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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.
Read more
In this course, you will explore the impact of generative artificial intelligence (AI) on society, the workforce, organizations, and the environment.
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/07wdbf/generative
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What's inside
Syllabus
Limitations and Ethical Issues of Generative AI
This module delves into the various limitations, concerns, and ethical issues associated with generative AI. You will gain insights into the limitations related to training data and the lack of accuracy, explainability, and interpretability. You will learn about various ethical issues and concerns around the use of generative AI, including data privacy, copyright infringement, and hallucination. You will explore the potential risks and misuses of generative AI, focusing on deepfake. Finally, you will identify the legal issues and implications around generative AI.
Read more
Syllabus
Limitations and Ethical Issues of Generative AI
This module delves into the various limitations, concerns, and ethical issues associated with generative AI. You will gain insights into the limitations related to training data and the lack of accuracy, explainability, and interpretability. You will learn about various ethical issues and concerns around the use of generative AI, including data privacy, copyright infringement, and hallucination. You will explore the potential risks and misuses of generative AI, focusing on deepfake. Finally, you will identify the legal issues and implications around generative AI.
Read more
Social and Economic Impact and Responsible Generative AI
In this module, you will examine the importance and considerations for responsible development and use of generative AI. You will discover the perspective of different key players, including IBM, about the ethical use of AI. You will also understand how corporations can use generative AI beyond the profit motive to safeguard the interests of all involved stakeholders.
Furthermore, you will explore the economic and social impact of generative AI. You will understand the potential economic growth that businesses can achieve with generative AI and how generative AI can benefit society and social well-being. Finally, you will identify the impact of generative AI on the workforce.
Course Quiz, Project, and Wrap-Up
The module includes a final project based on the concepts covered in the course. The module also includes a glossary to enhance comprehension of generative AI-related terms. This module includes a graded quiz to test and reinforce your understanding of concepts covered in the course. Finally, the module guides you through the next steps in your learning journey.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Explores the ethical issues of generative AI, such as data privacy and copyright infringement
Examines the limitations of generative AI, including the lack of accuracy and interpretability
Highlights the potential economic and social benefits of generative AI
Features practitioners sharing insights on the realities and limitations of generative AI
Provides a glossary to enhance comprehension of generative AI-related terms
Course is taught by Rav Ahuja, an experienced instructor in the field of generative AI research
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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 Generative AI: Impact, Considerations, and Ethical Issues with these
activities:
Review machine learning concepts
Show steps
Refresh and reacquaint yourself with machine learning fundamentals to prepare for this course.
Browse courses on
Machine Learning
Show steps
-
Review textbooks and notes from previous machine learning courses.
-
Read research papers and articles on recent advancements in machine learning.
-
Complete practice problems and exercises to reinforce your understanding of machine learning concepts.
Review the Fundamentals of Generative AI
Show steps
Refreshes the basics of generative AI, which will improve understanding of course concepts.
Browse courses on
Generative AI
Show steps
-
Revisit introductory materials on generative AI concepts
-
Review key algorithms and techniques used in generative AI
Organize and review course materials
Show steps
Enhance your understanding by actively organizing and reviewing course materials.
Show steps
-
Download and organize lecture slides, notes, and assignments.
-
Review materials regularly to reinforce learning.
Three other activities
Expand to see all activities and additional details
Show all six activities
Attend industry conferences on generative artificial intelligence
Show steps
Expand your knowledge and connect with experts in the field by attending industry conferences on generative artificial intelligence.
Show steps
-
Identify and register for relevant conferences.
-
Attend presentations and workshops on generative artificial intelligence.
-
Network with industry professionals, researchers, and thought leaders.
Write a blog post on generative artificial intelligence
Show steps
Demonstrate your understanding by creating a blog post that explores generative artificial intelligence and its applications.
Show steps
-
Research generative artificial intelligence and its various applications.
-
Choose a specific topic or case study to focus on.
-
Write a blog post that explains the topic clearly and provides valuable insights.
Design a generative AI application
Show steps
Put your learning into practice by designing and developing a generative AI application.
Show steps
-
Identify a problem or need that can be addressed using generative AI.
-
Choose a specific generative AI technique or tool to use.
-
Design and implement the generative AI application.
-
Test and evaluate the application's performance.
Review machine learning concepts
Show steps
Refresh and reacquaint yourself with machine learning fundamentals to prepare for this course.
Browse courses on
Machine Learning
Show steps
Show steps
Show steps
- Review textbooks and notes from previous machine learning courses.
- Read research papers and articles on recent advancements in machine learning.
- Complete practice problems and exercises to reinforce your understanding of machine learning concepts.
Review the Fundamentals of Generative AI
Show steps
Refreshes the basics of generative AI, which will improve understanding of course concepts.
