AI Ethics for Professionals from edX

In a world where Artificial Intelligence is rapidly transforming every aspect of our lives, understanding the ethical implications of AI has never been more crucial. This comprehensive AI Ethics course equips you with the knowledge and skills to navigate the complex landscape of AI development and deployment responsibly.

Over four engaging units, you'll dive deep into the promises and perils of generative AI, explore key ethical challenges, and master practical frameworks for ethical AI governance. Whether you're a developer, business leader, policymaker, or simply an AI enthusiast, this course will empower you to make informed decisions in the age of AI.

Key Learning Objectives

Understand the fundamental principles of AI ethics and their importance in AI development and deployment.
Analyze the societal impact of AI technologies, including privacy, employment, and social interaction implications.
Identify and critically evaluate key ethical challenges in AI, such as bias, transparency, accountability, and potential misuse.
Examine legal and regulatory considerations surrounding AI, including current laws and the role of regulation.
Develop and apply ethical frameworks for AI decision-making in various contexts.
Evaluate and compare different AI governance approaches, from organizational policies to national and international regulations.
Communicate effectively about AI ethics issues and proposed solutions to both technical and non-technical audiences.
Promote responsible AI development and use within organizations and broader society.

Why It Matters:

As AI becomes increasingly integrated into our society, the ability to think critically about its ethical implications is not just valuable—it's essential. This course will give you the tools to:

Lead AI strategy and governance efforts in your organization
Make ethically informed decisions when developing or deploying AI systems
Contribute meaningfully to the global conversation on responsible AI

By the end of this course, you'll have a robust understanding of AI ethics principles and practical skills to apply them in real-world scenarios. Join us in shaping an ethical future for AI—enroll today!

What's inside

Learning objectives

This course provides a comprehensive exploration of the ethical challenges and considerations surrounding the development and deployment of artificial intelligence (ai) systems, with a focus on generative ai. students will gain a deep understanding of key ethical issues in ai, including alignment, transparency, security, bias, and responsibility. the course will also cover ai governance frameworks, standards, and best practices for responsible ai development and use. through case studies, discussions, and practical exercises, students will develop critical thinking skills and learn to apply ethical reasoning to real-world ai scenarios.
Grasp the fundamental distinctions between machine learning and generative ai
Unpack critical ethical issues in ai, including alignment, transparency, security, bias, and responsibility

Explore real-world case studies of ai ethics in action
Master ai governance frameworks from global leaders like the eu, us, and major tech companies
Develop skills to create and evaluate effective ai ethical statements

This course provides a comprehensive exploration of the ethical challenges and considerations surrounding the development and deployment of artificial intelligence (ai) systems, with a focus on generative ai. students will gain a deep understanding of key ethical issues in ai, including alignment, transparency, security, bias, and responsibility. the course will also cover ai governance frameworks, standards, and best practices for responsible ai development and use. through case studies, discussions, and practical exercises, students will develop critical thinking skills and learn to apply ethical reasoning to real-world ai scenarios.
Grasp the fundamental distinctions between machine learning and generative ai
Unpack critical ethical issues in ai, including alignment, transparency, security, bias, and responsibility
Explore real-world case studies of ai ethics in action
Master ai governance frameworks from global leaders like the eu, us, and major tech companies
Develop skills to create and evaluate effective ai ethical statements

Syllabus

Unit 1: GenAI Promises and Risks

The promise and peril of generative AI

Distinctions between machine learning and generative AI

AI alignment: challenges in aligning AI with human values, interests, and rights

Transparency in AI systems: importance and challengesAI security: types of attacks and vulnerabilities

Bias in AI: sources, implications, and case studies

The problem of responsibility in AI-driven decisions

Unit 2: How Can We Trust AI?

