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Brent Summers
AI Ethics research is an emerging field, and to prove our skills, we need to demonstrate our critical thinking and analytical ability. Since it's not reasonable to jump into a full research paper with our newly founded skills, we will instead work on 3 projects that will demonstrate your ability to analyze ethical AI across a variety of topics and situations. These projects include all the skills you've learned in this AI Ethics Specialization.
Register for this course and see more details by visiting:
OpenCourser.com/course/vofv3r/artificial
What's inside
Syllabus
Introduction
Welcome to the capstone! Get to know a little bit about the projects we will be tackling in this section
Project 1 - OpenAI: GPT-3 Analysis
Read more
Syllabus
Introduction
Welcome to the capstone! Get to know a little bit about the projects we will be tackling in this section
Project 1 - OpenAI: GPT-3 Analysis
Read more
Examining bias in a predictive text model
Project 2 - Alleghany Screening Analysis
Understanding fairness issues with sensitive predictions
Project 3 - Game Theory Algorithm Design
Predicting ethical issues before they arise in model theory
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Develops skills in critical thinking and analytical ability, which are core skills for ethics
Explores scenarios across a variety of topics and situations, which helps learners think more broadly about ethics
Projects are designed to demonstrate ability to analyze ethical AI
Covers bias in predictive text models, fairness issues with sensitive predictions, and ethical issues in model theory
Instructor Brent Summers are not recognized experts on ethics
Save this course
Save Artificial Intelligence Ethics in Action to your list so you can find it easily later:
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Reviews summary
Case study-based ai ethics practice
Learners say this course is a collection of case studies (real-life situations) to practice and apply AI ethics from the field. It reviews the principles of fairness, transparency, accountability, privacy, bias mitigation, and the impact of AI on society. The questions provide a well-thought through process to prepare for handling AI ethics situations in the future. Students suggest that the capstone projects are well placed after the other courses in the specialization, but there is room for improvement earlier on for richer content.
Capstone projects are well placed after other courses in the specialization.
"The idea of capstone projects is good and is well placed after the other courses."
Reviews principles of AI ethics, including fairness, transparency, accountability, privacy, bias mitigation, and impact on society.
"AI ethics often involve considerations such as fairness, transparency, accountability, privacy, bias mitigation, and the impact of AI on society."
Provides hands-on practice with AI ethics.
"Not exactly a course per se but rather a couple of real-life situations to apply knowledge from the previous courses within the same syllabus."
"The use cases and the questions are good to apply AI ethics in action."
Support for answers in the capstone projects is minimal.
"The support for the answer is minimal and is not, at least quantitatively, up to my expectations from one full course."
Earlier modules in the specialization need improvement to provide richer content.
"I appreciate this module in the specialization even though there is a scope to improve earlier modules to make the content richer over time."
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 Artificial Intelligence Ethics in Action with these
activities:
Review of Statistics and Probability
Show steps
Strengthen your foundation in statistics and probability, which are essential for understanding AI ethics.
Browse courses on
Statistics
Show steps
-
Review basic concepts of statistics and probability.
-
Solve practice problems to reinforce your understanding.
Bias Analysis Exercises
Show steps
Practice identifying and mitigating biases in AI systems through drills and exercises.
Browse courses on
Bias Mitigation
Show steps
-
Review common types of biases in AI.
-
Analyze real-world examples of biased AI systems.
-
Develop strategies to mitigate biases in your own AI projects.
Discussion Groups: AI Ethics Case Studies
Show steps
Engage in discussions with peers to explore real-world case studies and ethical dilemmas related to AI.
Browse courses on
AI Ethics
Show steps
-
Prepare by reading the assigned case study.
-
Participate actively in the discussion.
-
Reflect on the ethical implications raised.
Six other activities
Expand to see all activities and additional details
Show all nine activities
Workshop: Responsible AI Development
Show steps
Attend a workshop that focuses on responsible AI development, gaining insights from experts and exploring best practices.
Browse courses on
AI Ethics
Show steps
-
Register for the workshop and prepare beforehand.
-
Participate actively in the workshop sessions.
-
Implement the learnings in your own AI projects.
Project: Designing a Fairer AI System
Show steps
Work on a project that will test your skills in designing and implementing an AI system that takes fairness and ethical considerations into account.
Browse courses on
AI Ethics
Show steps
-
Define the problem and objectives of your project.
-
Gather data and explore potential biases.
-
Design and implement your AI system.
-
Evaluate the performance and fairness of your system.
