1. Data ethics and privacy
In this chapter, we will further explore the world of data.
2. Basics of data ethics
So far, you've learned that data can be used to drive decisions and make an impact at scale. Yet, this powerful resource comes with responsibilities.
How can organizations ethically
3. Basics of data ethics
collect,
4. Basics of data ethics
store, and
5. Basics of data ethics
use data? This is what data ethics is all about. Data ethics allow us to catch unethical data collection, storage, or use. Doing so will protect customers' safety and save organizations from legal issues.
6. Principles of data ethics
So, what does data ethics mean in practice? The world of data ethics is constantly evolving and there isn't one clear consensus on what data ethics entails.
7. Principles of data ethics
One approach to data ethics breaks it into five key principles: permission, transparency, privacy, intention and outcome.
8. Permission and transparency
The first principle, permission, breaks down simply to asking for user consent before collecting data. Ethical data collection requires users to always be in control of their data and consent to giving that data away instead of having it taken from them.
In addition to getting permission, being transparent with customers about how you plan to use, store, and collect their data allows them to decide if they want to share their data or not. A lack of transparency exposes organizations to reputation damage and legal issues when users realize their data is not being used properly.
9. Data privacy
At its core, data privacy requires individuals to be in control of how their data is collected and used. In this case, data privacy specifically applies to your personal identifiable information (PII in short). PII includes your full name, birthdate, ID card number, phone number... When you share these pieces of information with someone else, you don't want them to be publicly available.
Therefore, data privacy requires that organizations must put in place controls over the data they collect to ensure that sensitive data is well protected.
10. Privacy protection
But even if you manage to store data in a high-end encrypted database, meaning that it has been translated into another form, so that only people with a digital key can read it, mistakes can happen.
Simple things, such as using strong and different passwords online and offline, keeping operating systems up-to-date, and browsing Internet and using email with caution are individual responsibilities. So called-data breaches are often caused by avoidable human actions that allowed malicious individuals to retrieve PII or other sensitive data.
There are generally two ways to prevent this. The first one, and perhaps the most effective, is by simply limiting what you share. Phishing emails or ransomware are obvious examples that try to convince you to share PII. But other less explicit ways, such as what you share on social media, is another example.
Pseudo-data anonymization is a second way to protect data privacy. By removing PII from a dataset, the data becomes anonymous, while still allowing to find patterns of interest. In this way, specific data points can't be tracked back to individuals.
11. Intentions and outcome
The last two data ethic principles are intentions and outcome.
Having good intentions ensures that data is collected and used for the right reasons. It is important to think, should I be doing this with data? How will it benefit our customers or society? If you don't have a good answer then you might need to reconsider if your use is ethical.
This leads to the final principle. Even if your intentions are good you must consider and monitor the outcome. Protecting vulnerable populations and ensuring data usage doesn't cause inadvertent harm to individuals is a cornerstone of ethical data use.
12. Let's practice!
Let's do some exercises to test your data ethics understanding.