To infer is to understand something, not because it is clearly explained but because you can figure it out from the evidence. Making inferences is an important reading skill—and essential in tests like the TOEFL.

I have found inference difficult to explain—until now. Read some of the articles below, or watch the TED talk, for some thought-provoking commentary on how much computer algorithms can infer about us. Then try the Algorithmic Inferences Crossword to practice related vocabulary.

There are a number of fascinating articles and talks that explain the power of these algorithms for good or ill. It was difficult to choose which to mention, but I finally chose the following four. (Several of them also have links to others.)

I was impressed that some of these commentators saw the social and political implications of these algorithms long before the 2016 American election made them obvious. (Zeynep Tufekci discusses their power to make social divisions worse in her 2017 TED talk, minutes 9-12:45. She demonstrates how data collected to target ads to interested people is now being used for other, less harmless, purposes.

A 2013 article in the Guardian notes how data algorithms have been used to increase public safety and solve scientific problems. However, it also points out how algorithms can cause harm or even increase inequality or racial discrimination when they are used to determine things like the probability of future financial trouble, health problems, or criminal behavior. Employers, banks, insurance companies, and courts may use algorithmic computations to make decisions that can affect people’s ability to get jobs, credit, insurance, and even parole from prison.

CBS News looks at algorithms from a different angle: the way they work to capture our attention and keep us interested as long as possible. It's often by appealing to our most negative and primitive emotions (“a race to the bottom of the brain stem.") The article points out how these programs, based on brain science, manipulate us in ways we often don’t recognize, with effects on our well-being & society that are still unclear.

I wasn’t sure whether to include this final short article , but it explains algorithms and what they do in an easy-to-understand way. It calls algorithms “the decision-making parts of code” and points out some major consequences of their power, “found in the way that they sort, filter and manipulate the things that we encounter.” (It also provides great examples of the use of some key academic vocabulary: complex, consequences, manipulate, potential, revelations, visibility, and more.)