Author: Danielle Clifford
Publisher: Pinsent Masons
Publication Year: 2021
Summary: The following article discusses how the data ethics challenge spans multiple vectors. One of the most concerning issues centers around the artificial intelligence (AI) and machine learning-powered algorithms that form a key part of many organizations’ operations. These technologies have the potential to revolutionize crucial sectors such as healthcare through automation, increased efficiency, and reduced costs. Businesses should validate where a particular algorithm has originated and carry out due diligence to avoid putting bias into their platforms. Transparency is a key part of any data ethics strategy and applies to why and how an algorithm makes decisions. Data ethics policy needs to be clear, with a central decision outlining an organization’s expectations when handling information. Data ethics emphasizes transparency, and the first step towards this is visibility of the data a company collects, stores, and uses. At the same time, businesses should consider data ownership, considering an individual’s rights over their personal information. When undertaking a data protection impact assessment, companies should examine who needs to see the data, for how long, and what it will be used for.