Browse courses on
Generative AI
Show steps
Show steps
Show steps
- Revisit introductory materials on generative AI concepts
- Review key algorithms and techniques used in generative AI
Organize and review course materials
Show steps
Enhance your understanding by actively organizing and reviewing course materials.
Show steps
Show steps
Show steps
- Download and organize lecture slides, notes, and assignments.
- Review materials regularly to reinforce learning.
Three other activities
Expand to see all activities and additional details
Show all six activities
Attend industry conferences on generative artificial intelligence
Show steps
Expand your knowledge and connect with experts in the field by attending industry conferences on generative artificial intelligence.
Show steps
Show steps
Show steps
- Identify and register for relevant conferences.
- Attend presentations and workshops on generative artificial intelligence.
- Network with industry professionals, researchers, and thought leaders.
Write a blog post on generative artificial intelligence
Show steps
Demonstrate your understanding by creating a blog post that explores generative artificial intelligence and its applications.
Show steps
Show steps
Show steps
- Research generative artificial intelligence and its various applications.
- Choose a specific topic or case study to focus on.
- Write a blog post that explains the topic clearly and provides valuable insights.
Design a generative AI application
Show steps
Put your learning into practice by designing and developing a generative AI application.
Show steps
Show steps
Show steps
- Identify a problem or need that can be addressed using generative AI.
- Choose a specific generative AI technique or tool to use.
- Design and implement the generative AI application.
- Test and evaluate the application's performance.
Career center
Learners who complete Generative AI: Impact, Considerations, and Ethical Issues will develop knowledge and skills
that may be useful to these careers:
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers design, develop, and deploy machine learning models to solve real-world problems. This course provides valuable insights into the impact, considerations, and ethical issues of generative AI, which is becoming increasingly prevalent in machine learning. By understanding the limitations, biases, and potential risks associated with generative AI, you can develop and deploy machine learning models responsibly, ensuring their ethical use and minimizing potential harm.
Data Scientist
Data Scientist
Data Scientists leverage artificial intelligence, data, and machine learning models to solve business problems and extract meaningful insights from data. This course explores the impact, considerations, and ethical issues of generative AI, giving you a solid foundation for understanding the responsible development and use of generative AI. By understanding the limitations, ethical concerns, and potential risks of generative AI, you can effectively evaluate and mitigate these factors in your work as a Data Scientist, ensuring the ethical and responsible use of AI in data analysis.
AI Engineer
AI Engineer
AI Engineers design, develop, implement, and maintain AI systems. This course delves into the impact, considerations, and ethical issues of generative AI, which is a rapidly growing subfield within AI. By understanding the unique challenges and opportunities presented by generative AI, you can develop and implement AI systems responsibly, addressing ethical concerns and ensuring their beneficial use in various applications.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software applications. This course explores the impact, considerations, and ethical issues of generative AI, which is increasingly incorporated into software development. By understanding the potential benefits and risks associated with generative AI, you can effectively integrate this technology into your software development practices, ensuring the ethical use of AI in software applications.
Data Analyst
Data Analyst
Data Analysts collect, clean, analyze, and interpret data to extract meaningful insights and inform decision-making. This course provides a comprehensive overview of the impact, considerations, and ethical issues of generative AI, which is increasingly used in data analysis. By understanding the potential benefits and limitations of generative AI, you can effectively evaluate and utilize this technology to enhance your data analysis practices and ensure ethical data handling.
Product Manager
Product Manager
Product Managers are responsible for the development, launch, and management of products. This course provides insights into the impact, considerations, and ethical issues of generative AI, which is becoming increasingly relevant in product development. By understanding the potential benefits and limitations of generative AI, you can make informed decisions about incorporating this technology into your product development strategy, ensuring the ethical use of AI and enhancing the value of your products.
Privacy Officer
Privacy Officer
Privacy Officers are responsible for protecting the privacy of individuals and ensuring compliance with privacy laws and regulations. This course provides insights into the impact, considerations, and ethical issues of generative AI, which is increasingly used in data processing and analysis. By understanding the potential benefits and risks associated with generative AI, you can effectively evaluate and utilize this technology to enhance your privacy practices, ensuring the ethical use of AI and safeguarding the privacy of individuals.
Business Analyst
Business Analyst
Business Analysts analyze business needs and processes to improve efficiency and effectiveness. This course delves into the impact, considerations, and ethical issues of generative AI, which is increasingly used in business analysis. By understanding the potential benefits and risks associated with generative AI, you can effectively evaluate and utilize this technology to enhance your business analysis practices, ensuring ethical data handling and informed decision-making.
