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Data Science Ethics

Explore the ethics of big data collection and sharing, and consider the importance of data privacy in our society today.

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Identify the best practices for ethical and responsible data management

This 4-week course will develop your knowledge of data ethics as you explore the questions around the ethics of big data and AI.

Explore the ethics of data collection and data sharing

From developments in healthcare to keeping cities safe, we’ve found a huge variety of useful ways of using data collection and sharing. But how does collecting data affect our personal privacy? And, how much should we trust algorithmic fairness?

Led by experts at the University of Michigan, you’ll use the framework of ethics to analyse the societal consequences of data science and identify why data privacy is important.

Consider how big data is affecting the modern world

As society grapples with defining shared values regarding what is okay and what isn’t when it comes to data, you’ll examine how data impacts on our principles of fairness, accountability, and transparency, and discover why it’s important we develop a shared set of societal values when it comes to data ethics.

While laws will be mentioned in places, this course will invite you to take a compliance viewpoint, where you think not in terms of what one can do (legally), but instead in terms of what one should do.

Learn with the director of the Michigan Institute for Data Science

The leading educator on this course is Professor HV Jagadish, Professor of Electrical Engineering and Computer Science at the University of Michigan and distinguished scientist at the Michigan Institute for Data Science.

Professor Jagadish is well known for his broad-ranging research on information management and has published over 200 major papers and 37 patents.

Whether you’re studying data science or you’re a practising data scientist, you’ll enhance your knowledge of data ethics and privacy with a leading researcher in data science and management.

What topics will you cover?

  • This course will establish a basic foundation in the notion of simple utilitarian ethics and introduce the Principle of Informed Consent
  • This course will examine data privacy and anonymity
  • This course will discuss data validity and algorithmic fairness
  • This course will cover societal consequences of Data Science that we should be concerned about even if there are no issues with fairness, validity, anonymity, privacy, ownership or human subjects research

When would you like to start?

Start straight away and join a global classroom of learners. If the course hasn’t started yet you’ll see the future date listed below.

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Learning on this course

On every step of the course you can meet other learners, share your ideas and join in with active discussions in the comments.

What will you achieve?

By the end of the course, you‘ll be able to...

  • Utilize the framework provided in the course to analyze concerns related to data science ethics.
  • Explore the broader impact of the data science field on modern society and the principles of fairness, accountability and transparency.
  • Examine the need for voluntary disclosure when leveraging metadata to inform basic algorithms and/or complex artificial intelligence systems.
  • Learn best practices for responsible data management.
  • Gain an understanding of the significance of the Fair Information Practices Principles Act and the laws concerning the "right to be forgotten."

Who is the course for?

This course is designed for data scientists and enthusiasts interested in developing their understanding of how data science impacts our society, for better or worse.

Who will you learn with?

Who developed the course?

University of Michigan

As the #1 public research university in the United States, U-M has been a leader in research, learning, and teaching for more than 200 years, with 102 Grad programs in the top 10 — U.S. News & World Report (2019).

  • Established

    1817
  • Location

    Ann Arbor, Michigan, USA
  • World ranking

    Top 30Source: Times Higher Education World University Rankings 2020
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