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Ben Weissman
More and more organizations are implementing artificial intelligence (AI) within their processes. In this course, you'll learn the importance of responsible use of AI by taking ethics and bias into account.
More and more organizations are implementing artificial intelligence (AI) within their processes for hiring, automation, autonomous and predictive devices, and many other use cases.
In this course, Artificial Intelligence Essentials: Responsible AI, you'll discover the meaning and impact of a responsible way to implement AI.
Read more
More and more organizations are implementing artificial intelligence (AI) within their processes. In this course, you'll learn the importance of responsible use of AI by taking ethics and bias into account.
More and more organizations are implementing artificial intelligence (AI) within their processes for hiring, automation, autonomous and predictive devices, and many other use cases.
In this course, Artificial Intelligence Essentials: Responsible AI, you'll discover the meaning and impact of a responsible way to implement AI.
Read more
More and more organizations are implementing artificial intelligence (AI) within their processes. In this course, you'll learn the importance of responsible use of AI by taking ethics and bias into account.
More and more organizations are implementing artificial intelligence (AI) within their processes for hiring, automation, autonomous and predictive devices, and many other use cases.
In this course, Artificial Intelligence Essentials: Responsible AI, you'll discover the meaning and impact of a responsible way to implement AI.
First, you'll build an understanding of what we mean when we talk about responsibility in terms of AI.
Next, you'll see how bias comes into play and how we face it in a conscious or unconscious way every single day.
Finally, you'll get into the importance of ethics in AI by looking at unethical means in AI implementations and principles to avoid them.
When you’re finished with this course, you’ll have the skills and knowledge needed to understand what ethics and bias in AI are, and how to make sure you’re using AI in a responsible way that is benefitting users without putting others or society at a disadvantage.
Register for this course and see more details by visiting:
OpenCourser.com/course/dva646/introduction
What's inside
Syllabus
Course Overview
Responsible and Ethical Artificial Intelligence (AI)
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Develops foundational skills and knowledge about responsible use of AI, which is essential for anyone working in AI-related fields
Taught by Ben Weissman, an expert in the field of AI ethics and governance
Examines ethical considerations for using AI, which are important for addressing potential negative effects and biases
Covers responsible AI implementation, which is highly relevant to organizations using AI across industries
Provides a starting point for exploring ethical considerations in AI, though it may require supplemental learning for in-depth knowledge
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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 Introduction to Amazon Cognito with these
activities:
Review AI Fundamentals
Show steps
Reinforce your understanding of core AI concepts to enhance comprehension of ethical issues.
Show steps
-
Review introductory AI and machine learning materials.
-
Attend a refresher course or workshop.
Review: The Ethical Algorithm
Show steps
Gain a deeper understanding of the ethical principles and challenges in AI algorithm design.
View
The Ethical Algorithm: The Science of Socially...
on Amazon
Show steps
-
Read and summarize key chapters.
-
Identify and analyze case studies of ethical algorithm design.
Responsible AI Frameworks and Best Practices
Show steps
Explore established frameworks and guidelines for implementing responsible AI.
Browse courses on
AI Ethics
Show steps
-
Review industry standards for ethical AI.
-
Identify best practices for responsible AI development.
-
Apply frameworks to real-world AI scenarios.
Six other activities
Expand to see all activities and additional details
Show all nine activities
Case Study Discussions
Show steps
Engage with peers to analyze real-world examples of responsible AI implementation.
Show steps
-
Identify case studies of responsible AI.
-
Analyze the ethical considerations and outcomes.
-
Discuss best practices and lessons learned.
Bias Exercises
Show steps
Practice recognizing and reducing bias in AI algorithms.
Show steps
-
Identify sources of data bias.
-
Analyze algorithms for potential bias.
-
Develop techniques to mitigate bias.
AI Ethics and Regulatory Compliance Workshop
Show steps
Attend workshops to gain practical insights on ethical AI implementation and regulatory compliance.
Show steps
-
Identify relevant workshops or conferences.
-
Attend sessions on AI ethics and regulations.
-
Engage with speakers and network with experts.
Ethical AI Impact Assessment
Show steps
Evaluate the ethical implications of implementing an AI solution.
Show steps
-
Identify stakeholders and their ethical concerns.
-
Analyze potential risks and benefits of the AI solution.
