2.2 - Quantitative efficiency over qualitative meaningfulness

The last aspect of how algorithmic choice differs from human choice is the difference between efficiency and meaningfulness. As we discussed before, algorithms break down the filtering problem in its most basic elements in order to be able to apply the operations a computer is capable of enacting. Fundamentally, the strength of a computer isn’t in making complex choices — its strength is in making a great amount of very simple choices very fast (see Chapter 1.2). For this reason, the efficiency of an algorithm is defined by the ability of its developer(s) to reduce a complex problem to a set of basic mathematical operations. When choosing which piece of information is more important, algorithms don’t perform holistic analysis — they don’t evaluate a piece of information as part of a whole. They break down defining qualities of a set of information into the most basic components the developers were capable of defining, they look at the metadata (like provenance, category, length, number of views) and compare it with other pieces of information in the dataset to decide the order of importance.

The most important differentiator is the lack of holistic qualitative analysis — the understanding of how certain types of information are interconnected, what importance they might hold at a certain moment in time for the societal understanding of a phenomenon. For example, algorithms can predict that news articles about soccer should be prioritized for certain groups during a soccer championship, but they might miss the societal importance in connecting news articles about national team preparations, reports about hooligan riots, and articles about strikes in a certain country (an example, in the 2016 Euro championship, is public transport companies in Rome, Italy, declaring a full strike at the same time the Italian national team played its first game).

This ability to see patterns of meaning across disparate and diverse sources of information is crucial to our understanding of phenomenons, and it’s been the role of journalists and other human gatekeepers to identify these patterns and extract meaning, or assist the public with the understanding of a phenomenon through conscious filtering choices.