Key elements of trustworthy AI systems

Safety and harm mitigation strategies

Privacy and data security considerations in AI

Explainability and interpretability in AI systems

Addressing potential biases in AI models

Case studies on AI trustworthiness (e.g., ChatGPT, facial recognition technologies)

Human-in-the-loop approaches to AI oversight

Unit 3: AI Governance and Regulation

Overview of AI governance approaches

The EU AI Act: risk-based classification and governance structures

U.S. federal efforts in AI governance: The Blueprint for an AI Bill of Rights

Executive Order on Safe, Secure, and Trustworthy AI

NIST AI Risk Management Framework

Comparing EU and U.S. approaches to AI regulation

AI governance in enterprises: case study of IBM's AI ethics structure

Implementing AI ethics in small and medium-sized businesses

Balancing top-down and bottom-up approaches to AI ethics

Challenges and considerations in organizational AI governance

Unit 4: Communicating AI Ethics

Purpose and importance of AI ethical statements

Analyzing and comparing organizational AI principles (e.g., Google, Anthropic)

Elements of effective ethical statements:

Communicating values and commitments

Specifying actionable policies and processes

Grounding ethical statements in broader ethical frameworks

Addressing specific ethical concerns (e.g., bias, privacy, safety)

Translating ethical principles into governance structures

Communicating AI ethics to various stakeholders (e.g., users, developers, policymakers)Practical exercise: Crafting and critiquing AI ethics statements

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Provides practical frameworks for ethical AI governance, which is essential for professionals navigating the complexities of AI development and deployment in various sectors

Examines legal and regulatory considerations surrounding AI, including current laws and the role of regulation, which is crucial for compliance and risk management

Explores real-world case studies of AI ethics in action, which helps learners understand the practical implications of ethical considerations in AI deployment

Requires learners to analyze and compare organizational AI principles, such as those of Google and Anthropic, which may require familiarity with these organizations

Covers the EU AI Act and U.S. federal efforts, which may not be directly applicable to learners outside of these jurisdictions, although they offer valuable insights

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 AI Ethics for Professionals with these activities:

Review Machine Learning Fundamentals

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Reviewing machine learning fundamentals will provide a solid foundation for understanding the distinctions between machine learning and generative AI, a key topic in Unit 1.

Browse courses on Machine Learning

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Review key concepts like supervised and unsupervised learning.
Practice basic machine learning algorithms.
Familiarize yourself with common machine learning terminology.

Review 'Ethics and Data Science'

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Reading this book will provide a broader understanding of data ethics, which is essential for grasping the nuances of AI ethics.

View Ethics and Data Science on Amazon

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Read the book, focusing on chapters related to bias and privacy.
Take notes on key concepts and examples.
Reflect on how these concepts apply to AI systems.

Write a blog post on AI bias

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Writing a blog post on AI bias will solidify your understanding of the topic and improve your communication skills, which are crucial for discussing AI ethics with various audiences.

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Research different types of AI bias and their causes.
Find real-world examples of AI bias.
Write a clear and concise blog post explaining the issue.
Share your blog post on social media.

Four other activities

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Review 'AI Ethics' by Mark Coeckelbergh

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Reading this book will provide a deeper philosophical understanding of the ethical issues surrounding AI.

View Communicative AI: A Critical Introduction to... on Amazon

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Read the book, focusing on chapters related to responsibility and autonomy.
Take notes on key arguments and concepts.
Reflect on how these concepts relate to real-world AI applications.

Develop an AI Ethics Checklist

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Developing an AI ethics checklist will help you internalize the key ethical considerations and apply them to real-world AI projects.

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Research existing AI ethics frameworks and guidelines.
Identify key ethical considerations for AI development and deployment.
Create a checklist with actionable steps for each consideration.
Test your checklist on a hypothetical AI project.

Presentation on AI Governance Frameworks

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Creating a presentation on AI governance frameworks will deepen your understanding of different approaches to AI regulation and governance, as covered in Unit 3.

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Research different AI governance frameworks (EU AI Act, NIST AI RMF, etc.).
Compare and contrast the different frameworks.
Create a presentation summarizing the key features of each framework.
Present your findings to a group of peers or colleagues.

Volunteer at an AI Ethics Organization

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Volunteering at an AI ethics organization will provide practical experience and exposure to real-world ethical challenges in AI.

