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Google Cloud Training
As the use of enterprise Artificial Intelligence and Machine Learning continues to grow, so too does the importance of building it responsibly. A challenge for many is that talking about responsible AI can be easier than putting it into practice. If you’re interested in learning how to operationalize responsible AI in your organization, this course is for you.
Read more
As the use of enterprise Artificial Intelligence and Machine Learning continues to grow, so too does the importance of building it responsibly. A challenge for many is that talking about responsible AI can be easier than putting it into practice. If you’re interested in learning how to operationalize responsible AI in your organization, this course is for you.
Read more
As the use of enterprise Artificial Intelligence and Machine Learning continues to grow, so too does the importance of building it responsibly. A challenge for many is that talking about responsible AI can be easier than putting it into practice. If you’re interested in learning how to operationalize responsible AI in your organization, this course is for you.
In this course, you will learn how Google Cloud does this today, together with best practices and lessons learned, to serve as a framework for you to build your own responsible AI approach.
Register for this course and see more details by visiting:
OpenCourser.com/course/iizj1i/responsible
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What's inside
Syllabus
Introduction
In this module, you will learn about the impact of AI technology and Google's approach to responsible AI, and also be introduced to Google's AI Principles.
Read more
Syllabus
Introduction
In this module, you will learn about the impact of AI technology and Google's approach to responsible AI, and also be introduced to Google's AI Principles.
Read more
The Business Case for Responsible AI
In this module, you will learn about how to make a business case for responsible AI, based on the report 'The Business Case for Ethics by Design' by the Economist Intelligence Unit.
AI’s Technical Considerations and Ethical Concerns
In this module, you will learn about ethical dilemmas and how emerging technology such as generative AI can surface ethical concerns that need to be addressed.
Creating AI Principles.
In this module, you will learn about how Google’s AI Principles were developed and explore the ethical aims of each of these Principles.
Operationalizing AI Principles: Setting Up and Running Reviews
In this module, you will learn about the practical application of responsible AI and how to operationalize AI principles by setting up and running reviews.
Operationalizing AI Principles: Issue Spotting and Lessons Learned
In this module, you will learn about the process of identifying possible ethical issues and identify issue spotting questions to think critically about the potential benefits and harms of a use case.
Continuing the Journey Towards Responsible AI
In this module, you will learn about the next steps and resources you can use to continue your responsible AI journey.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Examines ethical dilemmas and how emerging technology can surface ethical concerns that need to be addressed
Develops skills for operationalizing AI principles, which are highly relevant to industry
Taught by Google Cloud Training, who are recognized for their work in the topic that the course teaches
Explores how Google Cloud does this today, together with best practices and lessons learned, which may be valuable for students
Explicitly requires that students come in with extensive background knowledge first
Save this course
Save Responsible AI: Applying AI Principles with Google Cloud to your list so you can find it easily later:
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Save
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 Responsible AI: Applying AI Principles with Google Cloud with these
activities:
Read the foundational book on business ethics
Show steps
The course will address the Business Case for Responsible AI so it is helpful to be familiar with the ethical subject beforehand.
View
Which MBA?: A Critical Guide to the World's...
on Amazon
Show steps
-
Purchase and read the Economist Intelligence Unit book
-
Take notes on the main ideas
Review basic machine learning concepts, such as supervised and unsupervised learning
Show steps
Strengthens your understanding of the fundamentals of machine learning, which are essential for this course
Browse courses on
Machine Learning Fundamentals
Show steps
-
Review your notes
-
Watch online tutorials
-
Solve practice problems
Review: The Business Case for Ethics by Design
Show steps
Provides a solid foundation for understanding the business case for responsible AI.
View
Which MBA?: A Critical Guide to the World's...
on Amazon
Show steps
-
Read the book and summarize the key arguments.
-
Identify the benefits of implementing responsible AI practices.
-
Consider how the concepts in the book apply to your organization.
14 other activities
Expand to see all activities and additional details
Show all 17 activities
Review 'The Alignment Problem: Machine Learning and Human Values'
Show steps
Prepares you to understand the ethical concerns around AI
View
The Alignment Problem: Machine Learning and...
on Amazon
Show steps
-
Read chapters 1-3 to build a strong foundation in the key concepts
-
Take notes on the ethical concerns raised in these chapters
Follow tutorials on Google's AI Principles
Show steps
Helps you understand and apply Google's AI Principles to your own work.
