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Data Science Ethics

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Based on 4 ratings
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H. V. Jagadish

As patients, we care about the privacy of our medical record; but as patients, we also wish to benefit from the analysis of data in medical records. As citizens, we want a fair trial before being punished for a crime; but as citizens, we want to stop terrorists before they attack us. As decision-makers, we value the advice we get from data-driven algorithms; but as decision-makers, we also worry about unintended bias. Many data scientists learn the tools of the trade and get down to work right away, without appreciating the possible consequences of their work.

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As patients, we care about the privacy of our medical record; but as patients, we also wish to benefit from the analysis of data in medical records. As citizens, we want a fair trial before being punished for a crime; but as citizens, we want to stop terrorists before they attack us. As decision-makers, we value the advice we get from data-driven algorithms; but as decision-makers, we also worry about unintended bias. Many data scientists learn the tools of the trade and get down to work right away, without appreciating the possible consequences of their work.

This course focused on ethics specifically related to data science will provide you with the framework to analyze these concerns. This framework is based on ethics, which are shared values that help differentiate right from wrong. Ethics are not law, but they are usually the basis for laws.

Everyone, including data scientists, will benefit from this course. No previous knowledge is needed.

Enroll now

What's inside

Learning objectives

  • Who owns data
  • How we value different aspects of privacy
  • How we get informed consent
  • What it means to be fair

Traffic lights

Read about what's good
what should give you pause
and possible dealbreakers
Develops an understanding of the relationship between data science and ethics
Taught by H. V. Jagadish, an experienced expert in data science
Relevant to individuals in various roles, including patients, citizens, and decision-makers
Explores ethical considerations related to data ownership, privacy, fairness, and bias
Provides a strong foundation for understanding the ethical implications of data science

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Reviews summary

Framework for data science ethics

According to learners, this course offers a solid and much-needed framework for understanding the ethical implications of data science. Many find the topic highly relevant and critically important in today's world. The course provides a thought-provoking exploration of complex issues like privacy, fairness, and bias. While some reviews mention the philosophical nature of the content and a potential lack of practical coding examples, the overall sentiment is strongly positive, with many appreciating the clear explanations and structured approach to tackling challenging ethical dilemmas. Students feel it provides essential context often missing in technical data science training.
Debate on abstract vs. applied focus.
"The course is quite philosophical and abstract, which is good for understanding the concepts, but sometimes lacks practical application."
"I enjoyed the philosophical depth, but I was hoping for more concrete examples or case studies related to coding practices."
"It's more about the *why* than the *how*, which is fine, but set your expectations accordingly."
"Could benefit from integrating more technical scenarios or examples of ethical AI/ML implementation challenges."
Concepts are explained well.
"The instructor does an excellent job of explaining complex ethical concepts clearly."
"I found the lectures easy to follow and the explanations insightful."
"Despite the challenging topic, the material was presented in a very accessible way."
"The clarity of the explanations made grappling with the ethical dilemmas much easier."
Prompts deep thinking on key issues.
"The course material is highly thought-provoking, forcing you to confront difficult questions about data use."
"I found myself constantly reflecting on the examples and frameworks presented long after the lectures."
"It challenges your perspectives on privacy, fairness, and consent in a meaningful way."
"This course sparks important discussions and self-reflection."
Covers a critical and timely topic.
"The topic of data science ethics is incredibly relevant and important right now, and this course addresses it directly."
"This course is essential for anyone working with data today. The ethical considerations are paramount."
"I wish more data scientists took this course. The issues discussed are vital for building responsible systems."
"The content feels incredibly timely and crucial for the future of technology."
Provides a crucial framework for ethics.
"This course provides a much-needed framework for understanding and navigating the ethical challenges inherent in data science."
"The framework presented here is incredibly valuable, helping me structure my thinking around complex ethical issues."
"I feel much better equipped to identify and analyze ethical dilemmas in my work after taking this course."
"It gave me a solid foundation for approaching ethics in a data-driven world."
Some challenges with assignments/grading.
"Some of the assignments, particularly the peer-reviewed ones, felt subjective and the grading inconsistent."
"I struggled with the peer review process; it felt like reviewers sometimes didn't understand the prompt."
"Grading criteria weren't always perfectly clear, leading to some frustration on assignments."
"More structure or guidance on peer review and assignment expectations would be helpful."

