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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.
Read more
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.
Read more
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.
Register for this course and see more details by visiting:
OpenCourser.com/course/1989hc/data
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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
- Who owns data
- How we value different aspects of privacy
- How we get informed consent
- What it means to be fair
Good to know
Good to know
Know what's good ,
what to watch for , 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
Save this course
Save Data Science Ethics to your list so you can find it easily later:
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Reviews summary
Data science ethics overview
According to students, this overviews data science ethics in a 4-week course. It is knowledgeable, but in need of updating. The use cases are good, but the ethics framework is lacking. Some students recommend having more solid foundations and less subjective discussions.
The course uses good case studies.
"The course gives a great overview of the subject. Good use cases."
This course provides a well-rounded overview of ethics in data science.
"The course gives a great overview of the subject."
"This course presents some interesting case studies and raises many data sciences ethical problems worth thinking about."
The course content is subjective.
"This course is essentially the lecturers subjective opinion on ethical matters and would make more sense as a presentation by the lecturer rather than billed as a course."
The course is in need of some updating.
"Professor is knowledgeable. Course is in need of some updating."
"This is an important subject and I hope that future courses will have more solid foundations, and less subjective discussions."
The course lacks an adequate ethical framework.
"This course presents some interesting case studies and raises many data sciences ethical problems worth thinking about. However, the course lacks any academic rigour and the introduction to ethics section is far too brief."
"This leads to the lack of a solid framework from which the ethical issues presented can be analysed."
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
Show steps
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
Show steps
Review core ethical principles and consider how they may apply to the field of data science.
Browse courses on
Ethics
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
Show steps
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
Show steps
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
Show steps
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
Show steps
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
Show steps
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
Show steps
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
Show steps
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
Show steps
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
Show steps
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
Show steps
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
Show steps
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
Show steps
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.
Review notes and readings from ethics courses
Show steps
Review previous knowledge of ethics to strengthen foundational understanding.
Browse courses on
Ethics
Show steps
Show steps
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
Show steps
Review core ethical principles and consider how they may apply to the field of data science.
Browse courses on
Ethics
Show steps
Show steps
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
Show steps
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
Show steps
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
Show steps
Seek guidance and insights from experienced professionals in the field of data ethics.
Browse courses on
Data Ethics
Show steps
Show steps
Show steps
- Attend industry events and conferences.
- Reach out to professionals on LinkedIn or other networking platforms.
Read tutorial on data ethics
Show steps
Reading a tutorial on data ethics will help you to understand the ethical considerations of data science.
Browse courses on
Data Ethics
Show steps
Show steps
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
Show steps
Understand the legal and regulatory frameworks governing data privacy to ensure compliance.
Browse courses on
Data Privacy
Show steps
Show steps
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
Show steps
Discuss real-world ethical scenarios and analyze different perspectives to enhance ethical reasoning.
Browse courses on
Ethics
Show steps
Show steps
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
Show steps
Develop critical thinking skills to identify and assess ethical implications in data science projects.
Browse courses on
Ethics
Show steps
Show steps
Show steps
- Examine case studies and real-world examples.
- Conduct ethical impact assessments for potential data science projects.
Complete practice problems on data ethics
Show steps
Completing practice problems on data ethics will help you to apply the concepts you have learned.
Browse courses on
Data Ethics
Show steps
Show steps
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
Show steps
Create a comprehensive policy outlining ethical guidelines for data handling and analysis within an organization.
Browse courses on
Data Ethics
Show steps
Show steps
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
Show steps
Engage in competitions that focus on ethical considerations in data science and AI to gain practical experience.
Browse courses on
Data Ethics
Show steps
Show steps
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
Show steps
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
Show steps
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
Show steps
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
Show steps
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
Show steps
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
Show steps
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 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.
Machine Learning Engineer
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.
Data Analyst
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.
Data Engineer
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.
Product Manager
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.
Policy Analyst
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.
Consultant
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.
Business Analyst
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.
Software 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.
Anthropologist
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.
UX Researcher
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.
Ethnographer
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.
Social Scientist
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.
Lawyer
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.
Journalist
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.
For more career information including salaries, visit:
OpenCourser.com/course/1989hc/data
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.
An overview of data science ethics, including historical and philosophical perspectives.
Save
A practical guide to data ethics and responsible AI development.
A philosophical exploration of the ethical issues surrounding AI.
An examination of the ways in which AI algorithms can perpetuate social and economic inequality.
An examination of the dangers of using big data for social and political purposes.
Save
An exploration of the ethical issues raised by big data, including privacy, discrimination, and algorithmic bias.
An examination of the social and political implications of algorithms.
An introduction to the use of data science for solving social problems.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/1989hc/data
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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
Good to know
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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