Browse courses on
AI Principles
Show steps
-
Find tutorials on Google's AI Principles.
-
Go through the tutorials and take notes.
-
Apply the principles to a project or situation.
Compile your course notes and materials
Show steps
Helps you organize and review the course material, and it also allows you to create a valuable resource for future reference.
Show steps
-
Gather your notes, assignments, and other course materials.
-
Organize the materials into a coherent structure.
-
Review the materials regularly.
Review the following topics from your previous coursework:
Show steps
Help refresh skills that this course will heavily rely upon
Browse courses on
Data Science
Show steps
-
Review your Python coding skills.
-
Review the latest trends and best practices for data science.
Participate in a peer learning group to discuss AI principles and best practices
Show steps
Allows you to exchange ideas and learn from others' perspectives, deepening your understanding of the course material
Browse courses on
Collaboration
Show steps
-
Find a group of peers who are also taking this course
-
Meet regularly to discuss the course material
-
Share your insights and learn from others' perspectives
Complete exercises on AI principles and ethical considerations
Show steps
Provides opportunities to apply your knowledge and develop strong problem-solving skills
Browse courses on
AI Principles
Show steps
-
Find practice exercises and quizzes online
-
Complete the exercises regularly
Solve case studies on ethical concerns
Show steps
Helps you apply the concepts of responsible AI to real-world scenarios and develop your problem-solving skills.
Browse courses on
Ethical AI
Show steps
-
Review the case study and identify the key ethical concerns.
-
Analyze the potential risks and benefits of the AI system in the case study.
-
Propose recommendations for how to mitigate the ethical concerns.
Discuss AI ethics with peers
Show steps
Provides an opportunity to exchange ideas, learn from others, and develop your critical thinking skills.
Browse courses on
AI Ethics
Show steps
-
Find a peer group or online forum.
-
Discuss ethical issues related to AI.
-
Share your perspectives and learn from others.
Follow tutorials on the latest AI tools and techniques
Show steps
Keeps you up-to-date on the latest advancements in AI and enhances your practical skills
Browse courses on
AI Tools
Show steps
-
Identify tutorials that align with your learning goals
-
Follow the tutorials step-by-step
-
Practice using the tools and techniques covered in the tutorials
Create a written report on the ethical implications of using AI in healthcare
Show steps
Helps you apply your knowledge to a real-world scenario and develop your critical thinking skills
Show steps
-
Research and identify the ethical concerns associated with AI in healthcare
-
Analyze the potential benefits and risks of using AI in healthcare
-
Develop recommendations for how to mitigate the ethical risks of using AI in healthcare
Create a presentation on AI ethics for your team
Show steps
Helps you develop your communication and presentation skills, and it also allows you to share your knowledge with others.
Show steps
-
Gather information on AI ethics.
-
Develop a presentation outline.
-
Create slides and visuals.
-
Practice your presentation.
-
Deliver the presentation.
Contribute to open-source projects related to responsible AI
Show steps
Involves you in the real-world application of responsible AI and expands your professional network
Browse courses on
Open Source
Show steps
-
Find open-source projects that align with your interests
-
Contribute to the project by reporting bugs, writing documentation, or contributing code
Develop a responsible AI framework for your organization
Show steps
Provides practical experience in operationalizing responsible AI principles.
Show steps
-
Identify the stakeholders and their concerns.
-
Establish a set of ethical principles and guidelines.
-
Develop a process for reviewing and approving AI projects.
-
Implement a monitoring and evaluation system.
-
Communicate the framework to stakeholders and educate them on its importance.
Contribute to open-source projects related to responsible AI
Show steps
Provides hands-on experience with responsible AI development and allows you to contribute to the community.
Browse courses on
Responsible AI
Show steps
-
Find open-source projects related to responsible AI.
-
Identify areas where you can contribute.
-
Submit a pull request.
Read the foundational book on business ethics
Show steps
The course will address the Business Case for Responsible AI so it is helpful to be familiar with the ethical subject beforehand.
