Author: Steven Tiell
Publisher: Ethics of Data
Publication Year: 2020
Summary: The following visualization focuses on how a lot of terms surrounding the ethical considerations of data seem interchangeable, yet educating ourselves on what really constitutes ethical data is not something we always consider. Each term has nuance that makes it unique, but they are also all interconnected in a data ethics framework. At the core of it all is ethical artificial intelligence (AI), meaning practices used to make decision-making systems fair, equitable, and effective. Data ethics relies on remedying concerns with data cleaning and manipulation, in addition to the facets of ethical AI. Digital ethics refers to how the correctness of how findings are communicated, in addition to the facets of data ethics. The umbrella term of it all is responsible innovation, whereby companies must do all of the aforementioned facets but also build trust within their customer base that their data will be used and communicated ethically and the underlying algorithms are deployed ethically. In this sense, businesses should strive for responsible innovation of AI and machine learning technologies, rather than just ethical AI or data ethics.
