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Rav Ahuja
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.
Read more
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.
Read more
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.
Register for this course and see more details by visiting:
OpenCourser.com/course/5x6d8a/impact
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.
- • 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
Read more
Syllabus
Module 1: Limitations and Ethical Issues of Generative AI
• Video: Course Introduction
• Reading: Course Overview
• Reading: Program Overview
Read more
Traffic lights
Traffic lights
Read about what's good
what should give you pause 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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Reviews summary
Generative ai: ethics and impact
According to students, this course offers a comprehensive and timely overview of generative AI's impact, covering crucial ethical considerations, socioeconomic implications, and principles for responsible use. Learners highlight its value for professionals seeking to understand AI's broader effects and appreciate the engaging hands-on labs and real-world case studies. While generally perceived as a strong foundation, some note that it remains at a high-level conceptual overview and may not provide deep technical insights for advanced practitioners. The practical examples and focus on responsible AI implementation are frequently praised, making it a valuable resource for anyone navigating the evolving AI landscape.
Includes engaging labs and real-life scenarios to illustrate concepts effectively.
"The hands-on labs, like creating AI portraits, really helped solidify my understanding of the implications for me."
"I appreciated the case studies and insights from practitioners, which made the theories feel grounded in reality for me."
"The examples helped me connect the ethical considerations to real-world applications of generative AI."
Content is clear and understandable, making complex topics accessible to non-experts.
"As a non-technical professional, I found the explanations easy to follow and highly informative."
"The course does an excellent job of breaking down complex concepts without requiring deep technical knowledge on my part."
"I didn't need a background in coding or AI to grasp the key takeaways on its impact, which was great."
Emphasizes critical ethical issues and practical considerations for responsible AI use.
"I particularly appreciated the deep dive into data privacy, biases, and copyright issues covered in the modules."
"The discussions on responsible AI implementation are invaluable for me, especially working with this technology."
"This course really highlighted the importance of accountability and safety in developing AI, which I found crucial for my role."
Provides a relevant and essential introduction to generative AI's societal impact.
"I found this course provided an essential overview of generative AI's societal implications and ethical dilemmas."
"The content felt incredibly timely and relevant, helping me grasp the broader impact beyond just the technology."
"It's a great starting point for me to understand the non-technical aspects and crucial considerations of AI."
Provides a foundational understanding but lacks deep technical or algorithmic detail.
"While comprehensive, I found it somewhat high-level, and I wished for more technical depth in certain areas myself."
"If you're a developer looking for how to build ethical AI, this course is more about the 'why' than the 'how' for me."
"It's great for policy or business analysis, but for me, it wasn't for diving into the algorithms themselves."
Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Impact, Ethics, and Issues with Generative AI with these
activities:
Reach out to experts in the field of generative AI
Show steps
Connecting with experts in generative AI will provide valuable guidance and support for your learning journey.
Browse courses on
Mentorship
Show steps
-
Identify experts in the field through online directories or professional networks.
-
Reach out to them via email or LinkedIn and express your interest in learning about generative AI.
-
Request to set up a virtual or in-person meeting to discuss your aspirations and seek their advice.
Sharpening Python Skills
Show steps
Refreshing Python skills provides a strong foundation for understanding the code examples and assignments in the course.
Browse courses on
Python
Show steps
-
Review the basics of Python syntax and data structures
-
Complete a few practice problems
Attend industry events focused on generative AI
Show steps
Participating in industry events will connect you with professionals in the field and provide opportunities to learn about the latest advancements in generative AI.
Browse courses on
Generative AI
Show steps
-
Identify industry events or conferences focused on generative AI.
-
Register and attend the events.
-
Engage with speakers, exhibitors, and other attendees to gain insights and expand your knowledge.
Nine other activities
Expand to see all activities and additional details
Show all 12 activities
Review of Natural Language Processing
Show steps
Reviewing NLP will provide a strong foundation for understanding the course content.