Tutorials on Advanced AI Ethics Techniques
Show steps
Expand your knowledge and skills in AI ethics by following guided tutorials on advanced topics.
Browse courses on
AI Ethics
Show steps
-
Identify areas where you want to enhance your knowledge.
-
Search for reputable tutorials and resources.
-
Follow the tutorials and complete the exercises.
AI Ethics Competition
Show steps
Participate in an AI ethics competition, showcasing your understanding of the field and applying your skills to solve real-world problems.
Browse courses on
AI Ethics
Show steps
-
Identify and research the competition.
-
Form a team and develop a project.
-
Submit your project and present it to the judges.
Blog Post: The Future of AI Ethics
Show steps
Write a blog post that explores your thoughts on the future of AI ethics and the challenges and opportunities ahead.
Browse courses on
AI Ethics
Show steps
-
Research current trends and developments in AI ethics.
-
Develop a clear and concise thesis statement.
-
Write a well-structured and engaging blog post.
Contribute to Open Source Projects on AI Ethics
Show steps
Make meaningful contributions to open source projects related to AI ethics, gaining hands-on experience and collaborating with experts.
Browse courses on
AI Ethics
Show steps
-
Identify open source projects that align with your interests.
-
Read the documentation and understand the project's goals.
-
Contribute code, documentation, or other resources.
Review of Statistics and Probability
Show steps
Strengthen your foundation in statistics and probability, which are essential for understanding AI ethics.
Browse courses on
Statistics
Show steps
Show steps
Show steps
- Review basic concepts of statistics and probability.
- Solve practice problems to reinforce your understanding.
Bias Analysis Exercises
Show steps
Practice identifying and mitigating biases in AI systems through drills and exercises.
Browse courses on
Bias Mitigation
Show steps
Show steps
Show steps
- Review common types of biases in AI.
- Analyze real-world examples of biased AI systems.
- Develop strategies to mitigate biases in your own AI projects.
Discussion Groups: AI Ethics Case Studies
Show steps
Engage in discussions with peers to explore real-world case studies and ethical dilemmas related to AI.
Browse courses on
AI Ethics
Show steps
Show steps
Show steps
- Prepare by reading the assigned case study.
- Participate actively in the discussion.
- Reflect on the ethical implications raised.
Six other activities
Expand to see all activities and additional details
Show all nine activities
Workshop: Responsible AI Development
Show steps
Attend a workshop that focuses on responsible AI development, gaining insights from experts and exploring best practices.
Browse courses on
AI Ethics
Show steps
Show steps
Show steps
- Register for the workshop and prepare beforehand.
- Participate actively in the workshop sessions.
- Implement the learnings in your own AI projects.
Project: Designing a Fairer AI System
Show steps
Work on a project that will test your skills in designing and implementing an AI system that takes fairness and ethical considerations into account.
Browse courses on
AI Ethics
Show steps
Show steps
Show steps
- Define the problem and objectives of your project.
- Gather data and explore potential biases.
- Design and implement your AI system.
- Evaluate the performance and fairness of your system.
Tutorials on Advanced AI Ethics Techniques
Show steps
Expand your knowledge and skills in AI ethics by following guided tutorials on advanced topics.
Browse courses on
AI Ethics
Show steps
Show steps
Show steps
- Identify areas where you want to enhance your knowledge.
- Search for reputable tutorials and resources.
- Follow the tutorials and complete the exercises.
AI Ethics Competition
Show steps
Participate in an AI ethics competition, showcasing your understanding of the field and applying your skills to solve real-world problems.
Browse courses on
AI Ethics
Show steps
Show steps
Show steps
- Identify and research the competition.
- Form a team and develop a project.
- Submit your project and present it to the judges.
Blog Post: The Future of AI Ethics
Show steps
Write a blog post that explores your thoughts on the future of AI ethics and the challenges and opportunities ahead.
Browse courses on
AI Ethics
Show steps
Show steps
Show steps
- Research current trends and developments in AI ethics.
- Develop a clear and concise thesis statement.
- Write a well-structured and engaging blog post.
Contribute to Open Source Projects on AI Ethics
Show steps
Make meaningful contributions to open source projects related to AI ethics, gaining hands-on experience and collaborating with experts.
Browse courses on
AI Ethics
Show steps
Show steps
Show steps
- Identify open source projects that align with your interests.
- Read the documentation and understand the project's goals.
- Contribute code, documentation, or other resources.
