AI's ethics problem: Abstractions everywhere but where are the rules?

Machines that make decisions about us: what could possibly go wrong? Essays, speeches, seminars pose that question year after year as artificial intelligence research makes stunning advances. Baked-in biases in algorithms are only one of many issues as a result. Jonathan Shaw, managing editor, Harvard Magazine, wrote earlier this year: "Artificial intelligence can aggregate and assess vast quantities of data that are sometimes beyond human capacity to analyze unaided, thereby enabling AI to make hiring recommendations, determine in seconds the creditworthiness of loan applicants, and predict the chances that criminals will re-offend." Again, what could possibly go wrong?