Browse courses on
Natural Language Processing
Show steps
-
Read an article on the basics of NLP
-
Complete an online tutorial on NLP
-
Practice using an NLP library
The Ethical Algorithm
Show steps
This book provides a comprehensive overview of the ethical challenges and opportunities presented by generative AI.
View
The Ethical Algorithm: The Science of Socially...
on Amazon
Show steps
-
Read Chapter 1 to understand the foundations of AI ethics
-
Read Chapters 2-4 to explore specific ethical issues related to generative AI
Generate text using a variety of prompts
Show steps
Practicing generating text with different prompts will help you gain a better understanding of the capabilities and limitations of generative AI.
Browse courses on
Text Generation
Show steps
-
Choose a variety of prompts, including different topics, lengths, and styles.
-
Use a generative AI tool to generate text for each prompt.
-
Analyze the generated text for quality, coherence, and relevance to the prompt.
Using Generative AI Tools
Show steps
Following tutorials allows students to gain hands-on experience with generative AI tools.
Browse courses on
Generative AI Tools
Show steps
-
Choose a generative AI tool to explore
-
Follow a tutorial on using the tool
-
Experiment with the tool and explore its capabilities
Explore case studies of generative AI implementations
Show steps
Examining case studies of real-world generative AI applications will provide practical insights into the potential uses and challenges of this technology.
Browse courses on
Case Studies
Show steps
-
Identify a few case studies of generative AI implementations in different industries.
-
Read or watch the case studies to understand the problem being addressed, the solution implemented, and the outcomes achieved.
-
Discuss the implications of the case studies for the ethical and responsible use of generative AI.
Exploring Generative AI Prompts
Show steps
Practicing prompts helps students understand how to effectively interact with generative AI models.
Show steps
-
Experiment with different types of prompts
-
Get feedback on your prompts
Case Study: Responsible AI Implementation
Show steps
Creating a case study allows students to apply the concepts of responsible AI in a practical setting.
Show steps
-
Identify a real-world scenario for generative AI implementation
-
Research and analyze the ethical considerations of implementing generative AI in the scenario
-
Develop and present a plan for implementing generative AI responsibly
Develop a proposal for a generative AI project
Show steps
Creating a proposal for a generative AI project will allow you to apply your understanding of the technology and its potential applications.
Show steps
-
Define the problem or opportunity that your project will address.
-
Research potential generative AI solutions and select the most appropriate approach.
-
Develop a detailed plan for implementing and evaluating your project.
-
Write a persuasive proposal that outlines your project's objectives, methods, and expected outcomes.
Collaborative AI Project
Show steps
Working on a collaborative project allows students to share knowledge, learn from others, and improve their communication and teamwork skills.
Show steps
-
Form a team of 2-3 students
-
Brainstorm and select an AI project
-
Collaborate on developing the project
Reach out to experts in the field of generative AI
Show steps
Connecting with experts in generative AI will provide valuable guidance and support for your learning journey.
Browse courses on
Mentorship
Show steps
Show steps
Show steps
- Identify experts in the field through online directories or professional networks.
- Reach out to them via email or LinkedIn and express your interest in learning about generative AI.
- Request to set up a virtual or in-person meeting to discuss your aspirations and seek their advice.
Sharpening Python Skills
Show steps
Refreshing Python skills provides a strong foundation for understanding the code examples and assignments in the course.
Browse courses on
Python
Show steps
Show steps
Show steps
- Review the basics of Python syntax and data structures
- Complete a few practice problems
Attend industry events focused on generative AI
Show steps
Participating in industry events will connect you with professionals in the field and provide opportunities to learn about the latest advancements in generative AI.
Browse courses on
Generative AI
Show steps
Show steps
Show steps
- Identify industry events or conferences focused on generative AI.
- Register and attend the events.
- Engage with speakers, exhibitors, and other attendees to gain insights and expand your knowledge.
