Wikipedia:Wiki Ed/George Washington University/DATS 6450 - Data Science Ethics (Fall 2020)

Ethical issues are increasingly at center of developing, deploying and using data science. Efforts to supplement human with artificial intelligence create systems that can impact the wellbeing, happiness, and even the lives of human beings without oversight or failsafe controls. Such systems need more than precision and accuracy: they need to reflect the ethical principles of the world in which we wish to live.

This course introduces a range of ethical topics that are relevant to today’s data scientists, starting a brief introduction to ethical systems, intellectual property and wicked problems. Next, the course analyzes topical ethical problems that have resulted through the deployment of data science and information technology. Finally, the course explores approaches that have been put forth to solve these problems.

Classes are mostly discussions employing the case study method. Labs explore key issues in at the intersection of data science and ethics. Students enrolling in this class should have a working knowledge of Python and machine learning.

Week 1
Welcome to your Wikipedia assignment's course timeline. This page guides you through the steps you'll need to complete for your Wikipedia assignment, with links to training modules and your classmates' work spaces.

Your course has been assigned a Wikipedia Expert. You can reach them through the Get Help button at the top of this page.

Resources:


 * Editing Wikipedia, pages 1–5
 * Evaluating Wikipedia

Create an account and join this course page, using the enrollment link your instructor sent you. (Because of Wikipedia's technical restraints, you may receive a message that you cannot create an account. To resolve this, please try again off campus or the next day.)

Begin a blog about your experiences. You can use discussion questions to frame your entries, or reflect on the research and writing process. Create at least one blog entry each week during the Wikipedia assignment.

This week, everyone should have a Wikipedia account.

Exercise
Evaluate an article

Thinking about sources and plagiarism

Exercise
Choose a topic

Resource: Editing Wikipedia, page 6

Exercise
Add a citation

Finalize your topic / Find your sources

Week 5
Reach out to your Wikipedia Expert if you have questions using the Get Help button at the top of this page.

Resource: Editing Wikipedia, pages 7–9

Everyone has begun writing their article drafts.

Week 6
Guiding framework

Thinking about Wikipedia

Every student has finished reviewing their assigned articles, making sure that every article has been reviewed.

Week 7
You probably have some feedback from other students and possibly other Wikipedians. Consider their suggestions, decide whether it makes your work more accurate and complete, and edit your draft to make those changes.

Resources:


 * Editing Wikipedia, pages 12 and 14
 * Reach out to your Wikipedia Expert if you have any questions.

Week 8
Now that you've improved your draft based on others' feedback, it's time to move your work live - to the &quot;mainspace.&quot;

Resource: Editing Wikipedia, page 13

Nominating your article for Did You Know

Exercise
Add links to your article

Now's the time to revisit your text and refine your work. You may do more research and find missing information; rewrite the lead section to represent all major points; reorganize the text to communicate the information better; or add images and other media.

Continue to expand and improve your work, and format your article to match Wikipedia's tone and standards. Remember to contact your Wikipedia Expert at any time if you need further help!

Week 11
Guiding questions

It's the final week to develop your article.


 * Read Editing Wikipedia page 15 to review a final check-list before completing your assignment.
 * Don't forget that you can ask for help from your Wikipedia Expert at any time!

Week 12
Everyone should have finished all of the work they'll do on Wikipedia, and be ready for grading.

Write a paper going beyond your Wikipedia article to advance your own ideas, arguments, and original research about your topic.