View
Which MBA?: A Critical Guide to the World's...
on Amazon
Show steps
Show steps
Show steps
- Purchase and read the Economist Intelligence Unit book
- Take notes on the main ideas
Review basic machine learning concepts, such as supervised and unsupervised learning
Show steps
Strengthens your understanding of the fundamentals of machine learning, which are essential for this course
Browse courses on
Machine Learning Fundamentals
Show steps
Show steps
Show steps
- Review your notes
- Watch online tutorials
- Solve practice problems
Review: The Business Case for Ethics by Design
Show steps
Provides a solid foundation for understanding the business case for responsible AI.
View
Which MBA?: A Critical Guide to the World's...
on Amazon
Show steps
Show steps
Show steps
- Read the book and summarize the key arguments.
- Identify the benefits of implementing responsible AI practices.
- Consider how the concepts in the book apply to your organization.
14 other activities
Expand to see all activities and additional details
Show all 17 activities
Review 'The Alignment Problem: Machine Learning and Human Values'
Show steps
Prepares you to understand the ethical concerns around AI
View
The Alignment Problem: Machine Learning and...
on Amazon
Show steps
Show steps
Show steps
- Read chapters 1-3 to build a strong foundation in the key concepts
- Take notes on the ethical concerns raised in these chapters
Follow tutorials on Google's AI Principles
Show steps
Helps you understand and apply Google's AI Principles to your own work.
Browse courses on
AI Principles
Show steps
Show steps
Show steps
- Find tutorials on Google's AI Principles.
- Go through the tutorials and take notes.
- Apply the principles to a project or situation.
Compile your course notes and materials
Show steps
Helps you organize and review the course material, and it also allows you to create a valuable resource for future reference.
Show steps
Show steps
Show steps
- Gather your notes, assignments, and other course materials.
- Organize the materials into a coherent structure.
- Review the materials regularly.
Review the following topics from your previous coursework:
Show steps
Help refresh skills that this course will heavily rely upon
Browse courses on
Data Science
Show steps
Show steps
Show steps
- Review your Python coding skills.
- Review the latest trends and best practices for data science.
Participate in a peer learning group to discuss AI principles and best practices
Show steps
Allows you to exchange ideas and learn from others' perspectives, deepening your understanding of the course material
Browse courses on
Collaboration
Show steps
Show steps
Show steps
- Find a group of peers who are also taking this course
- Meet regularly to discuss the course material
- Share your insights and learn from others' perspectives
Complete exercises on AI principles and ethical considerations
Show steps
Provides opportunities to apply your knowledge and develop strong problem-solving skills
Browse courses on
AI Principles
Show steps
Show steps
Show steps
- Find practice exercises and quizzes online
- Complete the exercises regularly
Solve case studies on ethical concerns
Show steps
Helps you apply the concepts of responsible AI to real-world scenarios and develop your problem-solving skills.
Browse courses on
Ethical AI
Show steps
Show steps
Show steps
- Review the case study and identify the key ethical concerns.
- Analyze the potential risks and benefits of the AI system in the case study.
- Propose recommendations for how to mitigate the ethical concerns.
Discuss AI ethics with peers
Show steps
Provides an opportunity to exchange ideas, learn from others, and develop your critical thinking skills.
Browse courses on
AI Ethics
Show steps
Show steps
Show steps
- Find a peer group or online forum.
- Discuss ethical issues related to AI.
- Share your perspectives and learn from others.
Follow tutorials on the latest AI tools and techniques
Show steps
Keeps you up-to-date on the latest advancements in AI and enhances your practical skills
Browse courses on
AI Tools
Show steps
Show steps
Show steps
- Identify tutorials that align with your learning goals
- Follow the tutorials step-by-step
- Practice using the tools and techniques covered in the tutorials
Create a written report on the ethical implications of using AI in healthcare
Show steps
Helps you apply your knowledge to a real-world scenario and develop your critical thinking skills
Show steps
Show steps
Show steps
- Research and identify the ethical concerns associated with AI in healthcare
- Analyze the potential benefits and risks of using AI in healthcare
- Develop recommendations for how to mitigate the ethical risks of using AI in healthcare
Create a presentation on AI ethics for your team
Show steps
Helps you develop your communication and presentation skills, and it also allows you to share your knowledge with others.
Show steps
Show steps
Show steps
- Gather information on AI ethics.
- Develop a presentation outline.
- Create slides and visuals.
- Practice your presentation.
- Deliver the presentation.