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Research AI ethics organizations in your area or online.
Contact the organization and inquire about volunteer opportunities.
Contribute your skills and knowledge to the organization's mission.

Career center

Learners who complete AI Ethics for Professionals will develop knowledge and skills that may be useful to these careers:

AI Ethics Consultant

An AI Ethics Consultant guides organizations in navigating the complex ethical landscape of artificial intelligence. This role involves assessing AI projects, identifying potential ethical risks, and developing strategies to ensure responsible AI development and deployment. This course is particularly relevant as it covers fundamental principles of AI ethics, bias, transparency, and accountability, all of which are critical areas of expertise for an AI Ethics Consultant. The course also provides practical frameworks for AI governance, which would help consultants develop effective strategies, and examine legal and regulatory considerations, which provides a well-rounded understanding needed in this role.

See salaries and explore the career path for AI Ethics Consultant

AI Policy Analyst

An AI Policy Analyst researches, analyzes, and develops policy recommendations related to artificial intelligence. This position is crucial for ensuring AI technologies are used responsibly and ethically within government and regulatory bodies. This course on AI ethics helps an AI Policy Analyst understand the ethical implications of AI, and learn about key issues such as bias, transparency, and accountability as they relate to policy. Further, the course reviews current laws and regulatory considerations, preparing professionals for the complexities of the policy landscape. The course also explores various governance approaches, which can directly impact an analyst's work.

See salaries and explore the career path for AI Policy Analyst

Technology Ethics Advocate

A Technology Ethics Advocate champions the ethical use of technology, ensuring that decisions are made with consideration for social impact and human rights. This role promotes responsible technological innovation and implementation. This course explores the fundamental principles of AI ethics and the societal impact of AI technologies making it very relevant. The course also covers the legal and regulatory landscape of AI, which an advocate must be familiar with. In addition, the course details the importance of ethical AI, making it particularly useful for an individual wishing to pursue this path.

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Compliance Officer

A compliance officer ensures that a company adheres to legal standards and internal policies. This role within the context of AI involves developing and implementing systems to ensure AI technologies are used ethically and in compliance with relevant regulations. This course is highly applicable as it explores key elements of trustworthy AI systems. It also goes into privacy and data security considerations which are critical for compliance. A compliance officer needs to know about AI governance to better evaluate and implement controls. This course provides a broad understanding of the issues.

See salaries and explore the career path for Compliance Officer

Corporate Social Responsibility Manager

A Corporate Social Responsibility Manager develops and implements a company's social responsibility initiatives. As AI becomes more pervasive, this includes ensuring responsible and ethical use of AI throughout the organization. This course helps a Corporate Social Responsibility Manager develop expertise regarding biases, transparency, accountability, and the potential misuse of AI. Moreover, the practical frameworks detailed in this course would help an individual create effective AI governance strategies and the legal and regulatory content would assist in ensuring that the company is acting responsibly. The course content prepares one to promote responsible development.

See salaries and explore the career path for Corporate Social Responsibility Manager

Data Governance Specialist

A Data Governance Specialist develops and implements data strategies, policies, and standards to ensure data is handled ethically and responsibly. This is especially pertinent in the context of AI where large data sets may be used to train models. The course explores key issues like privacy and bias which are directly relevant to the work of a Data Governance Specialist. Furthermore, the course also addresses AI governance frameworks which provides methods that would help in the creation of a data strategy and standards. This helps a specialist ensure responsible management of AI data.

See salaries and explore the career path for Data Governance Specialist

Innovation Manager

An Innovation Manager oversees the implementation of new ideas and technologies within organizations. This role requires an understanding of the ethical implications of new technologies, particularly with the rapid advancements in AI. This course would be useful by providing an overview of the promises and perils of generative AI, and by outlining the ethical challenges involved in AI. The practical frameworks given in the course would aid the Innovation Manager in responsible deployment of new technologies. This course's exploration of governance and regulation would also be beneficial.

