Responsible AI and Ethics from Coursera

The course "Responsible AI and Ethics" explores the ethical, social, and technical aspects of artificial intelligence (AI) and machine learning (ML). It focuses on understanding bias in both human and machine systems and provides strategies for mitigating risks. By examining key issues such as fairness, accountability, and the regulatory landscape, learners will gain essential knowledge to navigate the ethical challenges in AI. Through case studies and real-world examples, students will explore the complexities of AI implementations, assessing their impact on society and industries.

This course provides practical insights into responsible AI development, emphasizing both ethical decision-making and effective risk management. By the end of the course, learners will be equipped to lead AI projects that balance innovation with accountability, ensuring AI systems are fair, transparent, and sustainable. This unique combination of theoretical knowledge and real-world applications makes the course invaluable for anyone aiming to lead in the AI field.

What's inside

Syllabus

Course Introduction

In this course, you will explore the ethical, social, and technical aspects of Artificial Intelligence (AI) and Machine Learning (ML), focusing on sources of bias, risk mitigation strategies, and the regulatory landscape. You'll examine the trade-offs between human and machine biases, AI team dynamics, and emerging labor trends. The key topics of this course include responsible AI use, legal frameworks, and the impact of evaluation methods on team performance. you will gain practical insights into building fairer, more effective AI systems through case studies and discussions.

Bias (Human and Machine)

This module introduces you to the concept of bias in Artificial Intelligence. While there has been much publicity and attention on the topic of machine bias, it often ignores human bias. In this module, you will compare human and machine bias to enable a more fair assessment of risk in AI systems. Specific attention will be paid to Machine Learning bias, algorithm bias, human bias, measurement bias, and algorithmic drift.

Responsible AI

This module introduces you to the complex topic of responsible AI. The common “risk-based approach” will be contrasted with the more ethical “human baseline approach.” You will also cover fiscal/performance responsibility, international regulations, privacy, and legal considerations.

Case Studies

This AI case studies module offers you practical insights into AI's transformative power across various applications. You will explore successful integrations and lessons from AI's challenges, focusing on decision-making, implementation, and outcomes. Real-world examples will help you understand critical success factors and avoid potential pitfalls in AI adoption.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Examines the regulatory landscape surrounding AI, which is crucial for professionals navigating the legal and ethical implications of AI development and deployment

Explores the trade-offs between human and machine biases, which is essential for building fairer and more effective AI systems that account for both types of biases

Presents case studies offering practical insights into AI's transformative power across various applications, which helps learners understand critical success factors and avoid potential pitfalls in AI adoption

Contrasts the risk-based approach with the human baseline approach to responsible AI, which provides a comprehensive understanding of ethical considerations in AI development

Presented by Johns Hopkins University, which is known for its research and academic programs in engineering, medicine, and public health, among other fields

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 and Ethics with these activities:

Review 'Ethics and Data Science'

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Gain a deeper understanding of ethical considerations in 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 chapters on bias and fairness.
Summarize key ethical considerations.
Relate concepts to course modules.

Review statistical concepts

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Solidify your understanding of statistical concepts related to bias and fairness in AI.

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Review basic statistical definitions.
Practice calculating statistical measures.
Identify potential sources of bias.

Bias detection tool

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Apply your knowledge by building a tool to detect bias in a dataset.

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Select a dataset for analysis.
Implement bias detection algorithms.
Evaluate the tool's performance.
Document your findings and code.

Four other activities

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Create a presentation on AI ethics

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Deepen your understanding by creating a presentation on AI ethics for a general audience.

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Research key ethical considerations.
Develop a clear and concise narrative.
Design visually appealing slides.
Practice your presentation skills.

Review 'Weapons of Math Destruction'

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Understand the real-world impact of biased algorithms and the importance of ethical AI development.

View Weapons of Math Destruction: How Big Data... on Amazon

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Obtain a copy of 'Weapons of Math Destruction'.
Read the book and take notes.
Identify examples of algorithmic bias.
Reflect on the book's implications.