Contribute to open-source projects related to responsible AI
Show steps
Involves you in the real-world application of responsible AI and expands your professional network
Browse courses on
Open Source
Show steps
Show steps
Show steps
- Find open-source projects that align with your interests
- Contribute to the project by reporting bugs, writing documentation, or contributing code
Develop a responsible AI framework for your organization
Show steps
Provides practical experience in operationalizing responsible AI principles.
Show steps
Show steps
Show steps
- Identify the stakeholders and their concerns.
- Establish a set of ethical principles and guidelines.
- Develop a process for reviewing and approving AI projects.
- Implement a monitoring and evaluation system.
- Communicate the framework to stakeholders and educate them on its importance.
Contribute to open-source projects related to responsible AI
Show steps
Provides hands-on experience with responsible AI development and allows you to contribute to the community.
Browse courses on
Responsible AI
Show steps
Show steps
Show steps
- Find open-source projects related to responsible AI.
- Identify areas where you can contribute.
- Submit a pull request.
Career center
Learners who complete Responsible AI: Applying AI Principles with Google Cloud will develop knowledge and skills
that may be useful to these careers:
AI Ethicist
AI Ethicist
AI Ethicists ensure that AI systems are developed and used in a responsible and ethical manner. They work with engineers, product managers, and other stakeholders to identify and mitigate ethical risks. This course provides AI Ethicists with the tools and knowledge they need to be effective in their role.
AI Policy Advisor
AI Policy Advisor
AI Policy Advisors develop and implement policies that govern the use of AI. They work with governments, businesses, and other organizations to ensure that AI is used in a responsible and ethical manner. This course provides AI Policy Advisors with the knowledge and skills they need to be effective in their role.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers build, deploy, and maintain machine learning models. They may also work with Data Scientists to develop new algorithms. This course teaches Machine Learning Engineers how to identify and mitigate the ethical risks associated with AI, and develop more responsible AI solutions.
Product Manager
Product Manager
Product Managers define the vision and roadmap for new AI products and features. They work with engineers, designers, and other stakeholders to bring these products to life. This course can help Product Managers understand the ethical considerations involved in AI development, and develop more responsible AI products.
UX Designer
UX Designer
UX Designers design the user experience for AI products and features. They work with engineers, product managers, and other stakeholders to create AI systems that are easy to use and understand. This course can help UX Designers understand the ethical considerations involved in AI development, and design more responsible AI experiences.
Software Engineer
Software Engineer
Software Engineers build and maintain the software that powers AI systems. They work with engineers, product managers, and other stakeholders to bring these systems to life. This course can help Software Engineers understand the ethical considerations involved in AI development, and develop more responsible AI systems.
Data Analyst
Data Analyst
Data Analysts collect, clean, and analyze data to identify trends and patterns. They work with engineers, product managers, and other stakeholders to use data to make better decisions. This course can help Data Analysts understand the ethical considerations involved in AI development, and use data more responsibly to develop AI systems.
Data Scientist
Data Scientist
Data Scientists research and develop new algorithms and techniques for extracting actionable insights from large datasets. This course may be useful for Data Scientists who want to gain a deeper understanding of the ethical considerations involved in AI development, as well as how to operationalize responsible AI principles within their organization.
Business Analyst
Business Analyst
Business Analysts help organizations understand and improve their business processes. They work with stakeholders across the organization to gather requirements, analyze data, and identify opportunities for improvement. This course can help Business Analysts understand the ethical considerations involved in AI development, and develop more responsible AI solutions.
Project Manager
Project Manager
Project Managers lead and manage projects to deliver new AI products and features. They work with engineers, product managers, and other stakeholders to ensure that projects are completed on time, within budget, and to the required quality. This course can help Project Managers understand the ethical considerations involved in AI development, and manage AI projects more responsibly.
Technical Writer
Technical Writer
Technical Writers create documentation for AI systems and products. They work with engineers, product managers, and other stakeholders to create clear and concise documentation that helps users understand how to use and maintain AI systems. This course can help Technical Writers understand the ethical considerations involved in AI development, and write more responsible AI documentation.
Marketer
Marketer
Marketers promote and sell AI products and services. They work with engineers, product managers, and other stakeholders to create marketing campaigns that reach and engage target audiences. This course can help Marketers understand the ethical considerations involved in AI development, and market AI products and services more responsibly.