-
Develop strategies to mitigate ethical risks.
-
Create a report outlining the ethical impact assessment.
Contribute to Open Source Ethical AI Projects
Show steps
Collaborate on open-source initiatives to advance responsible AI practices.
Show steps
-
Identify open-source projects focused on ethical AI.
-
Contribute to codebase, documentation, or community discussions.
-
Showcase your contributions in a portfolio or resume.
Develop a Responsible AI Policy for an Organization
Show steps
Apply ethical principles to create a comprehensive policy for AI implementation within an organization.
Show steps
-
Research industry best practices and regulatory guidelines.
-
Conduct stakeholder interviews to identify ethical concerns.
-
Draft and refine an AI policy document.
Review AI Fundamentals
Show steps
Reinforce your understanding of core AI concepts to enhance comprehension of ethical issues.
Show steps
Show steps
Show steps
- Review introductory AI and machine learning materials.
- Attend a refresher course or workshop.
Review: The Ethical Algorithm
Show steps
Gain a deeper understanding of the ethical principles and challenges in AI algorithm design.
View
The Ethical Algorithm: The Science of Socially...
on Amazon
Show steps
Show steps
Show steps
- Read and summarize key chapters.
- Identify and analyze case studies of ethical algorithm design.
Responsible AI Frameworks and Best Practices
Show steps
Explore established frameworks and guidelines for implementing responsible AI.
Browse courses on
AI Ethics
Show steps
Show steps
Show steps
- Review industry standards for ethical AI.
- Identify best practices for responsible AI development.
- Apply frameworks to real-world AI scenarios.
Six other activities
Expand to see all activities and additional details
Show all nine activities
Case Study Discussions
Show steps
Engage with peers to analyze real-world examples of responsible AI implementation.
Show steps
Show steps
Show steps
- Identify case studies of responsible AI.
- Analyze the ethical considerations and outcomes.
- Discuss best practices and lessons learned.
Bias Exercises
Show steps
Practice recognizing and reducing bias in AI algorithms.
Show steps
Show steps
Show steps
- Identify sources of data bias.
- Analyze algorithms for potential bias.
- Develop techniques to mitigate bias.
AI Ethics and Regulatory Compliance Workshop
Show steps
Attend workshops to gain practical insights on ethical AI implementation and regulatory compliance.
Show steps
Show steps
Show steps
- Identify relevant workshops or conferences.
- Attend sessions on AI ethics and regulations.
- Engage with speakers and network with experts.
Ethical AI Impact Assessment
Show steps
Evaluate the ethical implications of implementing an AI solution.
Show steps
Show steps
Show steps
- Identify stakeholders and their ethical concerns.
- Analyze potential risks and benefits of the AI solution.
- Develop strategies to mitigate ethical risks.
- Create a report outlining the ethical impact assessment.
Contribute to Open Source Ethical AI Projects
Show steps
Collaborate on open-source initiatives to advance responsible AI practices.
Show steps
Show steps
Show steps
- Identify open-source projects focused on ethical AI.
- Contribute to codebase, documentation, or community discussions.
- Showcase your contributions in a portfolio or resume.
Develop a Responsible AI Policy for an Organization
Show steps
Apply ethical principles to create a comprehensive policy for AI implementation within an organization.
Show steps
Show steps
Show steps
- Research industry best practices and regulatory guidelines.
- Conduct stakeholder interviews to identify ethical concerns.
- Draft and refine an AI policy document.
Career center
Learners who complete Introduction to Amazon Cognito will develop knowledge and skills
that may be useful to these careers:
Artificial Intelligence Specialist
Artificial Intelligence Specialist
Artificial Intelligence Specialists design, develop, and implement AI systems. Introduction to Amazon Cognito may help Artificial Intelligence Specialists gain a strong foundation in AI ethics and bias, which are important considerations for the field.
AI Ethicist
AI Ethicist
AI Ethicists ensure that AI systems are developed and used in an ethical and responsible manner. Introduction to Amazon Cognito may provide AI Ethicists with a foundation in AI ethics.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers work with Artificial Intelligence (AI) and related technologies to create intelligent and useful software programs. As an AI-focused course, Introduction to Amazon Cognito may help Machine Learning Engineers learn about responsible AI usage. The course could also be useful for engineers seeking to build a foundation in ethical AI for machine learning.
