AI Ethics, Responsible Use, and Creativity from Coursera

“AI Ethics, Responsible Use, & Creativity” explores ethics and responsible use of generative AI tools for creative work. After completing this course, you will learn how to engage with generative AI tools with an eye toward intentionality, sustainability, and responsibility.

You will learn the SIFT (Specify, Identify, Focus, Trust) process for evaluating AI tools. This compact method helps learners employ AI successfully and sustainably by realistically approaching the technology and prioritizing intentional decision-making for individuals and enterprises. You will learn the practical application of the SIFT framework by using it to evaluate tools and creative work developed in the first course. You will also learn about the reputational and legal risks of using AI in creative fields. You will explore issues of environmental cost, cultural bias, and data risks of contemporary GenAI tools through readings and a guest lecture by expert Justin Joque.

This is the second course in “AI for Creative Work,” a series exploring how artificial intelligence can enhance the work of creatives.

What's inside

Syllabus

Introduction to the Course

Introduction to Legal and Ethical Considerations

Bonus Content

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Examines the ethical considerations surrounding generative AI, which is crucial for responsible innovation and deployment in creative industries

Teaches the SIFT framework, which helps learners approach AI tools with intentionality and sustainability in their creative processes

Explores the reputational and legal risks associated with using AI in creative fields, which is essential for professionals to understand and mitigate

Examines issues of environmental cost, cultural bias, and data risks associated with contemporary GenAI tools, which are important considerations for responsible AI development

Belongs to a series exploring how artificial intelligence can enhance creative work, suggesting a comprehensive and detailed approach to the subject

Requires learners to have taken the first course in the series, which may be a barrier for some learners who are new to the topic

Reviews summary

Ai ethics and responsible use

According to learners, this course addresses relevant and timely topics surrounding AI ethics and responsible use. Students appreciate the introduction to crucial concepts and the useful SIFT framework provided for evaluating AI tools. The course is seen as providing a solid foundational understanding, covering important areas like legal, bias, and environmental risks. While generally seen as largely positive, some feedback indicates it could lack depth in certain areas and needs more practical application for those specifically focused on hands-on creative work. It is considered a strong starting point for those new to the subject.

Best suited for beginners or those needing an overview.

"Great for someone new to AI ethics and its implications."

"Provides a solid foundational understanding of key concepts."

"Might be too basic if you're already familiar with the topic or seeking advanced ethical frameworks."

Provides a structured method for evaluating AI.

"The SIFT framework is a useful takeaway I can actually apply."

"Found the SIFT process practical and easy to follow."

"Helped me structure my thinking about evaluating different AI tools effectively."

Addresses legal, bias, and other AI-related dangers.

"Learning about the legal risks of using AI was particularly enlightening."

"The segment on cultural bias in AI was very important and well-explained."

"They highlighted risks of GenAI use in creative fields I hadn't fully considered before taking this course."

Covers crucial, current topics in AI ethics.

"The ethical issues discussed are incredibly relevant right now."

"So important to understand these topics with AI everywhere."

"The course covers a timely subject that is crucial for anyone using AI tools."

Could benefit from more hands-on application.

"This was less practical than I hoped for applying directly to creative work."

"More theoretical discussion than hands-on application exercises."

"Didn't provide many tools or demonstrations for direct creative implementation using the ethical concepts."

Some topics could be explored in more detail.

"I wished some topics, like data privacy issues, were covered more deeply."

"Felt like a good overview for beginners, but not highly in-depth on complex issues."

"While broad, the course could benefit from more concrete examples or case studies in certain areas."

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, Responsible Use, and Creativity with these activities:

Ethics and Data Science

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Gain a deeper understanding of the ethical considerations surrounding data science and AI development.

View Ethics and Data Science on Amazon

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Obtain a copy of 'Ethics and Data Science'.
Read the book, focusing on chapters related to bias and fairness.
Reflect on how these ethical considerations apply to generative AI tools.

Review Intellectual Property Law

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Strengthen your understanding of intellectual property law to better navigate the legal risks associated with using AI in creative fields.

Browse courses on Copyright Law

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Review key concepts of copyright law.
Research recent court cases involving AI and copyright.
Consider how these legal precedents might impact your creative work.

Ethical AI Case Study Analysis

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Solidify your understanding of ethical AI principles by analyzing real-world case studies of AI misuse or ethical dilemmas.

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Research a case study involving ethical issues in AI.
Analyze the ethical implications of the case.
Write a report summarizing your findings and recommendations.

Four other activities

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Develop an AI Ethics Checklist

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Apply the SIFT framework and other ethical considerations to create a practical checklist for evaluating AI tools and creative work.

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Review the SIFT framework and ethical principles discussed in the course.
Develop a comprehensive checklist for evaluating AI tools.
Test your checklist on several AI tools and creative projects.
Refine your checklist based on your testing results.