Career center
Learners who complete Artificial Intelligence Ethics in Action will develop knowledge and skills
that may be useful to these careers:
AI Policy Analyst
AI Policy Analyst
AI Policy Analysts develop and implement policies that govern the use of artificial intelligence. They work with governments and other stakeholders to ensure that AI is used in a responsible and ethical manner. The course, *Artificial Intelligence Ethics in Action*, would be very useful for those interested in working as an AI Policy Analyst because it provides a comprehensive overview of the ethical issues involved in using AI. Additionally, the course will help develop the critical thinking and problem-solving skills that are essential for AI Policy Analysts.
AI Ethics Researcher
AI Ethics Researcher
AI Ethics Researchers study the ethical implications of using artificial intelligence. They work with a variety of stakeholders to develop ethical guidelines and ensure that AI is used in a responsible manner. The course, *Artificial Intelligence Ethics in Action*, would be very useful for those interested in working as an AI Ethics Researcher because it provides a comprehensive overview of the ethical issues involved in using AI. Additionally, the course will help develop the critical thinking and problem-solving skills that are essential for AI Ethics Researchers.
AI Risk Manager
AI Risk Manager
AI Risk Managers identify and manage risks associated with using artificial intelligence. They work with organizations to develop and implement risk management strategies that protect against the potential harms of AI. The course, *Artificial Intelligence Ethics in Action*, would be very useful for those interested in working as an AI Risk Manager because it provides a comprehensive overview of the ethical issues involved in using AI. Additionally, the course will help develop the critical thinking and problem-solving skills that are essential for AI Risk Managers.
AI Governance Specialist
AI Governance Specialist
AI Governance Specialists develop and implement governance frameworks that ensure that AI is used in a responsible and ethical manner. They work with organizations to develop and implement policies, procedures, and practices that promote the responsible use of AI. The course, *Artificial Intelligence Ethics in Action*, would be very useful for those interested in working as an AI Governance Specialist because it provides a comprehensive overview of the ethical issues involved in using AI. Additionally, the course will help develop the critical thinking and problem-solving skills that are essential for AI Governance Specialists.
AI Auditor
AI Auditor
AI Auditors assess the ethical and responsible use of artificial intelligence. They work with organizations to identify and mitigate risks associated with using AI. The course, *Artificial Intelligence Ethics in Action*, would be very useful for those interested in working as an AI Auditor because it provides a comprehensive overview of the ethical issues involved in using AI. Additionally, the course will help develop the critical thinking and problem-solving skills that are essential for AI Auditors.
Risk Analyst
Risk Analyst
Risk Analysts help organizations identify and manage risks. They use data and analysis to assess the likelihood and impact of potential risks. The course, *Artificial Intelligence Ethics in Action*, may be useful for those interested in working as a Risk Analyst because it will teach them how to analyze data and identify ethical issues when using AI. Additionally, the course will help develop problem-solving and critical thinking skills that are essential for Risk Analysts.
Product Manager
Product Manager
Product Managers are responsible for developing and managing products. They work with engineers, designers, and marketers to ensure that products meet the needs of customers. The course, *Artificial Intelligence Ethics in Action*, may be useful for those interested in working as a Product Manager because it addresses the ethical issues involved in product development. Additionally, the course will help develop problem-solving and critical thinking skills that are essential for Product Managers.
Data Scientist
Data Scientist
Data Scientists are responsible for collecting, cleaning, and analyzing large amounts of data. They use this data to build models and provide insights that can be used to improve decision-making. The course, *Artificial Intelligence Ethics in Action*, may be useful for those interested in working as a Data Scientist because it explores the ethical implications of using data and AI. Additionally, the course is mostly quantitative and will help build a foundation for data science.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to analyze data and make predictions. They work in a variety of industries, including finance, consulting, and healthcare. The course, *Artificial Intelligence Ethics in Action*, may be useful for those interested in working as a Quantitative Analyst because it will teach them how to analyze data and identify ethical issues when using AI. Additionally, the course is mostly quantitative and will help develop mathematical and statistical skills.
Data Engineer
Data Engineer
Data Engineers design and maintain data pipelines that collect, clean, and store data. They work with a variety of programming languages and technologies to create pipelines that are efficient and reliable. The course, *Artificial Intelligence Ethics in Action*, may be useful for those interested in working as a Data Engineer because it will teach them how to analyze data and identify ethical issues when using AI. Additionally, the course will help develop the programming and problem-solving skills that are essential for Data Engineers.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers design, build, and maintain machine learning models. They work with a variety of programming languages and technologies to create models that can be used to solve problems and make decisions. The course, *Artificial Intelligence Ethics in Action*, may be useful for those interested in working as a Machine Learning Engineer because it addresses the ethical issues involved in developing and using machine learning models. Additionally, the course will help develop the programming and problem-solving skills that are essential for Machine Learning Engineers.
