Interrogating and Evaluating Resources: Algorithms

What Exactly is an Algorithm? Algorithms Explained - BBC Ideas

Algorithms are step-by-step instructions that computers follow to complete tasks, solve problems, and make automated decisions. They use data to make predictions about people, including their preferences, attributes, and behaviors. Algorithms power nearly everything we see online, including search engines, social media, video games, online dating, and smartphone apps. They are used to shape and filter content on the platforms many of us interact with daily, such as Google, YouTube, Instagram, Netflix, Facebook, Amazon, Twitter, and Spotify. For example, algorithms determine which websites you see first in your Google search results, which posts you see on Facebook, and which videos YouTube “recommends” and autoplays for you.

Overview

“Everyone who has accessed the internet has experienced the personalizing actions of algorithms, whether they realize it or not. These invisible lines of code can track our interactions, trying to game our consumer habits and political leanings to determine what ads, news stories and information we see….As tracking practices have become more common and advanced, it has become urgent to understand how these computer programs work and have a widespread impact. How do students understand the hidden filters that influence what they see and learn, and shape what they think and who they are?” (Head et al. 13)

Positive & Negative

As companies, governments, and other organizations continue to collect and analyze massive amounts of our data, the use of algorithms has become pervasive. In fact, many are referring to this period as the “Age of Algorithms” or the “Algorithm Era,” and researchers are considering the significant impacts that these tools may have—both positive and negative.

“We live in an era of ambient information. Amidst the daily flood of digital news, memes, opinion, advertising, and propaganda, there is rising concern about how popular platforms, and the algorithms they increasingly employ, may influence our lives, deepen divisions in society, and foment polarization, extremism, and distrust” (Head et al. 1).

Because we often assume that algorithms are neutral and objective, they can inaccurately project greater authority than human expertise. Thus, the pervasiveness of algorithms—and their incredible potential to influence our society, politics, institutions, and behavior—has been a source of growing concern.

Algorithmic bias is one of those key concerns. This occurs when algorithms reflect the implicit values of the humans involved in their creation or use, systematically “replicating or even amplifying human biases, particularly those affecting protected groups” (Lee et al.). In search engines, for example, algorithmic bias can create search results that reflect racist, sexist, or other social biases, despite the presumed neutrality of the data. Here are just a few examples of algorithmic bias (Lee et al.):

• An algorithm used by judges to predict whether defendants should be imprisoned or released on bail was found to be biased against African-Americans.

• Amazon had to discontinue using a recruiting algorithm after discovering gender bias: The algorithm was penalizing any resume that contained the word “women’s” in the text, because the data was based on resumes historically submitted to Amazon, which were predominantly from white males.

• Numerous articles have examined the role that YouTube’s recommendation algorithm might play in radicalizing viewers.

Weapons of Math Destruction

Cathy O’Neil has written several books on data science, including Weapons of Math Destruction. She was the former Director of the Lede Program in Data Practices at Columbia University Graduate School of Journalism. In the following video [13:11], she explains how algorithms are not fair and objective, and may in fact “automate the status quo” and “codify” sexism and bigotry. She concludes that these secret “black box” algorithms, created by private companies, can hide ugly truths, often with destructive results.

Algorithms decide who gets a loan, who gets a job interview, who gets insurance and much more -- but they don't automatically make things fair. Mathematician and data scientist Cathy O'Neil coined a term for algorithms that are secret, important and harmful: "weapons of math destruction." Learn more about the hidden agendas behind the formulas.

Sources

Head, Alison J., Barbara Fister, and Margy MacMillan. “Information Literacy in the Age of Algorithms.” Project Information Literacy, 15 Jan. 2020. Licensed under CC BY-NC-SA 4.0

Image: “Big Data is Watching You” by ev is in the Public Domain, CC0

“The Era of Blind Faith in Big Data Must End: Cathy O’Neil” by TED is licensed under CC BY-NC-ND 4.0

This chapter is adapted from What are Algorithms? in Introduction to College Research by Walter D. Butler, Aloha Sargent, and Kelsey Smith, licensed under a Creative Commons Attribution 4.0 International License.