Algorithm Developer
Algorithm Developer
Algorithm Developers design and develop algorithms for use in computer programs. Introduction to Amazon Cognito may be helpful for Algorithm Developers seeking to create ethical and responsible AI algorithms.
Data Scientist
Data Scientist
Data Scientists help turn raw data into usable information. This role involves building models and analyzing data in order to provide insights. Introduction to Amazon Cognito may be useful to Data Scientists seeking to create and implement ethical AI solutions.
Data Analyst
Data Analyst
Data Analysts clean, analyze, and interpret data to help businesses make better decisions. Introduction to Amazon Cognito may be useful for Data Analysts seeking to implement ethical AI into their data analysis.
Software Engineer
Software Engineer
Software Engineers design, develop, maintain, and manage computer software systems. As an AI-focused course, Introduction to Amazon Cognito can help Software Engineers by providing a foundation for building reliable, responsible AI software.
Business Analyst
Business Analyst
Business Analysts work with stakeholders and analyze data to improve business processes. Introduction to Amazon Cognito may be useful for Business Analysts seeking to create ethical AI solutions that meet the needs of stakeholders.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to analyze data and provide insights for businesses. Introduction to Amazon Cognito may be useful for Quantitative Analysts who want to develop ethical AI-powered models.
Product Manager
Product Manager
Product Managers are responsible for planning and developing new products or features. Introduction to Amazon Cognito may be helpful for Product Managers hoping to incorporate ethical AI into their products.
Data Engineer
Data Engineer
Data Engineers design, build, and manage data pipelines and systems. Introduction to Amazon Cognito may be useful for Data Engineers seeking to incorporate ethical AI into their data engineering
Project Manager
Project Manager
Project Managers plan, execute, and oversee projects. Introduction to Amazon Cognito may be useful for Project Managers who are working with AI-powered projects and who want to ensure they are done responsibly.
For more career information including salaries, visit:
OpenCourser.com/course/dva646/introduction
Reading list
We've selected 12 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
Introduction to Amazon Cognito.
Provides an overview of the ethical issues surrounding AI, including privacy, bias, and accountability. It good starting point for anyone interested in learning more about the ethical implications of AI.
Save
Provides a comprehensive overview of deep learning, including its algorithms, techniques, and applications. It good resource for anyone interested in learning more about the technical aspects of deep learning.
Provides a practical guide to machine learning, including its algorithms, techniques, and applications. It good resource for anyone interested in learning more about the technical aspects of machine learning.
Provides a practical guide to machine learning using the R programming language. It good resource for anyone interested in learning more about the technical aspects of machine learning.
Provides a comprehensive overview of the current state of AI, including its potential benefits and risks. It good resource for anyone interested in learning more about the future of AI.
Save
Provides a philosophical exploration of the potential risks and benefits of AI. It good resource for anyone interested in learning more about the ethical implications of AI.
Provides a comprehensive overview of the current state of AI, including its potential benefits and risks. It good resource for anyone interested in learning more about the future of AI.
Save
Provides a speculative look at the future of humanity, including the potential impact of AI. It good resource for anyone interested in learning more about the potential implications of AI for society.
Provides a speculative look at the future of humanity, including the potential impact of AI. It good resource for anyone interested in learning more about the potential implications of AI for society.
Save
Provides a speculative look at the future of humanity, including the potential impact of AI. It good resource for anyone interested in learning more about the potential implications of AI for society.
Provides a gentle introduction to machine learning, including its algorithms, techniques, and applications. It good resource for anyone interested in learning more about the basics of machine learning.
Save
Provides a non-technical overview of AI, including its history, applications, and potential impact on society. It good resource for anyone interested in learning more about the basics of AI.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/dva646/introduction
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Time
128 hours
Level
Intermediate
Via
Pluralsight
Instructor
Ben Weissman
Language
English
Good to know
Develops foundational skills and knowledge about responsible use of AI, which is essential for anyone working in AI-related fields
Taught by Ben Weissman, an expert in the field of AI ethics and governance
Examines ethical considerations for using AI, which are important for addressing potential negative effects and biases
Covers responsible AI implementation, which is highly relevant to organizations using AI across industries
Provides a starting point for exploring ethical considerations in AI, though it may require supplemental learning for in-depth knowledge
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