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 Data Science Ethics with these activities:
Review notes and readings from ethics courses
Review previous knowledge of ethics to strengthen foundational understanding.
Browse courses on Ethics
Show steps
  • Gather notes and readings from previous ethics courses.
  • Review notes and readings, focusing on key concepts and principles.
  • Identify areas where your understanding is strong and where you need improvement.
Review Ethics Principles
Review core ethical principles and consider how they may apply to the field of data science.
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Show steps
  • Read and summarize articles on ethics in data science.
  • Identify and analyze ethical dilemmas that may arise in data science projects.
Review basic concepts in data science before class
Reviewing basic concepts in data science will help you to better understand the material covered in this course.
Browse courses on Data Science Concepts
Show steps
  • Read textbook chapters on data science fundamentals.
  • Complete online tutorials on data science concepts.
  • Watch videos on data science topics.
11 other activities
Expand to see all activities and additional details
Show all 14 activities
Connect with Data Ethics Professionals
Seek guidance and insights from experienced professionals in the field of data ethics.
Browse courses on Data Ethics
Show steps
  • Attend industry events and conferences.
  • Reach out to professionals on LinkedIn or other networking platforms.
Read tutorial on data ethics
Reading a tutorial on data ethics will help you to understand the ethical considerations of data science.
Browse courses on Data Ethics
Show steps
  • Find a tutorial on data ethics that is relevant to your interests.
  • Read the tutorial carefully and take notes.
  • Complete any exercises or activities that are included in the tutorial.
Learn about Data Privacy Regulations
Understand the legal and regulatory frameworks governing data privacy to ensure compliance.
Browse courses on Data Privacy
Show steps
  • Research and familiarize yourself with relevant data privacy regulations.
  • Identify best practices for implementing data privacy measures in data science projects.
Engage in Ethical Case Studies
Discuss real-world ethical scenarios and analyze different perspectives to enhance ethical reasoning.
Browse courses on Ethics
Show steps
  • Present an ethical case study to the group.
  • Facilitate a group discussion, exploring diverse ethical viewpoints.
Analyze Ethical Implications of Data Science Projects
Develop critical thinking skills to identify and assess ethical implications in data science projects.
Browse courses on Ethics
Show steps
  • Examine case studies and real-world examples.
  • Conduct ethical impact assessments for potential data science projects.
Complete practice problems on data ethics
Completing practice problems on data ethics will help you to apply the concepts you have learned.
Browse courses on Data Ethics
Show steps
  • Find a set of practice problems on data ethics that are relevant to your interests.
  • Work through the problems carefully and check your answers.
  • Review your answers and identify any areas where you need further study.
Develop a Data Ethics Policy
Create a comprehensive policy outlining ethical guidelines for data handling and analysis within an organization.
Browse courses on Data Ethics
Show steps
  • Gather input from stakeholders and subject matter experts.
  • Draft a policy that addresses key ethical issues and establishes clear principles.
  • Review and refine the policy to ensure clarity and enforceability.
Participate in Data Science Ethics Competitions
Engage in competitions that focus on ethical considerations in data science and AI to gain practical experience.
Browse courses on Data Ethics
Show steps
  • Identify and register for relevant data science ethics competitions.
  • Team up with others or work individually on competition projects.
  • Develop and implement data science solutions while adhering to ethical principles.
Write a blog post on a data ethics topic
Writing a blog post on a data ethics topic will help you to deepen your understanding of the topic and to share your knowledge with others.
Browse courses on Data Ethics
Show steps
  • Choose a data ethics topic that you are interested in.
  • Research the topic thoroughly.
  • Write a blog post that is clear, concise, and informative.
  • Publish your blog post on a platform where others can read it.
Mentor a junior data scientist on data ethics
Mentoring a junior data scientist on data ethics will help you to solidify your understanding of the topic and to make a difference in the life of another person.
Browse courses on Data Ethics
Show steps
  • Find a junior data scientist who is interested in learning about data ethics.
  • Meet with the junior data scientist regularly to discuss data ethics topics.
  • Provide the junior data scientist with resources and support.
  • Help the junior data scientist to develop their skills in data ethics.
Contribute to an open-source project on data ethics
Contributing to an open-source project on data ethics will help you to learn about the latest developments in the field and to make a difference in the world.
Browse courses on Data Ethics
Show steps
  • Find an open-source project on data ethics that you are interested in.
  • Contact the project maintainers and express your interest in contributing.
  • Follow the project's contribution guidelines.
  • Submit your contributions to the project.