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AI Product Manager

An AI Product Manager guides the development and launch of AI products, ensuring they are not only functional but also adhere to ethical guidelines. This role is pivotal in the responsible development of AI. This course may be useful as it analyzes biases and security concerns which a product manager must be aware of. Also the course explores the importance of AI alignment with human values and interests. For an AI Product Manager, this training serves as an important introduction to the ethical considerations that must be weighed when developing new AI products.

See salaries and explore the career path for AI Product Manager

Public Relations Specialist

A Public Relations Specialist manages the public image of an organization or person. As AI becomes more prominent, the role of a public relations professional increasingly includes communicating AI ethics and practices to the public. The course would be useful in understanding key elements of trustworthy AI systems. Moreover, the course teaches how to communicate AI ethics which would be very helpful. This course also covers specific ethical concerns like bias and privacy, which are important areas for someone in public relations to understand.

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Research Scientist

A Research Scientist engaged in AI may find this course helpful as it provides a comprehensive background in AI ethics, biases, and governance. Although this path typically requires a PhD, the course may be useful for professionals working in fields such as AI alignment, fairness, and transparency, as it provides a framework for understanding and addressing practical issues. The course's learning objectives, focused on ethical challenges and critical thinking, can help the research scientist create better AI research practices.

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Software Engineer

A Software Engineer may find that this course is useful in providing insight into the ethical considerations of AI, especially in the areas concerning bias, transparency, and accountability. While this role is more focused on the technical aspects of creating software, the course can help build a foundation in ethical AI which may be very useful for professionals in this field who are working with AI. The course may also help an engineer communicate effectively with various stakeholders regarding ethical concerns.

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Project Manager

A Project Manager may find this course useful. As a Project Manager, understanding the ethical implications of AI projects is becoming critical for successful implementation and alignment with stakeholder expectations. The course offers frameworks for ethical AI decision making, which is directly relevant to managing responsible projects. Additionally, the course covers AI governance and regulations, and the course can help the project manager better direct the projects they manage.

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Business Analyst

A Business Analyst may find that this training is helpful. This role often involves analyzing trends and providing advice that supports crucial business decisions, and the advent of AI has made understanding AI ethics essential. This course helps an analyst understand practical frameworks for ethical AI governance, which assists in providing informed recommendations. Also, the course provides insight into the societal impacts of AI, and this knowledge would help the analyst better support business decisions.

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Human Resources Specialist

A Human Resources Specialist is involved in workplace policies and practices including the use of AI tools in human resources. This job may find the course helpful. The course’s exploration of bias in AI would help in creating fair and transparent AI tools for the workplace. In addition, the course’s overview of important legal considerations regarding AI would be important for individuals in this position. This course can help keep a Human Resources Specialist up to date on important ethical considerations.

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Teacher

A teacher may find that this course is helpful, especially if they are teaching younger students about technology. The course explores the promises, perils, and ethical challenges of AI, and provides a framework for discussing responsible technology use. Further, the course explores key issues such as bias, transparency, and accountability. The practical exercises and case studies of the course also provide valuable teaching materials and discussion points. This course would be particularly useful in education.

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Reading list

We've selected two 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 AI Ethics for Professionals.

Communicative AI

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Offers a comprehensive and philosophical exploration of AI ethics. It delves into the fundamental ethical questions raised by AI, such as responsibility, autonomy, and human dignity. It is particularly useful for students seeking a deeper understanding of the theoretical underpinnings of AI ethics. This book is commonly used in university courses on AI ethics.

Communicative AI: A Critical Introduction to Large...

Hardcover

$$$

Ethics and Data Science

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Provides a broad overview of ethical considerations in data science, including bias, privacy, and fairness. It's a valuable resource for understanding the ethical challenges discussed throughout the course. While not specifically focused on AI, the principles discussed are highly relevant to AI ethics. It serves as a good reference for understanding the broader context of data ethics.

Ethics and Data Science

Kindle Edition

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AI Ethics for Professionals

What's inside

Learning objectives

Syllabus

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Activities

Career center

Reading list

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