Big data can make big mistakes.

In writing the book, O’Neil has a big advantage. She is a data scientist and knows whereof she speaks. Big data does not lead to the truth. It just leads to a different truth. By definition, algorithms feeding off data inputs can tell us useful things about the areas giving rise to that data. But what if those data inputs are proxies since the actual data is not available? What if the algorithms are applied to different situations that merely have superficial similarities to the environments giving rise to the original data? O’Neil chronicles the resultant mistakes. Alarmingly, her findings encompass recruitment, college applications, advertising, law and justice, employment, access to credit, insurance and politics. In short, the sloppy or negligent use of big data can damage or misrepresent every aspect of our lives. Such misuse also increases inequality. So far, governments are doing little to remedy this situation.

Link to book:

You may like to browse other AI books: