Author: Orlando Torres
Publisher: Medium
Publication Year: 2018
Summary: The following article discusses how data scientists must be reactive instead of proactive when it comes to artificial intelligence (AI) tech dangers. He mentions 7 important topics in which we should create questions and be proactive with potential issues: 1). Biases in algorithms; 2). Transparency of algorithms; 3). Supremacy of algorithms; 4). Fake news and fake videos; 5). Lethal autonomous weapons systems; 6). Self-driving cars; 7). Privacy versus surveillance. Some of these are more relevant to us as data analysts and some are less (more general AI ethics), but the inherent bias in algorithms is an important thing to be aware of, and the concept of algorithm supremacy is good to consider — no matter how good an algorithm is, should it ever/when should it be trusted over the judgement of a human?
