Data Science Ethics
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.
What you'll learn
- Who owns data
- How we value different aspects of privacy
- How we get informed consent
- What it means to be fair
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| Rating | 3.3★ based on 3 ratings |
|---|---|
| Length | 4 weeks |
| Effort | 4 weeks, 3–4 hours per week |
| Starts | On Demand (Start anytime) |
| Cost | $49 |
| From | MichiganX, The University of Michigan via edX |
| Instructor | H. V. Jagadish |
| Download Videos | On all desktop and mobile devices |
| Language | English |
| Subjects | Programming Data Science |
| Tags | Computer Science Data Analysis & Statistics Engineering |
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What people are saying
ds101x data science ethics
DS101x Data Science Ethics is a 4-week survey of ethical issues that arise in data science offered by the University of Michigan through the edX MOOC platform.
lacks any academic rigour
However, the course lacks any academic rigour and the introduction to ethics section is far too brief.
lecturer rather than billed
The 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.
problems worth thinking about
This course presents some interesting case studies and raises many data sciences ethical problems worth thinking about.
can earn enough points
You can earn enough points to pass the course without doing the peer-graded assignment.
allow unlimited attempts
Grading is based on 9 quizzes (one for each module) that allow unlimited attempts and a written, peer-graded case study.
edx mooc platform
far too brief
no real prerequisites
There are no real prerequisites to take the course, although some familiarity with data science will give you more insight into the material.
4-week survey
michigan through
algorithmic fairness
The course includes 9 modules that begin with a basic overview of ethics and the history of ethics, followed by discussions of data ownership, privacy, anonymity, data validity, algorithmic fairness and society consequences.
Careers
An overview of related careers and their average salaries in the US. Bars indicate income percentile.
Data 1 2 $50k
Data 2 $50k
Environmental Scientists $54k
Clinical Lab Scientists $62k
Outbreak Response Scientists $72k
scientists $88k
Data Analyst, Data Warehousing $93k
Atmospheric Scientists/Physical Oceanographer $103k
Computer Scientists $105k
Data Administrator / Data Modeler $108k
Data Integration Engineer| Data Warehouse $116k
Senior Research Scientists $164k
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| Rating | 3.3★ based on 3 ratings |
|---|---|
| Length | 4 weeks |
| Effort | 4 weeks, 3–4 hours per week |
| Starts | On Demand (Start anytime) |
| Cost | $49 |
| From | MichiganX, The University of Michigan via edX |
| Instructor | H. V. Jagadish |
| Download Videos | On all desktop and mobile devices |
| Language | English |
| Subjects | Programming Data Science |
| Tags | Computer Science Data Analysis & Statistics Engineering |
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