Atlas of AI

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Explore the broader societal and environmental impacts of AI development and deployment.

View Atlas of AI on Amazon

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Obtain a copy of 'Atlas of AI'.
Read the book, paying attention to the sections on environmental costs and cultural bias.
Reflect on how these issues relate to your own creative work with AI.

Write a Blog Post on AI Ethics

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Reinforce your learning by summarizing key concepts and sharing your insights on AI ethics with a wider audience.

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Choose a specific topic related to AI ethics.
Research and gather information on your chosen topic.
Write a blog post summarizing your findings and offering your perspective.
Publish your blog post on a relevant platform.

Volunteer for an AI Ethics Initiative

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Gain practical experience and contribute to the field by volunteering for an organization working on AI ethics issues.

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Research organizations working on AI ethics.
Contact an organization and inquire about volunteer opportunities.
Contribute your skills and knowledge to the organization's work.

Career center

Learners who complete AI Ethics, Responsible Use, and Creativity will develop knowledge and skills that may be useful to these careers:

AI Ethicist

An AI Ethicist ensures that artificial intelligence systems are developed and used responsibly and ethically. This role involves developing guidelines, conducting risk assessments, and advising organizations on the ethical implications of AI. This course on AI ethics, responsible use, and creativity helps you prioritize intentional decision making for both individuals and enterprises. It will be helpful to understand the legal and reputational risks of using AI. You will learn to approach AI tools realistically, including the environmental costs, cultural bias, and data risks, that will allow you to inform your work as an AI Ethicist. Additionally, the SIFT process will help AI ethicists evaluate and use AI tools effectively.

See salaries and explore the career path for AI Ethicist

Technology Ethics Consultant

A Technology Ethics Consultant advises organizations on the ethical implications of technology, including artificial intelligence. This role involves assessing risks, developing responsible use policies, and ensuring alignment with ethical principles. This course on AI ethics, responsible use, and creativity will help you as a Technology Ethics Consultant understand the potential ethical challenges. You will also be able to effectively use the SIFT framework for evaluating AI tools, and will gain a robust understanding of risks, including reputational and legal risks. Also, this course will inform your work by covering the environmental costs, cultural biases, and data risks associated with current AI tools.

See salaries and explore the career path for Technology Ethics Consultant

Responsible AI Developer

A Responsible AI Developer creates AI systems while prioritizing ethical considerations and societal impact. This role requires a deep understanding of potential biases and risks in AI, and the ability to mitigate these issues through careful design and implementation. This course will help a Responsible AI Developer approach their work with intentionality, sustainability, and responsibility. By learning the SIFT process, you will gain a practical method for evaluating AI tools and their impact. The course's discussion about reputational and legal risks will inform design decisions, ensuring the ethical and responsible development of AI applications. This course teaches the practical application of the SIFT framework which is critical for a responsible AI developer.

See salaries and explore the career path for Responsible AI Developer

AI Policy Analyst

An AI Policy Analyst develops and evaluates policies related to the development and deployment of artificial intelligence. This role involves research, analysis, and advocacy to ensure that AI is used in a way that aligns with ethical and societal values. The course's focus on the ethical dimensions of AI helps an AI policy analyst understand the complexities surrounding new technologies. The SIFT framework provides a structured approach to analyzing AI tools, so policy recommendations are well developed and sound. This course also explores the environmental costs, cultural biases, and data risks of AI, which are crucial considerations for policy development. You will also be able to analyze the legal and reputational risks of AI in creative fields to inform your policy recommendations.

See salaries and explore the career path for AI Policy Analyst

AI Project Manager

An AI Project Manager oversees projects that involve artificial intelligence, ensuring they are delivered on time, within budget, and in alignment with ethical standards. This role requires a solid understanding of AI technologies, their potential risks, and responsible implementation. This course will help an AI Project Manager understand the ethical and responsible use of generative AI tools. The SIFT process will help you evaluate AI tools effectively, and the discussion of reputational and legal risks allows for a more comprehensive awareness of project considerations. Furthermore, the course will provide you with a better awareness of the environmental costs, cultural bias, and data risks of contemporary AI tools.

See salaries and explore the career path for AI Project Manager

Content Creator

A Content Creator produces engaging and informative content for various platforms, often using creative tools. This role requires understanding the capabilities and limitations of different content-creation technologies, including artificial intelligence. This course in AI ethics, responsible use, and creativity will help you as a content creator use generative AI tools responsibly. The SIFT process will help you evaluate AI tools, and the course's discussions about reputational and legal risks will help you to create and share content responsibly. The exploration of environmental costs, cultural bias, and data risks will allow you to apply a considered approach to content creation.

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Innovation Strategist

An Innovation Strategist identifies and implements new ideas and technologies to enhance an organization's performance. This often involves exploring emerging technologies like artificial intelligence. This course helps you as an Innovation Strategist evaluate and integrate AI responsibly. The SIFT framework provides a structured method for assessing the risks and benefits of AI tools. The discussion of reputational and legal risks of AI in creative fields will be particularly valuable. This course will also help you to evaluate innovative technologies in terms of environmental costs, cultural bias, and data risks.

