## Write A Data Ethics Case Study

## Instructions

You've learned about various [Data Ethics Challenges](README.md#2-ethics-challenges) and seen some examples of [Case Studies](README.md#3-case-studies) reflecting data ethics challenges in real-world contexts.

In this assignment, you'll write your own case study reflecting a data ethics challenge from your own experience, or from a relevant real-world context you are familiar with. Just follow these steps:

1. `Pick a Data Ethics Challenge`. Look at [the lesson examples](README.md#2-ethics-challenges) or explore online examples like [the Deon Checklist](https://deon.drivendata.org/examples/) to get inspiration.

2. `Describe a Real World Example`. Think about a situation you have heard of (headlines, research study etc.) or experienced (local community), where this specific challenge occurred. Think about the data ethics questions related to the challenge - and discuss the potential harms or unintended consequences that arise because of this issue. Optional stretch: think about potential solutions or processes that may be applied here to help eliminate or mitigate the adverse impact of this challenge.

3. `Provide a Related Resources list`. Share one or more resources (links to an article, a personal blog post or image, online research paper etc.) to prove this was a real-world occurrence. Optional stretch: share resources that also showcase the potential harms and consequences from the incident, or highlight positive steps taken to prevent its recurrence.



## Self-Review Guide

Exemplary | Adequate | Needs Improvement
--- | --- | -- |
One or more data ethics challenges are identified. <br/> <br/> The case study clearly describes a real-world incident reflecting that challenge, and highlights undesirable consequences or harms it caused. <br/><br/> There is at least one linked resource to prove this occurred. | One data ethics challenge is identified. <br/><br/> At least one relevant harm or consequence is discussed briefly. <br/><br/> However discussion is limited or lacks proof of real-world occurence. | A data challenge is identified. <br/><br/> However the description or resources do not adequately reflect the challenge or prove it's real-world occurence. |