Volunteer at an AI ethics organization

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Gain practical experience by volunteering at an organization focused on AI ethics.

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Identify relevant organizations.
Contact the organization and offer your services.
Contribute to their projects and initiatives.
Reflect on your experiences and learnings.

Develop an AI ethics checklist

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Create a practical checklist to guide ethical AI development and deployment.

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Research existing AI ethics guidelines.
Identify key ethical considerations.
Develop a comprehensive checklist.
Test the checklist on real-world scenarios.

Career center

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

AI Risk Analyst

An AI risk analyst evaluates potential risks associated with artificial intelligence systems within an organization. This involves assessing algorithmic biases and ensuring compliance with standards and guidelines. A course focusing on responsible artificial intelligence and ethics may be helpful for an AI risk analyst, particularly its coverage of risk mitigation strategies, bias analysis, and the regulatory landscape. This course will help provide context on how to evaluate real-world case studies and how to build more fair systems, making this an excellent fit for individuals interested in pursuing a career as an AI risk analyst.

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Data Privacy Officer

A data privacy officer is responsible for ensuring their organization complies with data privacy laws and regulations. An essential part of this job is proactively addressing issues related to the collection, storage, use, and transmission of data. This course on responsible artificial intelligence and ethics may be particularly relevant for a data privacy officer due to its focus on privacy and legal considerations. The course's exploration of responsible AI and risk management provides critical insights into navigating privacy issues related to AI systems. Taking this course can help a data privacy officer understand the ethical implications of AI, ensuring that their organization uses this technology in a responsible and compliant manner.

See salaries and explore the career path for Data Privacy Officer

Ethics Officer

An ethics officer is responsible for ensuring an organization adheres to ethical standards and legal regulations. This role requires a deep understanding of complex ethical issues, and a course focusing on responsible artificial intelligence and ethics may be particularly helpful. The course's emphasis on understanding and mitigating bias, as well as its exploration of legal frameworks and case studies, helps prepare an ethics officer to address ethical questions surrounding AI implementation within their organization. The course's discussion of the trade-offs between human and machine biases provides a solid foundation for navigating these questions.

See salaries and explore the career path for Ethics Officer

AI Product Manager

An AI product manager guides the strategy, roadmap, and execution of artificial intelligence products. This position requires a blend of technical knowledge, market awareness, and an understanding of ethical considerations. The course on responsible artificial intelligence and ethics may be instrumental to an AI product manager because it provides insights into responsible AI development, while also covering the trade-offs between human and machine biases. In this way, the course helps an AI product manager balance innovation with accountability, ensuring AI products are fair, transparent, and sustainable.

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AI Project Manager

An AI project manager oversees the planning, execution, and completion of artificial intelligence projects. The work requires coordinating and communicating with diverse teams, as well as ensuring a project meets its objectives and complies with organizational and ethical standards. This course on responsible artificial intelligence and ethics may help an AI project manager, particularly because of its emphasis on ethical decision making and effective risk management within AI project development. The course's examination of the trade-offs between human and machine biases, as well as its handling of case studies, provides a foundation for overseeing projects that balance innovation with accountability.

See salaries and explore the career path for AI Project Manager

AI Educator

An AI educator is someone who teaches others about artificial intelligence. This can happen in various settings such as a university, online, or in workshops and training programs. This course on responsible artificial intelligence and ethics may help an AI educator prepare quality material. Because the course focuses on ethical, social, and technical aspects of AI, it can help educators give a comprehensive view of artificial intelligence as it relates to bias, risk mitigation, and the regulatory landscape. The course also includes case studies that may be used as curriculum examples.