Statistician
Statistician
Statisticians use data to solve problems and make decisions. They work in a variety of industries, including healthcare, finance, and education. The course, *Artificial Intelligence Ethics in Action*, may be useful for those interested in working as a Statistician because it will teach them how to analyze data and identify ethical issues when using AI. Additionally, the course is mostly quantitative and will help build a foundation for statistics.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software applications. They work with a variety of programming languages and technologies to create software that meets the needs of users. The course, *Artificial Intelligence Ethics in Action*, may be useful for those interested in working as a Software Engineer because it addresses the ethical issues involved in software development. Additionally, the course will help develop problem-solving and critical thinking skills that are essential for Software Engineers.
Data Analyst
Data Analyst
A Data Analyst plays a key role in almost every industry as they can use data to gain insight and make better decisions. As part of their role, they must be able to identify patterns, find trends, and predict future outcomes. The course, *Artificial Intelligence Ethics in Action*, may be useful for those interested in working as a Data Analyst because it will teach them how to analyze data and identify ethical issues when using AI. Additionally, the course is mostly quantitative and will help develop data analysis skills.
For more career information including salaries, visit:
OpenCourser.com/course/vofv3r/artificial
Reading list
We've selected 13 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
Artificial Intelligence Ethics in Action.
Provides a comprehensive overview of the ethical issues surrounding artificial intelligence, including topics such as fairness, bias, and privacy. It valuable resource for students and researchers in the field of AI ethics.
Provides a clear and concise introduction to the field of artificial intelligence. It covers a wide range of topics, from the history of AI to the latest advances in machine learning.
Save
Explores the ethical issues that arise in the design and use of computational systems. It provides a framework for thinking about the moral implications of AI and offers practical guidance for developers and policymakers.
Examines the problem of aligning the goals of AI systems with human values. It argues that this is one of the most important challenges facing humanity and offers a number of possible solutions.
Save
Provides a comprehensive overview of the safety and security risks associated with AI. It covers topics such as adversarial attacks, data poisoning, and the potential for AI to be used for malicious purposes.
Save
Explores the possible futures of humanity in the age of AI. It discusses topics such as the singularity, the ethics of human enhancement, and the potential for AI to create a new kind of society.
Save
Explores the potential risks and benefits of superintelligence. It argues that superintelligence is one of the most important challenges facing humanity and offers a number of possible strategies for dealing with it.
Save
Examines the global race for AI supremacy. It provides a detailed look at the AI strategies of China and the United States and offers insights into the potential implications of AI for the future of the world.
Explores the history and future of machine learning. It provides a clear and concise explanation of the underlying principles of machine learning and offers insights into the potential applications of machine learning in various fields.
Save
Explores the implications of AI for humanity's future. It argues that AI will have a profound impact on our lives and offers insights into how we can prepare for this future.
Save
Explores the impact of AI on human society. It provides a clear and concise explanation of the underlying principles of AI and offers insights into the potential benefits and risks of AI.
Provides a comprehensive overview of the ethical issues surrounding AI. It covers a wide range of topics, from the history of AI ethics to the latest developments in the field.
Provides a comprehensive overview of the ethical issues surrounding AI. It covers a wide range of topics, from the history of AI ethics to the latest developments in the field.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/vofv3r/artificial
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Level
Intermediate
Via
Coursera
Institution
LearnQuest
Instructor
Brent Summers
Language
English
Transcripts
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This course belongs to a
collection
called
Ethics in the Age of AI. It's comprised of four courses:
- Artificial Intelligence Algorithms Models and Limitations
- Artificial Intelligence Data Fairness and Bias
- Artificial Intelligence Privacy and Convenience
- Artificial Intelligence Ethics in Action (viewing)
Good to know
Develops skills in critical thinking and analytical ability, which are core skills for ethics
Explores scenarios across a variety of topics and situations, which helps learners think more broadly about ethics
Projects are designed to demonstrate ability to analyze ethical AI
Covers bias in predictive text models, fairness issues with sensitive predictions, and ethical issues in model theory
Instructor Brent Summers are not recognized experts on ethics
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