Salesperson
Salesperson
Salespeople sell AI products and services to customers. They work with engineers, product managers, and other stakeholders to identify and qualify leads, and close deals. This course can help Salespeople understand the ethical considerations involved in AI development, and sell AI products and services more responsibly.
Customer Success Manager
Customer Success Manager
Customer Success Managers help customers adopt and use AI products and services. They work with engineers, product managers, and other stakeholders to ensure that customers are successful with their AI investments. This course can help Customer Success Managers understand the ethical considerations involved in AI development, and help customers use AI products and services more responsibly.
Support Engineer
Support Engineer
Support Engineers provide technical support to customers who are using AI products and services. They work with engineers, product managers, and other stakeholders to resolve customer issues and ensure that customers are satisfied with their AI investments. This course can help Support Engineers understand the ethical considerations involved in AI development, and provide more responsible AI support to customers.
For more career information including salaries, visit:
OpenCourser.com/course/iizj1i/responsible
Reading list
We've selected 15 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
Responsible AI: Applying AI Principles with Google Cloud.
Explores the challenges of aligning the goals of AI systems with human values. It must-read for anyone interested in the future of AI and its potential impact on society.
A critical examination of the use of AI in decision-making, highlighting the potential for bias and discrimination. Raises awareness of the societal risks of irresponsible AI and the need for transparency and accountability.
A practical guide to building machine learning models using popular libraries such as Scikit-Learn, Keras, and TensorFlow. Provides hands-on experience in implementing responsible AI practices, such as model evaluation and bias mitigation.
A hands-on guide to deep learning, using the fastai library and PyTorch framework. Provides practical experience in building and deploying AI models, reinforcing the technical concepts covered in the course.
An economic perspective on AI, examining the impact of AI on labor markets, productivity, and innovation. Provides insights into the economic benefits and challenges of responsible AI adoption.
Save
A business-oriented perspective on AI, exploring the opportunities and challenges of implementing AI in various industries. Provides insights into the strategic advantages of responsible AI and how to avoid potential pitfalls.
Save
Comprehensive introduction to the field of deep learning. It covers the basics of deep learning algorithms, as well as how to apply them to real-world problems. It valuable resource for anyone who wants to learn more about deep learning.
Comprehensive introduction to the field of reinforcement learning. It covers the basics of reinforcement learning algorithms, as well as how to apply them to real-world problems. It valuable resource for anyone who wants to learn more about reinforcement learning.
Provides a practical introduction to natural language processing. It covers the basics of natural language processing algorithms, as well as how to apply them to real-world problems. It valuable resource for anyone who wants to learn more about natural language processing.
Save
Provides a comprehensive overview of the field of computer vision. It covers the basics of computer vision algorithms, as well as how to apply them to real-world problems. It valuable resource for anyone who wants to learn more about computer vision.
Provides a comprehensive overview of the field of speech and language processing. It covers the basics of speech and language processing algorithms, as well as how to apply them to real-world problems. It valuable resource for anyone who wants to learn more about speech and language processing.
Provides a comprehensive overview of the field of probabilistic graphical models. It covers the basics of probabilistic graphical models, as well as how to apply them to real-world problems. It valuable resource for anyone who wants to learn more about probabilistic graphical models.
Provides a comprehensive overview of the field of Bayesian reasoning and machine learning. It covers the basics of Bayesian reasoning and machine learning algorithms, as well as how to apply them to real-world problems. It valuable resource for anyone who wants to learn more about Bayesian reasoning and machine learning.
Provides a comprehensive overview of the field of information theory, inference, and learning algorithms. It covers the basics of information theory, inference, and learning algorithms, as well as how to apply them to real-world problems. It valuable resource for anyone who wants to learn more about information theory, inference, and learning algorithms.
Provides a comprehensive overview of the field of machine learning from a probabilistic perspective. It covers the basics of machine learning algorithms, as well as how to apply them to real-world problems. It valuable resource for anyone who wants to learn more about machine learning from a probabilistic perspective.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/iizj1i/responsible
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Good to know
Examines ethical dilemmas and how emerging technology can surface ethical concerns that need to be addressed
Develops skills for operationalizing AI principles, which are highly relevant to industry
Taught by Google Cloud Training, who are recognized for their work in the topic that the course teaches
Explores how Google Cloud does this today, together with best practices and lessons learned, which may be valuable for students
Explicitly requires that students come in with extensive background knowledge first
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