Nine other activities
Expand to see all activities and additional details
Show all 12 activities
Review of Natural Language Processing
Show steps
Reviewing NLP will provide a strong foundation for understanding the course content.
Browse courses on
Natural Language Processing
Show steps
Show steps
Show steps
- Read an article on the basics of NLP
- Complete an online tutorial on NLP
- Practice using an NLP library
The Ethical Algorithm
Show steps
This book provides a comprehensive overview of the ethical challenges and opportunities presented by generative AI.
View
The Ethical Algorithm: The Science of Socially...
on Amazon
Show steps
Show steps
Show steps
- Read Chapter 1 to understand the foundations of AI ethics
- Read Chapters 2-4 to explore specific ethical issues related to generative AI
Generate text using a variety of prompts
Show steps
Practicing generating text with different prompts will help you gain a better understanding of the capabilities and limitations of generative AI.
Browse courses on
Text Generation
Show steps
Show steps
Show steps
- Choose a variety of prompts, including different topics, lengths, and styles.
- Use a generative AI tool to generate text for each prompt.
- Analyze the generated text for quality, coherence, and relevance to the prompt.
Using Generative AI Tools
Show steps
Following tutorials allows students to gain hands-on experience with generative AI tools.
Browse courses on
Generative AI Tools
Show steps
Show steps
Show steps
- Choose a generative AI tool to explore
- Follow a tutorial on using the tool
- Experiment with the tool and explore its capabilities
Explore case studies of generative AI implementations
Show steps
Examining case studies of real-world generative AI applications will provide practical insights into the potential uses and challenges of this technology.
Browse courses on
Case Studies
Show steps
Show steps
Show steps
- Identify a few case studies of generative AI implementations in different industries.
- Read or watch the case studies to understand the problem being addressed, the solution implemented, and the outcomes achieved.
- Discuss the implications of the case studies for the ethical and responsible use of generative AI.
Exploring Generative AI Prompts
Show steps
Practicing prompts helps students understand how to effectively interact with generative AI models.
Show steps
Show steps
Show steps
- Experiment with different types of prompts
- Get feedback on your prompts
Case Study: Responsible AI Implementation
Show steps
Creating a case study allows students to apply the concepts of responsible AI in a practical setting.
Show steps
Show steps
Show steps
- Identify a real-world scenario for generative AI implementation
- Research and analyze the ethical considerations of implementing generative AI in the scenario
- Develop and present a plan for implementing generative AI responsibly
Develop a proposal for a generative AI project
Show steps
Creating a proposal for a generative AI project will allow you to apply your understanding of the technology and its potential applications.
Show steps
Show steps
Show steps
- Define the problem or opportunity that your project will address.
- Research potential generative AI solutions and select the most appropriate approach.
- Develop a detailed plan for implementing and evaluating your project.
- Write a persuasive proposal that outlines your project's objectives, methods, and expected outcomes.
Collaborative AI Project
Show steps
Working on a collaborative project allows students to share knowledge, learn from others, and improve their communication and teamwork skills.
Show steps
Show steps
Show steps
- Form a team of 2-3 students
- Brainstorm and select an AI project
- Collaborate on developing the project
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 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 Researcher
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.
AI Policy Advisor
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.
Data Scientist
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 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 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 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.
UX Designer
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.
Product Manager
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 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.
Sales Manager
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 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.
Risk Manager
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.
Compliance Officer
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
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.
For more career information including salaries, visit:
OpenCourser.com/course/5x6d8a/impact
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.
Save
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.
Save
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.
Save
Explores the implications of artificial intelligence, including generative AI, for human society. It discusses topics such as the future of work, the nature of consciousness, and the meaning of life in the age of AI.
Save
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.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/5x6d8a/impact
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Rating
4.6
Effort
1 to 3 hours per week for 3 weeks
Level
Introductory
Via
edX
Institution
IBM
Instructor
Rav Ahuja
Language
English
Transcript
English
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