Career center

Learners who complete Data Science Ethics will develop knowledge and skills that may be useful to these careers:
Data Scientist
Data Scientists analyze data to extract meaningful insights and solve business problems. They may also develop and implement machine learning models. This course will help Data Scientists understand ethical considerations in data collection, use, and analysis. It will also cover topics such as privacy and security, which are essential for Data Scientists to understand.
See salaries and explore the career path for Data Scientist
Machine Learning Engineer
Machine Learning Engineers build and maintain machine learning models. They may also work on data preprocessing, feature engineering, and model evaluation. This course will help Machine Learning Engineers understand ethical considerations in the development and deployment of machine learning models. It will also cover topics such as fairness and bias, which are important for Machine Learning Engineers to be aware of.
See salaries and explore the career path for Machine Learning Engineer
Data Analyst
Data Analysts clean and analyze data to find patterns and trends. They may also create data visualizations and reports. This course will help Data Analysts understand ethical considerations in data collection, use, and analysis. It will also cover topics such as privacy and security, which are important for Data Analysts to understand.
See salaries and explore the career path for Data Analyst
Data Engineer
Data Engineers build and maintain data pipelines. They may also work on data integration, data cleaning, and data transformation. This course will help Data Engineers understand ethical considerations in data collection, use, and analysis. It will also cover topics such as privacy and security, which are important for Data Engineers to understand.
See salaries and explore the career path for Data Engineer
Software Engineer
Software Engineers design, develop, and maintain software systems. They may also work on data analysis and machine learning. This course will help Software Engineers understand ethical considerations in software development. It will also cover topics such as privacy and security, which are important for Software Engineers to understand.
See salaries and explore the career path for Software Engineer
Product Manager
Product Managers manage the development and launch of new products. They may also work on data analysis and market research. This course will help Product Managers understand ethical considerations in product development. It will also cover topics such as privacy and security, which are important for Product Managers to understand.
See salaries and explore the career path for Product Manager
Business Analyst
Business Analysts analyze business processes and data to identify areas for improvement. They may also work on data visualization and reporting. This course will help Business Analysts understand ethical considerations in data collection, use, and analysis. It will also cover topics such as privacy and security, which are important for Business Analysts to understand.
See salaries and explore the career path for Business Analyst
Consultant
Consultants provide advice and guidance to businesses on a variety of topics, including data science and ethics. This course will help Consultants understand ethical considerations in data collection, use, and analysis. It will also cover topics such as privacy and security, which are important for Consultants to understand.
See salaries and explore the career path for Consultant
Policy Analyst
Policy Analysts research and analyze public policy issues. They may also work on data analysis and reporting. This course will help Policy Analysts understand ethical considerations in data collection, use, and analysis. It will also cover topics such as privacy and security, which are important for Policy Analysts to understand.
See salaries and explore the career path for Policy Analyst
Lawyer
Lawyers advise clients on legal matters, including data privacy and security. This course will help Lawyers understand ethical considerations in data collection, use, and analysis. It will also cover topics such as informed consent and data ownership, which are important for Lawyers to understand.
See salaries and explore the career path for Lawyer
Journalist
Journalists research and write news stories. They may also work on data analysis and visualization. This course will help Journalists understand ethical considerations in data collection, use, and analysis. It will also cover topics such as privacy and confidentiality, which are important for Journalists to understand.
See salaries and explore the career path for Journalist
Ethnographer
Ethnographers study human behavior and culture. They may also work on data analysis and reporting. This course will help Ethnographers understand ethical considerations in data collection, use, and analysis. It will also cover topics such as privacy and confidentiality, which are important for Ethnographers to understand.
See salaries and explore the career path for Ethnographer
UX Researcher
UX Researchers study user experience and design. They may also work on data analysis and visualization. This course will help UX Researchers understand ethical considerations in data collection, use, and analysis. It will also cover topics such as privacy and user consent, which are important for UX Researchers to understand.
See salaries and explore the career path for UX Researcher
Social Scientist
Social Scientists study society and human behavior. They may also work on data analysis and reporting. This course will help Social Scientists understand ethical considerations in data collection, use, and analysis. It will also cover topics such as privacy and confidentiality, which are important for Social Scientists to understand.
See salaries and explore the career path for Social Scientist
Anthropologist
Anthropologists study human societies and cultures. They may also work on data analysis and reporting. This course will help Anthropologists understand ethical considerations in data collection, use, and analysis. It will also cover topics such as privacy and confidentiality, which are important for Anthropologists to understand.
See salaries and explore the career path for Anthropologist