See salaries and explore the career path for Innovation Strategist

Digital Media Strategist

A Digital Media Strategist develops and implements strategies for effective communication and engagement across various digital platforms. This role often involves using emerging technologies. This course can help a Digital Media Strategist responsibly integrate generative AI tools into their work. The SIFT framework provides a solid approach for evaluating AI tools to ensure they align with brand values and ethical guidelines. The course's discussion of reputational and legal risks associated with AI in creative fields will be particularly relevant to safeguarding a brand's image. The exploration of environmental costs, cultural bias, and data risks also contributes towards creating a responsible approach to digital media.

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Creative Director

A Creative Director leads the creative vision for a project, campaign, or brand. This role requires a deep understanding of creative processes and an awareness of technology's role in creation. This course will help a Creative Director understand the ethical and responsible use of generative AI tools, which are increasingly important in creative work. The SIFT framework is an effective tool for evaluating AI's impact. The course’s exploration of reputational and legal risks of AI in creative fields will also help you guide your team. The exploration of environmental costs, cultural bias, and data risks will help develop projects that are responsible, ethical, and socially aware.

See salaries and explore the career path for Creative Director

User Experience Designer

A User Experience Designer focuses on creating user-friendly and effective interfaces for digital products. This role often involves considering the ethical implications of technology and how it impacts users. This course will help a User Experience Designer responsibly integrate AI tools into designs, with the SIFT framework offering a method for assessing and improving AI-powered interfaces. By considering the reputational and legal risks introduced by AI in creative practice, the designer will be better prepared to protect the user. This course will also help you to evaluate digital tools with consideration for environmental costs, cultural bias, and data risks, allowing for a user experience that is both responsible and effective.

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Marketing Manager

A Marketing Manager develops and executes marketing strategies to promote products or services, and increasingly, such work involves using artificial intelligence. This course will help you to use AI tools ethically in your strategies, with the SIFT process as a practical tool to evaluate AI tools for marketing. The discussion of reputational and legal risks will allow you to create effective campaigns that are aligned with ethical standards. You will also have a stronger understanding of the environmental costs, cultural bias, and data risks of generative AI which will promote responsible marketing practice.

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Academic Researcher

An Academic Researcher conducts research on a wide variety of topics, usually earning a PhD before doing so. While the course does not explicitly focus on academic research methodology, it provides insights into the ethical and responsible use of AI, which is increasingly important in many research fields. The SIFT framework may be useful when incorporating AI tools into research projects. This course also covers the legal and reputational risks of AI in creative fields, but is not primarily designed for direct research application. This is a position that typically requires a PhD.

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Data Analyst

A Data Analyst collects, processes, and interprets large datasets to provide insights and recommendations. This role requires a deep understanding of statistics, data analysis tools, and emerging technologies like artificial intelligence. While this course does not directly teach quantitative data analysis, it focuses on the ethical and responsible use of AI tools in a creative context, which may be helpful if your work involves using AI tools. By learning the SIFT process, you may be able to evaluate AI tools more critically, but take note that this course is not focused on statistics or data analysis itself.

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Software Engineer

A Software Engineer develops and maintains software systems. This often involves working with a variety of programming languages and development tools. While this course does not directly teach software engineering, it explores the ethical and responsible use of generative AI, which may be helpful in integrating AI tools responsibly into code. The course provides practical approaches to evaluating these AI tools. However, please note that the course does not teach programming itself, so other courses may be more relevant.

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Project Manager

A Project Manager plans, executes, and closes projects, coordinating resources and ensuring project goals are met. While this course does not focus on project management itself, it explores the ethical and responsible use of generative AI tools in creative work. This may be helpful if your projects involve the use of artificial intelligence. By learning the SIFT process, you may better evaluate AI tools, but note that the course is not focused on project management principles, per se.

See salaries and explore the career path for Project Manager

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, Responsible Use, and Creativity.

Atlas of AI

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Examines the environmental, social, and political impacts of AI, providing a critical perspective on the technology's hidden costs. It is highly relevant to the course's focus on responsible AI use and sustainability. Reading this book will help students understand the broader context of AI development and its implications for society and the environment. It provides a valuable counterpoint to more optimistic views of AI.

Ethics and Data Science

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Provides a comprehensive overview of ethical considerations in data science, including bias, privacy, and fairness. It is particularly useful for understanding the ethical implications of AI algorithms and data used to train them. Reading this book will help students develop a strong foundation for responsible AI development and deployment, especially in creative contexts. It valuable resource for understanding the broader societal impact of AI.

Ethics and Data Science

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What's inside

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Reviews summary

Ai ethics and responsible use

Activities

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