Author: Jack Berkowitz
Publisher: ADP
Publication Year: N/A
Summary: The following article aims to define a framework for data ethics within human resources. Berkowitz lists 5 common principles of data ethics that can help answer the question of “should we do this?” when building models. These principles include transparency (with the customer to let them know what data is being collected, how it’s being used, and what decisions are AI-based); fairness (in the data that we use to make decisions and checking to see if there is bias within the dataset); accuracy (is the data we are using up to date and are representing it accurately in our analysis and not taking the data out of context); privacy (how can we maintain anonymity and secure customer data, so there is no risk of exposure of personal information); and accountability, making sure to comply with laws and regulations and ensuring the integrity of data sources.