Reading list

We've selected eight 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 Data Science Ethics.
Cover image
Ethics and Data Science
Save
An overview of data science ethics, including historical and philosophical perspectives.
Ethics and Data Science
Kindle Edition
Check Price
Cover image
Data Ethics
Save
A practical guide to data ethics and responsible AI development.
Data Ethics: Practical Strategies for Implementing...
Paperback
$$
Data Ethics: Practical Strategies for Implementing...
Kindle Edition
$$$
Cover image
Ethics of Artificial Intelligence
Save
A philosophical exploration of the ethical issues surrounding AI.
Ethics of Artificial Intelligence
Paperback
$$
Ethics of Artificial Intelligence
Kindle Edition
$$
Cover image
Algorithmic Discrimination and Ethical Perspective...
Save
An examination of the ways in which AI algorithms can perpetuate social and economic inequality.
Algorithmic Discrimination and Ethical Perspective...
Kindle Edition
$$$$
Cover image
Weapons of Math Destruction
Save
An examination of the dangers of using big data for social and political purposes.
Weapons of Math Destruction: How Big Data Increases...
Paperback
$$
Weapons of Math Destruction: How Big Data Increases...
Kindle Edition
$
The Shame Machine: Who Profits in the New Age of...
Hardcover
$$
(Español) Armas de Destruccion Matematica (Narración en...
Audible Audiobook
$$
Weapons of mass destruction math (Korean Edition)
Paperback
$$
Cover image
Ethics of Big Data
Save
An exploration of the ethical issues raised by big data, including privacy, discrimination, and algorithmic bias.
Ethics of Big Data: Balancing Risk and Innovation
Paperback
$$
Ethics of Big Data: Balancing Risk and Innovation
Kindle Edition
$$
Cover image
Automating Inequality
Save
An examination of the social and political implications of algorithms.
Automating Inequality
Paperback
Check
Automating Inequality
Kindle Edition
Check
Cover image
Planning with Complexity
Save
An introduction to the use of data science for solving social problems.
Planning with Complexity
Paperback
$$
Planning with Complexity: An Introduction to...
Paperback
$$
Planning with Complexity: An Introduction to...
Kindle Edition
$$$

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Rating
3.5 Filled star Filled star Filled star Half star Empty star
Effort
3 to 4 hours per week for 4 weeks
Level
Introductory
Via
edX
Institution
The University of Michigan
Instructor
H. V. Jagadish
Language
English
Transcript
English
Traffic lights
Read about what's good
what should give you pause
and possible dealbreakers
Develops an understanding of the relationship between data science and ethics
Taught by H. V. Jagadish, an experienced expert in data science
Relevant to individuals in various roles, including patients, citizens, and decision-makers
Explores ethical considerations related to data ownership, privacy, fairness, and bias
Provides a strong foundation for understanding the ethical implications of data science
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