Compliance Officer
Compliance Officer
Compliance Officers ensure that an organization complies with applicable laws, regulations, and ethical standards. This course explores the impact, considerations, and ethical issues of generative AI, which is becoming increasingly relevant in compliance management. By understanding the potential benefits and limitations of generative AI, you can effectively evaluate and utilize this technology to enhance your compliance practices, ensuring the ethical use of AI and minimizing legal and regulatory risks for your organization.
Risk Manager
Risk Manager
Risk Managers identify, assess, and mitigate risks to an organization. This course provides a comprehensive overview of the impact, considerations, and ethical issues of generative AI, which is becoming increasingly prevalent in risk management. By understanding the potential benefits and limitations of generative AI, you can effectively evaluate and utilize this technology to enhance your risk management practices, ensuring the ethical use of AI and minimizing potential risks to your organization.
IT Auditor
IT Auditor
IT Auditors evaluate the effectiveness of an organization's internal controls and provide assurance to management. This course provides a comprehensive overview of the impact, considerations, and ethical issues of generative AI, which is becoming increasingly prevalent in IT auditing. By understanding the potential benefits and limitations of generative AI, you can effectively evaluate and utilize this technology to enhance your IT auditing practices, ensuring the ethical use of AI and providing reliable assurance to management.
Cybersecurity Analyst
Cybersecurity Analyst
Cybersecurity Analysts protect computer networks and systems from unauthorized access, use, disclosure, disruption, modification, or destruction. This course delves into the impact, considerations, and ethical issues of generative AI, which is increasingly used in cybersecurity. By understanding the potential benefits and limitations of generative AI, you can effectively evaluate and utilize this technology to enhance your cybersecurity practices, ensuring the ethical use of AI and protecting your organization from cyber threats.
Sales Manager
Sales Manager
Sales Managers lead and manage sales teams to achieve revenue targets. This course delves into the impact, considerations, and ethical issues of generative AI, which is increasingly used in sales. By understanding the potential benefits and limitations of generative AI, you can effectively evaluate and utilize this technology to enhance your sales practices, ensuring the ethical use of AI and maximizing revenue generation for your organization.
Marketing Manager
Marketing Manager
Marketing Managers plan and execute marketing campaigns to promote products or services. This course provides insights into the impact, considerations, and ethical issues of generative AI, which is becoming increasingly prevalent in marketing. By understanding the potential benefits and limitations of generative AI, you can effectively evaluate and utilize this technology to enhance your marketing practices, ensuring the ethical use of AI and maximizing the impact of your marketing campaigns.
Financial Analyst
Financial Analyst
Financial Analysts analyze financial data to provide insights and recommendations for investment decisions. This course explores the impact, considerations, and ethical issues of generative AI, which is becoming increasingly used in financial analysis. By understanding the potential benefits and limitations of generative AI, you can effectively evaluate and utilize this technology to enhance your financial analysis practices, ensuring the ethical use of AI and making informed investment decisions.
For more career information including salaries, visit:
OpenCourser.com/course/07wdbf/generative
Reading list
We've selected seven 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
Generative AI: Impact, Considerations, and Ethical Issues.
Provides a hands-on introduction to deep learning, a foundational technology for generative AI. It covers neural networks, training techniques, and applications, equipping learners with the technical skills to understand and work with generative AI systems.
Save
Examines the phenomenon of deepfakes, a specific type of generative AI used to create realistic fake videos and images. It explores the ethical, legal, and social implications of deepfakes, providing a deeper understanding of their potential misuses.
Save
Explores the potential long-term implications of AI, including the potential for AI to surpass human intelligence and the impact on human society.
Provides a practical introduction to deep learning for coders, with a focus on using the Fastai and PyTorch libraries.
Provides a concise and accessible introduction to machine learning, with a focus on the key concepts and algorithms.
Provides a probabilistic perspective on machine learning, covering a wide range of topics from the basics to the latest advances.
Save
Comprehensive textbook on deep learning, covering a wide range of topics from the basics to the latest advances.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/07wdbf/generative
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Effort
3 weeks of study, 1–2 hours/week
Level
Introductory
Via
Coursera
Institution
IBM
Instructor
Rav Ahuja
Language
English
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This course belongs to a
collection
called
Generative AI Fundamentals. It's comprised of three courses:
- Generative AI: Foundation Models and Platforms
- Generative AI: Impact, Considerations, and Ethical Issues (viewing)
- Generative AI: Business Transformation and Career Growth
Good to know
Explores the ethical issues of generative AI, such as data privacy and copyright infringement
Examines the limitations of generative AI, including the lack of accuracy and interpretability
Highlights the potential economic and social benefits of generative AI
Features practitioners sharing insights on the realities and limitations of generative AI
Provides a glossary to enhance comprehension of generative AI-related terms
Course is taught by Rav Ahuja, an experienced instructor in the field of generative AI research
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