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Technology Consultant

A technology consultant provides expert advice and guidance to organizations on using AI and other technologies to solve business problems. This role requires a comprehensive understanding of complex technology and how to apply it successfully within different industries. A course focusing on responsible artificial intelligence and ethics may be beneficial for a technology consultant, especially due to its emphasis on exploring the complexities of AI implementations. The course's exploration of the ethical dimensions of AI, and its real-world case studies, allow a technology consultant to make responsible recommendations to their clients.

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Compliance Officer

A compliance officer ensures a business follows both internal rules and external regulations. A key aspect of this role is staying ahead of regulatory mandates and identifying current business practices that could lead to issues. The course on responsible artificial intelligence and ethics may be beneficial for a compliance officer, primarily because it provides exposure to international regulations and legal considerations surrounding artificial intelligence. Understanding the ethical risks and considerations discussed in the course strengthens the compliance officer's ability to advise the business.

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Data Scientist

Data scientists analyze large amounts of data to extract insights that may be useful for business decisions. They may create models to help the organization understand complex relationships in the data, and a course on responsible artificial intelligence and ethics may be helpful for a data scientist working on AI applications. The course's focus on bias in machine learning, risk mitigation strategies, and fair use of data can greatly enhance a data scientist's work. The course material helps a data scientist create more accurate models that take into account social and ethical considerations.

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Policy Analyst

A policy analyst researches and develops policies for governmental and non-governmental organizations. They need to understand complex problems and propose comprehensive solutions that are both effective and pragmatic. A course on responsible artificial intelligence and ethics may be valuable for an aspiring policy analyst, especially one interested in technology policy. The course's exploration of the regulatory landscape, as well as the ethical and social dimensions of AI, helps build a foundation for developing responsible and effective policies. The case studies covered in the course provide concrete examples of AI implementation and its impact on society.

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Research Scientist

A research scientist conducts research to expand scientific knowledge in a particular field. Depending on the field, this role may require an advanced degree like a PhD. A course on responsible artificial intelligence and ethics may be helpful to a research scientist working in artificial intelligence due to its coverage of bias, risk mitigation, and the social impact of AI. The course's insights into the complexities of AI implementations, evaluation methods, and emerging labor trends provides crucial context to a research scientist whose focus is on pushing the boundaries of the field. It helps inform a more nuanced approach to AI research.

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Software Developer

A software developer is a professional who builds and maintains computer software. The work requires technical expertise, as well as a comprehensive understanding of ethical considerations. A course focusing on responsible artificial intelligence and ethics may be beneficial for a software developer who works on AI systems, as it covers crucial areas of development such as bias mitigation, risk management, and fairness. Taking a course on responsible AI will help a software developer ensure their work aligns with the best practices in the field and does not cause harm through the implementation of bias.

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Innovation Manager

An innovation manager is responsible for fostering a culture of innovation within an organization. This role focuses on identifying opportunities for growth through new ideas and technologies. The course on responsible artificial intelligence and ethics may be helpful to an innovation manager due to its emphasis on understanding the ethical, social, and technical aspects of artificial intelligence. With this understanding, the innovation manager can better encourage the adoption of AI in a way that is both innovative and responsible, as well as promote the balance of innovation with accountability.

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Human Resources Specialist

A human resources specialist is responsible for managing an organization's employees, including recruitment, training, and managing performance. A course on responsible artificial intelligence and ethics may help a human resources specialist. This is because of the course's focus on understanding bias in both human and machine systems, exploring the trade-offs between human and machine biases, and examining emerging labor trends. These skills are relevant in hiring, employee development, and performance evaluation, especially as organizations increasingly integrate AI into their workflows. This course will make an HR specialist more aware of the impact of AI.

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Sustainability Analyst

A sustainability analyst promotes environmentally and socially responsible practices. This includes identifying risks and opportunities for an organization to improve its impact on society and the planet. Although this role is not directly related to AI, the course on responsible artificial intelligence and ethics may be helpful, particularly because of its coverage of how to build more fair and sustainable systems. The course's focus on responsible AI development, ethical decision-making, and risk management may be applied to broader sustainability challenges.

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