The seven major data ethics challenges

- Data ethics challenges can come in many different forms. And a lot of it depends on your industry and organization. No one course could cover all of the data ethics challenges. So my goal is to give you the tools you need to tackle the challenges that come your way. Here's a pneumonic to help you remember some of the data ethics challenges. You just need to remember the word Potomac. This pneumonic will give you an overview of the types of data ethic challenges that you'll likely run into in your organization. The P in Potomac stands for privacy. The O stands for data ownership. The T is for algorithmic traceability. The next O is for data objectivity. The M is for data misuse. The A is for data accuracy. And finally the C is for consent. You're certainly going to run into at least some of these common ethical challenges in every organization that collects data. In my previous data ethics course we talked about privacy and data ownership. Privacy is how much data can be collected and shared with those outside your organization. Data ownership is about some of the ethical challenges around who owns your data. This course will go over the T and the second O in Potomac. These are the ethical challenges around algorithmic traceability and data objectivity. First let's look at algorithmic traceability. These days, data processing technologies can make decisions about your customers in milliseconds. So if your customer is denied a loan based on an algorithm do you have an ethical responsibility to tell them why they were denied? Do you need to trace back your decisions or can you simply point to the machine? Second, you'll see challenges around data objectivity. Does your organization need to ensure that data is objective? Most of the data you collect will be describing human activity that is subjective and biased. Should your company try to correct for that bias? We won't dive into them fully now, but the last three letters in Potomac deal with data misuse, accuracy and consent. There are plenty of opportunities to misuse data. Should insurance companies have access to your credit card information so they can see if you're leaving a healthy lifestyle? Does your company need to make sure that the data uses is accurate? Should you correct false data or simply trust what the customer provides? Finally, there are the data ethics issues around consent. Your customer might hit the agree button when they use your software. But how does an organization really know when your customer has consented to sharing their data? Each of these groups has their own data ethics issues. That's why having a good understanding of different ethical theories can help you come up with your own strategies on how to deal with your organization's challenges.