In Dedense of Algorithms: THEY'RE GOOD FOR US. THEY MIGHT EVEN BE GOOD FOR DEMOCRACY.

• Author: Brown, Elizabeth Nolan

WHEN FACEBOOK LAUNCHED in 2004, it was a fairly static collection of profile pages. Facebook users could put lists of favorite media on their "walls" and use the "poke" button to give each other social-media nudges. To see what other people were posting, you had to intentionally visit their pages. There were no automatic notifications, no feeds to alert you to new information.

In 2006, Facebook introduced the News Feed, an individualized homepage for each user that showed friends' posts in chronological order. The change seemed small at the time, but it turned out to be the start of a revolution. Instead of making an active choice to check in on other people's pages, users got a running list of updates.

Users still controlled what information they saw by selecting which people and groups to follow. But now user updates, from new photos to shower thoughts, were delivered automatically, as a chronologically ordered stream of real-time information.

This created a problem. Facebook was growing fast, and users were spending more and more time on it, especially once Apple's iPhone app store brought social media to smartphones. It wasn't long before there were simply too many updates for many people to reasonably follow. Sorting the interesting from the irrelevant became a big task.

But what if there were a way for the system to sort through those updates for users, determining which posts might be most interesting, most relevant, most likely to generate a response?

In 2013, Facebook largely ditched the chronological feed. In its place, the social media company installed an algorithm.

Instead of a simple time-ordered log of posts from friends and pages you followed, you saw whichever of these posts Facebook's algorithms "decided" you should see, filtering content based on an array of factors designed to suss out which content users found more interesting. That algorithm not only changed Facebook; it changed the world, making Facebook specifically-and social media algorithms generally--the subject of intense cultural and political debate.

Nearly a decade later, the list of social ills blamed on algorithms is a long one. Echo chambers. Political polarization. Misinformation. Mental health problems. The election of Donald Trump. Addiction. Extremism. Teen suicides. The election of Joe Biden.

Headlines are full of warnings about algorithms. They "are controlling your life" (Vox), "amplifying misinformation and driving a wedge between people" (The Hill), fueling "massive foreign propaganda campaigns" (The Conversation), and serving as a "radicalization machine for the far-right" (The Daily Beast), to list a few.

Congress has been fretting too. Tech companies use "algorithms to drive destructive content to children," according to Sen. Richard Blumenthal (D-Conn.). Sen. Josh Hawley (R-Mo.) claims that Google algorithms dictate the outcomes of elections, while Sen. Elizabeth Warren (D-Mass.) says Amazon algorithms are "feeding misinformation loops." And Facebook algorithms "undermine our shared sense of objective reality" and "intensify fringe political beliefs," according to Reps. Anna Eshoo (D-Calif.) and Tom Malinowski (D-N.J.).

Algorithms, especially those used by search engines and social media, have become a strange new front in the culture war. And at the heart of that battle is the idea of control. Algorithms, critics warn, influence individual behavior and reshape political reality, acting as a mysterious digital spell cast by Big Tech over a populace that would otherwise be saner, smarter, less polarized, less hateful, less radical. Algorithms, in this telling, transform ordinary people into terrible citizens.

But the truth is much more complex and much less alarming. Despite the dire warnings found in headlines and congressional pronouncements, a wealth of research and data contradicts the idea that algorithms are destroying individual minds and America's social fabric. At worst, they help reveal existing divides, amplify arguments some would prefer to stay hidden, and make it harder for individuals to fully control what they see online. At best, they help make us better informed, better engaged, and actually less likely to encounter extremist content. Algorithms aren't destroying democracy. They just might be holding it together.

WHAT ARE ALGORITHMS?

AN ALGORITHM IS simply a set of step-by-step instructions for solving a problem. A recipe is a sort of algorithm for cooking. In math, an algorithm helps us with long division. Those are examples of algorithms meant for human calculations and processes, but machines use algorithms too. For computers, this means taking inputs (data) and using the explicit rules a programmer has set forth (an algorithm) to perform computations that lead to an output.

Machine-learning algorithms are an artificially intelligent (A.I.) subset of computer algorithms, in which a programmer will not explicitly spell out all of the rules; some of these, a computer program will find for itself. Uwe Peters of the Leverhulme Centre for the Future of Intelligence at the University of Cambridge has described them as programs "that can find patterns in vast amounts of data and may automatically improve their own performance through feedback."

The big difference between an A.I. algorithm and a recipe is that an algorithm can in some sense learn, adapting to new information, in particular to choices made by users. Think of a streaming video service like Netflix. As a brand new user, you'll get watch recommendations based on a certain set of generic criteria--what's popular, what's new, etc. But you'll start to get more personalized recommendations as the Netflix algorithm learns what kinds of shows you like.

Machine learning is why Netflix kept recommending Korean dramas to me after my K-pop-obsessed mother-in-law used my account for a month (sigh). Algorithms are why Amazon keeps recommending libertarian-leaning books to me and my Instagram ads are full of pretty dresses, day planners, and baby gearall things I am likely to click on. Without algorithms, I may have to wade through romance novels and politicians' biographies to find things I want to read; I might be served ads for men's boots, baseballs, and adult diapers.

The modern internet offers seemingly endless examples of sophisticated algorithms. Search engine results are based on algorithms that determine what is most relevant and credible on a given query. Algorithms determine what videos surface most on TikTok and what posts show up in your Twitter feed. But their roles go far beyond social media. Map apps use algorithms to choose the best route, Spotify uses them to choose what to play next, and email services use them to discard spam while trying to ensure you see emails from your boss and your grandmother.

Algorithms also drive many things unrelated to the consumer internet. They power facial recognition programs and medical diagnoses. They help child protective services weigh risk, NASA microscopes identify life, bored office workers generate weird art, and governments sort immigration applicants. Neuroscientists have used them to chart neural connections, judges to determine prison sentences, and physicists to predict particle behavior.

Algorithms, in other words, help solve problems of information abundance. They cut through the noise, making recommendations more relevant, helping people see what they're most likely to want to see, and helping them avoid content they might find undesirable. They make our internet...