsible use of AI.
Sales Manager
Sales Managers are responsible for leading sales teams and generating revenue. They work with a variety of customers, including businesses and individuals. This course can help Sales Managers understand the ethical implications of using generative AI in their sales pitches. It can also help them develop strategies to mitigate potential risks and ensure the responsible use of AI.
Business Analyst
Business Analysts analyze business processes and develop solutions to improve efficiency. They work with a variety of stakeholders, including executives, managers, and employees. This course can help Business Analysts understand the ethical implications of using generative AI in their analyses. It can also help them develop strategies to mitigate potential risks and ensure the responsible use of AI.
Product Manager
Product Managers are responsible for developing and managing product roadmaps. They work with a variety of stakeholders, including engineers, designers, and marketers. This course can help Product Managers understand the ethical implications of using generative AI in their products. It can also help them develop strategies to mitigate potential risks and ensure the responsible use of AI.
Marketing Manager
Marketing Managers are responsible for developing and executing marketing campaigns. They work with a variety of channels, including social media, email, and print. This course can help Marketing Managers understand the ethical implications of using generative AI in their campaigns. It can also help them develop strategies to mitigate potential risks and ensure the responsible use of AI.
UX Designer
UX Designers design the user experience for software applications. They work to ensure that applications are easy to use and enjoyable. This course can help UX Designers understand the ethical implications of using generative AI in their designs. It can also help them develop strategies to mitigate potential biases and ensure the responsible use of AI.
Compliance Officer
Compliance Officers are responsible for ensuring that organizations comply with laws and regulations. They work with a variety of stakeholders, including executives, managers, and employees. This course can help Compliance Officers understand the ethical implications of using generative AI in their compliance programs. It can also help them develop strategies to mitigate potential risks and ensure the responsible use of AI.
Lawyer
Lawyers advise clients on legal matters and represent them in court. They work with a variety of clients, including individuals, businesses, and governments. This course can help Lawyers understand the ethical implications of using generative AI in their legal practice. It can also help them develop strategies to mitigate potential risks and ensure the responsible use of AI.

Reading list

We've selected 11 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 Impact, Ethics, and Issues with Generative AI.
Explores the challenges of aligning the goals of artificial intelligence with human values. It discusses the risks of misalignment and proposes strategies for mitigating them.
Provides a practical guide to building and deploying generative AI models. It covers topics such as model selection, training, and evaluation.
This textbook provides a comprehensive overview of artificial intelligence, including generative AI. It covers topics such as search, planning, machine learning, and natural language processing.
Explores the economic and social implications of artificial intelligence, including generative AI. It discusses topics such as the impact of AI on jobs, wages, and inequality.
Provides a comprehensive overview of deep learning, which type of machine learning that is used to train generative AI models. It covers topics such as neural networks, convolutional neural networks, and recurrent neural networks.
Explores the potential risks and benefits of artificial intelligence, including generative AI. It discusses topics such as the possibility of AI surpassing human intelligence and the need for responsible AI development.
Provides a практический guide to building and deploying deep learning models using Python. It covers topics such as neural networks, convolutional neural networks, and recurrent neural networks.
Explores the future of humanity in the context of artificial intelligence, including generative AI. It discusses topics such as the potential for AI to solve global problems and the risks of AI misuse.
Provides a practical guide to applying artificial intelligence, including generative AI, to real-world problems. It covers topics such as data collection, model selection, and deployment.
Provides a clear and accessible introduction to artificial intelligence, including generative AI. It covers topics such as machine learning, natural language processing, and computer vision.

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