Author: Jeffrey Saltz, Neil Dewar, Robert Heckman
Publisher: Association for Computing Machinery (ACM) Digital Library
Publication Year: 2018
Summary: The following article features reviewed published codes of conduct and ethics in data science by the authors to create a list of the top 12 areas that should be covered in a data science ethics curriculum. They note that no single code or framework published address all 12 themes simultaneously. They encourage educational programs in data science to cover these 12 themes in their curriculum. The 12 themes are: 1). Professional conduct; 2). Duty to client; 3). Duty to industry; 4). Privacy and anonymity; 5). Data misuse; 6). Data accuracy and validity; 7). Personal and group harm; 8). Subjective model design; 9). Model misuse; 10). Aggregation; 11). Consent; and 12). Newness of field/the unknown unknowns.
